Journal Pre-proofs
Nucleation and Growth in Solution Synthesis of Nanostructures – from Fundamentals to Advanced Applications
Ke-Jun Wu, Edmund C.M. Tse, Congxiao Shang, Zhengxiao Guo
PII:
DOI:
Reference:
S0079-6425(21)00045-1
https://doi.org/10.1016/j.pmatsci.2021.100821
JPMS 100821
To appear in:
Progress in Materials Science
Received Date:
Revised Date:
Accepted Date:
1 August 2020
11 March 2021
16 May 2021
Please cite this article as: Wu, K-J., Tse, E.C.M., Shang, C., Guo, Z., Nucleation and Growth in Solution
Synthesis of Nanostructures – from Fundamentals to Advanced Applications, Progress in Materials Science
(2021), doi: https://doi.org/10.1016/j.pmatsci.2021.100821
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover
page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version
will undergo additional copyediting, typesetting and review before it is published in its final form, but we are
providing this version to give early visibility of the article. Please note that, during the production process, errors
may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
© 2021 Elsevier Ltd. All rights reserved.
Nucleation and Growth in Solution Synthesis of
Nanostructures – from Fundamentals to Advanced
Applications
Ke-Jun Wu1,5, Edmund C. M. Tse2,3, Congxiao Shang2,4, Zhengxiao Guo2,3,4 *
1School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, UK
2HKU-CAS Joint Laboratory on New Materials / Department of Chemistry, University of Hong
Kong, Hong Kong SAR, China
3Department of Mechanical Engineering, University of Hong Kong, Hong Kong SAR, China
4The University of Hong Kong Zhejiang Institute of Research and Innovation, Qingshan Lake
Scitech City, Hangzhou 311305, China
5College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027,
China
(Corresponding: zxguo@hku.hk)
Abstract
Nucleation and growth are two important and entwined processes in materials
synthesis and engineering. While understanding of the fundamental mechanisms of
the processes remain challenging, there is a growing demand for much improved
control over and modification of nanostructures with precise geometrical and chemical
features, well-tailored surface properties and functional attributes. To this end, we first
examine the key concepts of the classical and non-classical theories and then
emphasise mechanistic studies of nucleation and growth. Particularly, the state-of-theart imaging, signal and/or data acquisition techniques are discussed, including in-situ
liquid phase transmission electron microscopy, in-situ synchrotron X-ray diffraction,
microfluidic platforms and machine learning. Both quantitative and qualitative
experimental results with high temporal and spatial resolutions provide further insights
into these nanofabrication processes for representative systems, such as Au
nanoparticles and CaCO3, and subsequently guide the rational design and production
of materials with desirable properties. Based on current knowledge, strategies of
leveraging external fields to manipulate the nucleation and growth processes are
presented. Several case studies in important technological scenarios are discussed to
1
inspire further attempts for precisely engineered solutions. Finally, further
understanding of the processes are highlighted along with potential applications and
future perspectives of controlling solution-synthesized nanostructures.
Keywords: nucleation; crystal growth; solution synthesis; co-precipitation; in-situ
characterisations; nanostructure.
1. Introduction
The formation of solids from a liquid solution (subsequently termed as, a solution),
such as crystallisation, precipitation and co-precipitation, is of considerable
significance in nature and in industry [1,2]. Particularly in the chemical industry, 70%
of all solid materials are manufactured via the crystallization and precipitation from
solutions [3]. The overall process is generally described as two sequential events, i.e.
nucleation and growth. Nucleation is the first step in which monomers, e.g. atoms, ions,
or molecules, form a new thermodynamic configuration or structure at the atomic or
molecular level, followed by growth during which monomers are incorporated onto the
surface of the nuclei, which may also coalesce or aggregate, leading to an increase in
size. Generally speaking, the thermodynamic driving force for both nucleation and
growth in solution is the overall reduction in (Gibbs) free energy. Their rates or kinetics
are usually determined by competing factors: the chemical potential gradient between
a monomer in solution and in the new phase, the transport “resistance” of the
monomers in the solution, and the “concentration” of the monomers. In many cases,
nucleation and growth occur simultaneously and thus are dynamically competitive.
The nucleation and growth processes are crucial for controlling precise structural
characteristics and properties of the final solid material and thus pervade all aspects
of the industry that relies upon a specific set of functionalities of these materials. For
example, in the pharmaceutical industry, the bioavailability of tablets (e.g. digoxin
tablets) are strongly dependent on the shape, crystallinity, and hygroscopicity [4]; in
the chemical industry, the selectivity and activity of catalysts (e.g. Pd/Al2O3, Ag/Pd)
are affected by the crystallinity, size, morphology and surface [5,6]; in healthcare, the
properties of nanoscale biosensors (e.g. fluorescent quantum dots and plasmonic gold
nanoparticles) are susceptible to size, shape, crystalline structure, and associated
2
defects, dopants, surface morphology and charge, and density of capping ligands [7].
Numerous successful attempts have been reported for the synthesis of these materials
by a solution-phase route, such as hydro- and solvo- thermal [8], a seed-mediated [9],
a polyol-assisted [10], a template [11], and an electrochemical process [12], but in
order to gain better control over the synthesis leading to materials with optimal
properties for specific applications, it is truly important to understand clearly from the
atomic or molecular level the pathways that lead to the various macroscopic states as
well as the mechanisms that govern pathway selection, especially in complex systems,
e.g. in the presence of external “force” fields.
There are several influential reviews on the topic of nucleation and growth, particularly
in the solidification of melt [13–15]. Here, we focus our efforts on the formation of solids
from liquid solutions, covering both classical and non-classical theories as well as
recent experimental findings with novel techniques and new strategies/case studies of
nucleation and growth (Figure 1). This review aims to guide researchers in the design
of functional products based on the understanding and control of nucleation and
growth pathways that lead to various macroscale properties. In the first part of the
review (Sections 1. Introduction, 2. Classical Nucleation Theory (CNT), 3. NonClassical Nucleation Theories, 4. Classical and Non-Classical Crystal ), the
thermodynamic and kinetic aspects of the classical and non-classical nucleation and
growth theories were discussed briefly for inclusiveness, details of which may be found
from other articles of the volume, such as [references from this volume]. The key
notions, characteristics and limitations of these theories were summarised to facilitate
subsequent analysis. Currently, although it is often possible to correlate experimental
findings with a nucleation and growth theory, no single theory can explain all observed
phenomena and experimental results. This is mainly due to the complexity of the
processes at the atomistic scale and the lack of reliable experimental evidence. Hence,
the second part of this review (Section 5. Experimental Approaches for Nucleation and
Growth Pathway Evaluation) is devoted to the key in-situ techniques adopted in recent
years for detailed assessment of the processes. Although only model materials (e.g.
metal nanoparticles, CaCO3) were selected here, the development of novel in-situ
techniques and their combinations can provide considerable
insight of the
fundamental processes and further corroboration of the theories and potentially more
comprehensive theories. In addition, advanced data acquisition and processing
3
methods (e.g. microfluidic platforms and machine learning) make the study of the
processes more efficient and reliable. In the third part of the review (Section 6. Active
Control of Nucleation and Growth), the mechanism of external fields, such as
mechanical force fields, electric fields and magnetic fields on nucleation and growth
were discussed. Applying an external field to a conventional process enables more
degrees of influence in controlling nucleation and growth in solution. Finally, in the
fourth part of the review (Section 7. Practical Significance of Nucleation and Growth in
), five types of case studies of enhancing material and device performance via
nucleation and growth were discussed. The strategies adopted therein are directly
associated with classical and non-classical theories of nucleation and growth, offering
valuable guidance to other practical cases.
Figure 1. Applications of advanced materials underpinned by nucleation and growth (inserts have adopted parts of
figures from [16–21] )
4
2. Classical Nucleation Theory (CNT)
Classical Nucleation Theory (CNT) is most commonly applied to describe the
formation of a new thermodynamic phase or a new structure from a continuum point
of view. Depending on whether foreign bodies are present, nucleation can be classified
as either homogeneous or heterogeneous (Figure 2). Primary nucleation may occur
spontaneously within a chemically homogeneous system, which is referred to as
homogeneous nucleation. It may be induced in the presence of some foreign bodies,
which acts as the active centre for first monomeric units (e.g. atoms, ions, or molecules)
to attach; this process is referred to as heterogeneous nucleation. A special case in
point is when solute clusters of the same species exist in the system, in which case it
is named as secondary nucleation [22]. Liquid solutions, to some extent, are an
intrinsically uniform medium, which in principle ensures that the nucleation within is
homogeneous. However, due to the presence of multiple heterogeneities at the local
(molecular) level, such as solvent, impurities, different types of monomers and the
container wall, heterogeneous nucleation often occurs within a solution, which is also
more complicated than the traditional solidification of metals, conventional alloys [23]
and even high entropy alloys [24].
Figure 2. Schematic of homogeneous and heterogeneous crystallization processes.
5
2.1 Development of CNT
The pioneering work of CNT was performed during the 1920s and 1930s by Volmer
and Weber [25], Becker and Döring [26] and Frenkel [27]. CNT was initially proposed
to describe the condensation of a vapour to a liquid, and later it has been extended to
other liquid−solid equilibrium systems such as crystallization from saturated solutions.
In the CNT framework, the homogeneous nucleation rate (J) for liquid-solid systems
is expressed in the form of the Arrhenius reaction rate equation as:
∆𝐺 ∗
𝐽 = 𝐾exp ―
𝑘B𝑇
(
)
1
where K is the pre-exponential factor, kB is the Boltzmann’s constant, ∆G* is the
change in Gibbs free energy required for critical cluster formation, and T is the
nucleation temperature.
For a cluster containing n moles of monomer, the change in Gibbs free energy, ∆G, is
based on the chemical potential difference between liquid-solid phases, and the
energy cost of interface formation which can be characterized by interfacial tension σ
and surface area A:
4𝜋𝑟3
∆𝐺 = ―𝑛∆𝜇 + 𝜎𝐴 = ―
∆𝜇 + 4𝜋𝑟2𝜎
3𝑣
2
where v is the molar volume of the cluster, ∆μ is the difference in chemical potentials,
can be expressed as
∆𝜇 = 𝑘B𝑇ln𝑆
3
Here, the supersaturation S is:
𝑆=
𝑎
𝑎∗
4
where a and a* are the activity of the solute in supersaturated and saturated solutions,
respectively.
For minerals and solid electrolytes:
A𝛼B𝛽 = 𝛼A𝑎 + + 𝛽B𝑏 ―
5
Equation Error! Reference source not found. becomes:
6
∆𝜇 = 𝑣𝑘B𝑇ln𝑆 = 𝑣𝑘B𝑇ln
𝑎±
𝑎 ∗±
= 𝑣𝑘B𝑇ln
𝑎𝛼A𝑎𝛽B
( )
1𝑣
𝐾𝑠𝑝
6
where 𝑣 = 𝛼 + 𝛽, is the total number of ions in each formula unit, 𝑎 ± is the mean
activity of the ionic species, 𝑎A and 𝑎B are the activities of cation and anion,
respectively, 𝐾𝑠𝑝 is the solubility product.
When S is greater than 1, ∆G in equation Error! Reference source not found.
exhibits a maximum at r∗ (see Figure 3a), the size of the critical cluster that is in
unstable equilibrium with the supersaturated solution. Under conditions of constant
temperature and pressure, a system will tend to evolve in the direction of decreasing
Gibbs free energy. As shown in Figure 3a, nucleation is actually controlled by the
competition between the negative term, ―4π𝑟3∆𝜇 3𝑣, i.e. the volume energy and the
positive term, 4π𝑟2𝜎, i.e. the surface energy. It can be seen that the behaviour (grow
or re-dissolve) of a newly created solid nucleus in a supersaturated solution is
determined by their size. If the particle size is smaller than r*, it will re-dissolve to
reduce its Gibbs free energy. Likewise, if a particle is larger than r*, it will continue to
grow.
Figure 3. Free energy diagram for nucleation. (a) Dependence of nucleation barrier ∆G* on the radius r for
heterogeneous nucleation. (b) Nucleation barriers ∆G* for both heterogeneous nucleation (red curve) and
homogeneous nucleation (blue curve).
For a spherical critical cluster, the critical size r∗ and critical free energy ∆G* can be
determined mathematically by differentiating ∆G with respect to r and setting it to zero:
7
𝑑∆𝐺
=
𝑑𝑟
𝑟∗ =
∗
4𝜋𝑟3
𝑑 ―
∆𝜇 + 4𝜋𝑟2𝜎
3𝑣
(
𝑑𝑟
4𝜋𝑟3
𝑑 ―
∙ 𝑘B𝑇ln𝑆 + 4𝜋𝑟2𝜎
3𝑣
) (
=
)
𝑑𝑟
=0
2𝜎𝑣
𝑘B𝑇ln𝑆
∆𝐺 =
16𝜋𝜎3𝑣2
3(𝑘𝐵𝑇ln𝑆)2
7
8
9
Virtually, it is almost impossible to remove all foreign bodies (e.g. dust particles,
bubbles, and the wall of the reactor) from a nucleation system, especially in an
industrial environment. Therefore, in practical scenarios, most nucleation occurs
heterogeneously. For heterogeneous nucleation in the CNT framework, the energy
required to overcome for nucleation to occur is significantly decreased (the red curve
in Figure 3b) via a reduction in the surface energy, i.e. 4π𝑟2𝜎. The energy barrier for
heterogeneous nucleation is equal to the product of the nucleation barrier for
homogeneous nucleation and a correction [22,25]:
∗
∗
∆𝐺ℎ𝑒
= 𝜙∆𝐺ℎ𝑜
10
where the correction coefficient Φ is a function of the contact angle [22,25]:
𝜙=
(2 + cos𝜃)(1 ― cos𝜃)2
4
11
As shown in Figure 4, when θ = 180˚, cosθ = -1 and Φ = 1, there is non-affinity between
the nucleated solid and the foreign solid surface, the energy required to overcome for
∗
∗
nucleation to occur is the same as that of homogeneous nucleation, ∆𝐺ℎ𝑒
; by
= ∆𝐺ℎ𝑜
controlling the wetting conditions (90˚ < θ < 180˚ or θ < 90˚), the nucleation free energy
∗
∗
barrier ∆𝐺ℎ𝑒
for heterogeneous nucleation can be tuned within the range of 0 to ∆𝐺ℎ𝑜
,
as well as the nucleation rate. A typical example to avoid unwanted nucleation is the
anti-icing technology using hydrophobic surface (90˚ < θ < 180˚) to increase the
heterogeneous nucleation energy barrier, thus reducing the ice nucleation rate [28].
8
Figure 4. Three-phase contact angle for heterogeneous nucleation on a flat surface: (a) contact angle is smaller
than 90˚, (b) contact angle is between 90˚ and 180˚ and (c) contact angle is equal to 180˚ [29].
Therefore, under the CNT framework, the critical controlling parameters for
homogeneous and heterogeneous nucleation are temperature, interface tension, and
supersaturation which are highly inter-dependent.
CNT is later expanded by LaMer and Dinegar [30] to describe the nucleation and
growth of colloidal particles and nanoparticles. The key concept of the LaMer model
is that nanoparticle formation undergoes two steps, namely the “instantaneous
nucleation” (also known as “burst nucleation”) followed by “diffusion-controlled growth”.
However, agglomeration is not considered in the LaMer model. More importantly, the
LaMer model is the only explanation, even until recently, on how narrowly dispersed
colloidal particles/nanoparticles can be formed via self-assembly. More details about
the LaMer model can be found in the review recently published by Whitehead and coworkers [31].
2.2 Main Shortcomings of CNT
CNT represents an evident trade-off between accuracy and simplicity by adopting
assumptions to simplify the models [32]. The fundamental assumption of CNT is the
so-called capillarity approximation, which considers the following [33]:
1. Clusters are spherical with uniform interior properties same as those of the
nucleated bulk phase;
2. There is a clear interface between the cluster and the solution;
9
3. The interfacial tension of the cluster is identical to the planar interfacial tension,
regardless of the size and shape of the cluster;
In addition, CNT also assumes that:
4. The change in cluster size is due to the adsorption/emission of single monomer at
one time, thus excluding coalescence and break-off of pre-existing clusters (Becker
and Döring model) [26]; and
5. The nucleation rate and stationary distribution of clusters are time-independent.
The main shortcomings of CNT have been reviewed extensively in the literature [32]
and summarised as follows:
1. For certain two-component spherical clusters, e.g. ethanol-water cluster, the surface
of the cluster can show a considerably different composition from the bulk [9]. Schmitt
and co-workers [34] experimentally measured the binary nucleation rate of ethanol
and water mixtures. They concluded that CNT is unable to predict the data accurately,
especially at low ethanol concentrations.
2. In reality, the assumption of steady-state nucleation is not always valid [35]. CNT
fails to describe the nucleation rate when the driving force for nucleation is rapidly
changed where the cluster size distribution cannot relax fast enough to attain the
steady-state form [36]. For instance, molecular dynamics simulations carried out by
Huitema and co-workers [35] have demonstrated that the nucleation rate is equal to
the steady-state nucleation rate at a cooling rate of 15 K/ns while the nucleation rate
dropped by 97% at a cooling rate of 500 K/ns.
3. CNT fails for small clusters containing 20-50 molecules: 1) the properties of small
clusters can differ significantly from those of the bulk phase [37], 2) the cluster shape
can differ from the generally accepted spherical shape [38], and 3) small clusters with
sharply curved surface do not exhibit identical interfacial tension to the planar
counterpart [37].
4. CNT, as initially developed for vapour-liquid systems, considers that density is the
only order parameter that differs between the two phases, thus fails to provide the
information about pathways leading to crystallization from solution. For instance,
lysozyme nucleation in solution in which old and new phases differ by two order
parameters, i.e. density and structure [39].
10
3. Non-Classical Nucleation Theories
Non-Classical Nucleation Theories (NCNTs) were proposed to describe complex
behaviours and phenomena that do not follow CNT, such as intermediate stages
observed experimentally in solution crystallisation. NCNTs are not substitutes for, but
complements to, classical nucleation theories. However, a comprehensive NCNT
applicable in all types of systems has yet to be developed [40]. Although this is an
essential and challenging research area, only limited reports are devoted to improving
the NCNTs.
In CNT, nucleation of solid undergoes a single-step process in which the clusters
attained the critical size become thermodynamically stable and continue to grow
spontaneously (Figure 5a), while in non-classical nucleation theories, more steps were
introduced to describe the intermediate statuses, as observed in experiments [40–42]
and molecular dynamics (MD) simulations [43,44]. In general, depending on whether
the formed intermediates are considered to be thermodynamically metastable or
stable, non-classical nucleation process can be described via two major mechanisms:
a two-step nucleation mechanism and a pre-nucleation clusters concept (Figure 5b
and c). It was generally considered that the dense liquid-like phase in the two-step
nucleation mechanism is thermodynamically metastable, while the pre-nucleation
clusters in the pre-nucleation clusters concept are thermodynamically stable but do
not show an interface boundary [45].
11
Figure 5. Mechanisms for crystal nucleation: (a) Classical nucleation theory, (b) Two-step nucleation mechanism,
and (c) Pre-nucleation clusters concept. [46]
3.1 Two-Step Nucleation Mechanism
The two-step nucleation mechanism was initially proposed by Wolde and Frenkel [47]
based on numerical simulations for protein crystal nucleation. It is suggested that the
first step toward a critical cluster is the formation of a liquid-like phase, which shows
lower nucleation barrier ∆G than the classic nucleus. Wolde and Frenkel [47] propose
a strategy to control the nucleation rate of protein without affecting growth rate by
adjusting the composition of the system (e.g. addition of non-ionic polymer) and
thereby changing the range of interaction, such that a metastable liquid-liquid critical
point changes accordingly. Guided by this, strategies for particle size and morphology
control are proposed by the manipulation of local ligand environments and solvent
environment [48,49].
12
Vekilov and Galkin [50] later provide more experimental evidence for liquid-liquid
phase separation in lysozyme protein crystallization process. They observe the shift
of phase boundary using static light scattering and significantly change the nucleation
rate by adding glycerol and polyethylene glycol into the system, just as suggested by
Wolde and Frenkel [47].
Davey and co-workers [51] have expanded the two-step nucleation mechanism and
applied it to cooling crystallisation of small molecule, i.e. methyl(E)-2-[2-(6trifluoromethylpyridine-2-yloxymethyl)-phenyl]-3-methoxyacrylate. The formation of
two phases, i.e. a solute-rich dark phase and another solute-lean light phase, was
clearly observed. It was further confirmed by gas chromatography compositional
analysis that nucleation occurred in both phases, but the predominant domains are
generally formed in the dark phase.
The presence of liquid-like precursors has also been demonstrated experimentally
[52,53] and computationally [54] for the nucleation of inorganic minerals, mainly
CaCO3. The formation of crystalline carbonate phases from liquid-like precursors was
monitored by in-situ wide-angle scattering (WAXS) and liquid-like precursors were
characterised by transmission electron microscopy (TEM) as shown in Figure 6a.
Based on the experimental phenomena, Wallace and co-workers [54] predict the
formation of a dense liquid phase via liquid-liquid separation in which the nucleation
of CaCO3 occurs. The cluster dynamics obtained from MD simulation are consistent
with TEM observations (Figure 6b).
13
Figure 6. (a) TEM image of liquid-like precursors formed by CaCO3 [53] and (b) Molecular dynamics simulations
for the evolution of dense liquid clusters [54].
In summary, the two-step nucleation mechanism contains two key notations:
1. Two energy barriers need to be overcome: in the first step, dense liquid-like clusters
nucleate, which are metastable with respect to the final crystals; in the second, crystals
nucleate mainly within the dense liquid phase via structural transition;
2. There is a phase boundary between the dense liquid phase and the bulk liquid
phase.
3.2 Pre-Nucleation Clusters Concept
The Pre-Nucleation Clusters (PNCs) concept was first proposed by Cölfen and coworkers [55], although similar phenomena had been observed before for
biomineralization and formation of organic nanoparticles [56,57]. The pre-nucleation
clusters concept is developed based on CaCO3 crystallization by monitoring Ca2+
concentrations at different stages of crystallization in the solution while the
supersaturation slowly evolves with time (Figure 7a). The concentration of free Ca2+
ions increased linearly in the pre-nucleation stage (from t = 0 to the point with a blue
14
arrow in Figure 7a), but was lower than the dosed amount of Ca2+ (the grey dash curve
in Figure 7a), indicating portions of free Ca2+ disappear due to binding with CO32- in a
1:1 ratio (Figure 7b) [55]. Cölfen and co-workers [55] subsequently confirm that the
pre-nucleation clusters have to be considered with a “solute” character, i.e. there is no
interface between the pre-nucleation cluster and the bulk solution. By using analytical
ultracentrifugation (AUC), they further state that the pre-nucleation clusters are
thermodynamically stable as otherwise those clusters could not be detected through
AUC.
Figure 7. CaCO3 crystallization experiment: (a) Presence of free calcium ions measured by calcium ion-selective
electrode at different pH values. The blue arrows indicate the start of nucleation of calcium carbonate, and (b)
Averaged amount of bound calcium and carbonate at pH = 9.00 [45].
Sommerdijk and co-workers [58] first “saw” the presence of pre-nucleation clusters
claimed by Cölfen and co-workers using high-resolution cryo-TEM. Pre-nucleation
clusters with a diameter ranging from 0.6-1.1 nm are observed (Figure 8a and b), and
a small amount of larger particles (< 4 nm) are also detected (Figure 8c). It has been
claimed that the pre-nucleation clusters exist at different stages of CaCO3
crystallisation, even after nucleation.
15
Figure 8. (a) High-resolution cryo-TEM image of a fresh 9 mM Ca(HCO3)2 solution after image processing. Prenucleation clusters are observed. An arbitrary number of clusters are highlighted by black circles. Scale bar, 20
nm. (b) Nonfiltered images representing the zone delimited by the red square in (a). In the high-magnification image,
all particles present are highlighted by black circles. Particle sizes below the detection limit of 0.45 nm (3 times the
pixel size) are considered noise. Scale bar, 5 nm. (c) Particle diameter distribution of the pre-nucleation clusters
observed in the cryo-TEM images, and (d) Radial integration of the diffraction patterns of vitrified aqueous solutions
of (1) amorphous calcium carbonate (green), (2) 9 mM Ca(HCO3)2 (red), (3) water (blue), and (4) 10 mM CaCl2
(black). Vertical (black) lines are drawn to indicate shifts of the diffraction rings of different samples with respect to
that of a vitrified film of pure water [58].
Following the experimental work, Raiteri and Gale [59] reviewed the computer
simulation work published in 2003-2010 about amorphous calcium carbonate and
pointed out that the force fields employed in those papers failed in terms of an accurate
description of the aqueous calcium carbonate systems. Based on the force field
developed in house, Raiteri and co-workers [60] manage to corroborate most
experimental findings, e.g. pre-nucleation clusters are thermodynamically stable, in
their simulations. Gale and co-workers [61] then provide more structural information
about the pre-nucleation clusters using computational simulations combined with
experimental data analysis, and practically point out that the pre-nucleation clusters
are ionic polymers which consist of chains of cations and anions holding together by
ionic interactions.
Experimental and theoretical evidence also seems to suggest the “non-classical”
PNCs pathway for the formation of other inorganic [62–65] and organic crystals [66–
16
68]. A critical review from Gebauer and Wolf [69] has recently been published covering
most experimental and theoretical progress in terms of pre-nucleation clusters concept
until 2019.
In summary, the pre-nucleation clusters concept contains five key notations which
make it different from the two-step nucleation mechanism proposed by Wolde and
Frenkel [70]:
1. PNCs are considered as thermodynamically stable clusters with “solute” character,
and therefore no phase boundary exists between the clusters and the bulk solution;
2. PNCs are mainly composed of solid-forming monomers (e.g. atoms, molecules, and
ions), while they may contain other chemical species;
3. PNCs are molecular precursors which participate in the process of phase separation;
4. PNCs are highly dynamic entities and change configuration on time scales typical
for molecular rearrangements in solution (i.e. within hundreds of picoseconds);
5. PNCs may have encoded structural motifs resembling, or relating to, one of the
corresponding crystalline polymorphs.
4. Classical and Non-Classical Crystal Growth
Particle growth, along with particle nucleation, determine the properties and
characteristics of final products obtained in the system. In addition, the conditions and
rate of crystal growth have a significant impact on product purity and crystal structure
[71].
Under the classical crystal growth framework, crystal size enlargement can also be
attributed to layer-by-layer addition of monomers on an existing crystal surface, and
the thermodynamic driving force, e.g. supersaturation S, determines the growth
mechanism. In reality, however, this classical model captures only part of the picture.
Emerging fields, including nanoscience and biomineralization, have provided
numerous pieces of evidence that contradict the classical theory. Under the nonclassical crystal growth framework, crystal size enlargement can also be attributed to
the assembly of particles by both oriented and non-oriented attachment or aggregation
(Figure 9) [72–74]. The two mechanisms are differently affected by the thermodynamic
17
parameters of the process, i.e. temperature, pressure, and supersaturation, as well as
other variables such as additives in the system.
Figure 9. In classical models of crystal growth, crystals are produced by monomer-by-monomer addition of ions,
atoms or molecules (grey curve). In contrast, non-classical crystal growth occurs by the addition of higher-order
species ranging from multi-ion complexes to fully formed nanocrystals [75].
4.1 Classical Crystal Growth by Monomers
The mechanism of classical crystal growth follows two consecutive steps, namely, a
diffusional step followed by a surface reaction step; the latter is also known as the
particle integration step [76]. The fundamental, thermodynamic, driving force for
particle growth can be represented as the difference in chemical potential between the
standing and the equilibrium states:
∆𝜇 = 𝑘B𝑇ln𝑆 = 𝑘B𝑇ln
𝑎
𝑎
≅𝑘B𝑇
∗
(
𝑎
𝑎∗
)
― 1 = 𝑘B𝑇(𝑆 ― 1)
12
Several theories have been proposed to describe crystal growth [71], including twodimensional growth theories [77],
Burton-Cabrera-Frank (BCF) Model [78], and
diffusion layer model [79] which is mathematically more straightforward than the other
two. The diffusion layer model considers that solute needs to diffuse through the
boundary layer first and then the particle integration step can occur.
To determine the particle growth rate, it is easier to clarify first the dimension of
concern. In general, the particle growth rate (i.e. the linear growth rate with a unit of
length per unit time) is a function of supersaturation. The higher the supersaturation,
the higher the growth rate [80]:
18
𝐺 = 𝑘𝑔(𝑆 ― 1)𝑔
13
where kg is the growth rate constant which is a function of the solubility and
temperature, S is the supersaturation, and the growth order, g, signifies the
mechanism of crystal growth.
At low supersaturation, g is equal to2, resulting in the parabolic growth law. Particle
integration onto a surface is the control step for growth that results in polyhedral
crystals with smooth faces [78]. When supersaturation is increased, the value of g
increases
exponentially
with
supersaturation
[77].
Further
increasing
the
supersaturation, the surface becomes rough and unstable while the value of g
becomes 1. Particle integration onto the surface is no longer the control step due to
the extensive nucleation sites available in the solution, and thus the growth of particle
then follows the diffusion-controlled mechanism.
As can be seen from the expression for the driving force in terms of the difference in
chemical potential (Equation Error! Reference source not found.), which is related
to the differences in temperature and activity, the two transporting processes, i.e. heat
and mass transfer, are coupled in crystal growth. The degree of contribution from the
respective transport process is determined by the degree of condensation of the
environmental phase. Additionally, nucleation or formation of crystals (Equations
Error! Reference source not found.-Error! Reference source not found.) is also
driven by supersaturation and affected by temperature and activity. Therefore,
controlling the supersaturation level as well as heat and mass transfer processes over
time could assist the control of nucleation and growth, thereby providing insight into
how the properties and characteristics of the final products could be optimally tuned.
4.2 Growth by Particle Attachment and Aggregation
As discussed above, at low supersaturation, the generation of a critical nucleus is a
rare event. The growth process is actually integration controlled. Thus, one observes
a simple growth by monomers which interact through Brownian motion and it follows
well the classical growth theory. However, as supersaturation increases, more
complex behaviours between monomers and particles are observed. The particle
growth is attributed to not only the addition of monomers in the solution but also the
19
collision and coalescence with other particles.
A review from De Yoreo and co-workers [75] has demonstrated general concepts
about crystallization by particle attachment (CPA). Critical features of classical growth
theory and CPA can be understood by considering the interplay of free-energy
landscapes and reaction dynamics, as shown in Figure 10. Figure 10A represents
classical growth, in which a monomer-by-monomer growth pathway is observed.
Figure 10B-E represent particle-based pathways, discussing the attachment of various
precursor particles, e.g. oligomers, droplets, amorphous particles, or fully developed
nanocrystals.
Figure 10. Crystallization by a wide variety of pathways. The possible pathways by which monomers form a stable
bulk crystal, and the physical mechanisms that give rise to them, can have thermodynamic (A to C) and kinetic (D
and E) origins. (A) Classical monomer-by-monomer addition, (B) aggregation of metastable particles, such as liquid,
amorphous, or poorly crystalline particles, or oriented (and nearly oriented) attachment of metastable nanocrystals,
(C) crystallization via the formation of a metastable bulk phase, such as a liquid or solid polymorph, (D) kinetically
dominated aggregation of clusters or oligomers, and (E) aggregation of unstable particles whose internal structures
are not those of equilibrium phases [75].
The current available non-classical growth concepts focus on describing the way that
clusters are observed in both mono- and polycrystalline systems. However, the
corresponding rate equations and models describing CPA are still unavailable.
Therefore, a molecular and quantitative understanding of particle-attachment
pathways is still lacking.
5. Experimental Approaches for Nucleation and Growth Pathway
Evaluation
20
One of the main reasons for the lacking of comprehensive knowledge about the
complex nucleation and growth processes can be attributed to the absence of robust
and reliable experimental techniques and consequently experimental data, particularly
for particle size and concentration in a solution. Thus, one of the major research foci
in the field is focused around the development of in-situ experimental techniques with
high temporal and spatial resolutions and how to extract atomic- and micro- level
information to reveal the key steps of particle formation in solution. Also, new
experimental platforms, such as microfluidic devices, were developed to precisely
control and manipulate the nucleation and growth processes and enable a feasible
and fast approach to access the aforementioned in-situ experimental techniques.
Following experimental data acquisition, experimental data could be processed
manually, or more efficiently, via advanced techniques from data science, such as
machine learning (ML).
5.1 Electron Microscopy Techniques
Liquid electron microscopy [81,82] has opened an array of unique opportunities for
examining physical, chemical, and biological phenomena that take place in liquid
phases directly, as it provides a combination of temporal and spatial resolutions of
electron microscopy with the ability to monitor a wet environment. Figure 11 shows the
spatial resolution as a function of the liquid thickness for TEM, STEM, and SEM at 200
keV beam energy. In terms of spatial resolution, when the liquid cell thickness is
greater than 50 nm, STEM generally provides a higher resolution, but TEM could
provide better resolution when that value is less than 50 nm. In terms of temporal
resolution, TEM typically acquires over 10 frames per second, while the dwell time
needed to form each pixel in a STEM or SEM image is typically in the range of 1 - 60
μs.
21
Figure 11. Resolution of different forms of electron microscopy in liquid. The resolution was calculated for typical
TEM and STEM instrument parameters at 200 keV beam energy, and for imaging of Au nanoparticles at the bottom
of a layer of water for TEM, and at the top of the layer for STEM. The resolution obtained in SEM just below the
liquid-enclosing membrane does not depend on the liquid thickness (see text). Experimental data points are shown
for: a. Au nanoparticles in TEM [83], b. STEM with a 30-nm-thick SiN window [84], c. SEM with a 30-nm-thick SiN
window [85], and d. PbS nanoparticles in water imaged with STEM [86]. The error bars represent experimental
errors [82].
The majority of current experimental setups were inspired by the pioneering work by
Williamson and co-workers [87]. They used micro-fabricated hermetically-sealed liquid
cells in a unique TEM sample holder to image the heterogeneous formation of Cu
clusters on a surface during electrochemical plating with a resolution of 5 nm.
Following that, Zheng et al. employed the same TEM capability in a self-contained
liquid cell and showed single colloidal Pt nanocrystal growth trajectories with an
improved resolution in the sub-nanometre range [88], and Evans et al. reported
reproducible control over growth mechanisms that dictate the final morphology of
nanostructures while observing growth in real-time with sub-nanometre resolution
through the implementation of a continuous flow in situ liquid stage [86]. Different from
above studies that employed liquid cells equipped with a viewing window fabricated
from Si3N4 or SiO2, YuK and co-workers later introduced a new type of liquid cell which
was based on entrapment of a liquid film between layers of graphene. Due to the
22
reduced thickness and improved thermal conduction of graphene material, this type of
cell facilitates atomic-level resolution imaging and allows visualization of critical steps
such as site-selective coalescence, structural reshaping after coalescence, and
surface faceting [89]. It also leads to a cascade of successive studies using atomicresolution TEM or STEM [90–92].
A number of investigations using EM-based techniques have corroborated the theories
of classical and non-classical nucleation and growth: Au nanoparticles formation via
classical nucleation behaviour was observed [87][93] (Figure 12a-j); the nucleation of
metal halides [40] and Ag nanoparticles [94] follows the non-classical nucleation
pathway, i.e. pre-nucleation concept and two-step mechanism (Figure 12k-n); growth
via particle attachment and aggregation, i.e. non-classical growth was detected for
iron oxyhydroxide [95] (Figure 12o-v). All the findings demonstrate that EM-based
techniques offer a powerful tool for understanding the processes.
Figure 12. TEM images for materials formation in solution. a-j: During the nucleation of Au nanoparticles, many of
the nascent nuclei fail to reach the point of spontaneous growth and instead fluctuate in size until they disappear
[93]; k-n: A multistep pathway for silver nucleation in solution was observed, a dense liquid phase (in the red
freeform) appears before the formation of silver nanoclusters (in the yellow square) [94]; o-v: typical dynamics of
the attachment process of iron oxyhydroxide. The surfaces of particles I and II made transient contact at many
points and orientations (points 1-1, 1-2, 2-3, and 3-4) before finally attaching and growing together (points 3-5) [95].
5.2 X-Ray Techniques
In-situ X-ray techniques have been developed in recent years for probing the formation
of particles in solution and providing more quantitative information about nucleation
and growth kinetics [96]. While electron microscopy techniques are capable of
studying real-time formation of particles, the information is confined to a limited volume
23
of liquid solution and a small number of particles/clusters. In contrast, in-situ X-ray
techniques characterise large ensembles of particles, providing information with
significant statistical meaning. Various in-situ X-ray techniques were adopted to
specifically explore the nucleation and growth of various materials in solution, e.g.
metal nanoparticles, minerals, and proteins [96–101].
Wu and co-workers [96] have reviewed the applicability of various X-ray techniques,
i.e. X-ray absorption fine structure (XAFS), small-angle X-ray scattering (SAXS), and
wide-angle X-ray scattering (WAXS) for the studies of nucleation and growth of
nanoparticles at different stages of evolution (Figure 13). XAFS technique has been
proven to be a useful tool to provide quantitative information about chemical bonds,
oxidation states, and the coordination environment of the element. This information
provides valuable insights into the mechanism and kinetics of transformation from
precursor to monomer and cluster, especially at the pre-nucleation and nucleation
stages [102]. However, XAFS only probes the first few coordination shells and thus
fails to reveal nanometre-scale structure and dimension of particles which is essential
for the determination of the kinetics of nucleation and growth. In-situ SAXS (details
about this technique can be found in Li and co-worker’s review [103]) is an
extraordinarily useful tool for structural characterisation, e.g. size, shape, and size
distribution of solid particles, especially when the particle size is still relatively small
(i.e. < 10 nm). At the late growth stage, in-situ WAXS technique can also be used to
probe the growth of larger nanoparticles as they usually exhibit strong Bragg
diffractions, yielding discernible WAXS signals from which the evolution kinetics of
both geometrical and crystalline anisotropy could be extracted.
24
Figure 13. Schematic illustration of time-dependent evolution of concentrations of precursor reactant (red),
nanoparticle precursor (green), and size of nanoparticles (blue) involved in a typical synthesis of colloidal
nanoparticles. The lower part highlights the applicability of various X-ray techniques for different evolution periods
[96].
With the aid of in-situ X-ray techniques, more evidence about classical and nonclassical nucleation and growth has been released. Sauter and co-workers [97] have
studied protein crystallization of bovine β-lactoglobulin in the presence of CdCl2 using
in-situ SAXS. They suggest a two-step process of crystal nucleation within an
intermediate that forms first from solution and is later transformed to crystals and
interpret the non-classical growth kinetics mathematically. By combining in-situ XAFS
and SAXS, Polte and co-workers [104] have observed phenomena that are not in
complete agreement with the LaMer model. The citrate synthesis of gold nanoparticles
seems to follow the classical “burst nucleation”; however, in the growth step, the
number of particles decreases significantly after nucleation while only minor Au(III)
was consumed, suggesting the process does not follow the classical theory, and both
the monomer-by-monomer and particle-based pathways of growth may co-exist.
Interestingly, by changing the synthesis protocol and using SAXS and WAXS, Chen
and co-workers [105] pointed out that their results can be well described within the
framework of classical nucleation and growth theory. The kinetic model they
developed gave excellent agreement with experimental results in the literature
[106,107], even part of results from Polte and co-workers [104]. Staniuk and coworkers [108] explored the polyol synthesis of cobalt and cobalt oxide nanoparticles
using in-situ XAFS. Unlike the steady-state nucleation conditions described in CNT,
25
they observed time-dependent kinetics for the formation of Co, Co3O4, and CoO
nanoparticles.
5.3 Other Techniques
Besides in-situ EM and in-situ X-ray techniques, other techniques are also being used
to probe nucleation and growth processes in solution [55,109–112].
Micro-Raman spectroscopy-based techniques are typically used to determine the
vibrational modes of groups in the local environment which reflect the status of ions,
clusters and crystals during nucleation and growth. Lee and co-workers [109]
demonstrated multiple supersaturation-dependent pathways of nucleation in highly
supersaturated aqueous KH2PO4 (KDP) solution using in-situ micro-Raman. By
comparing the Raman spectral shift of P(OH)2 and PO2 peaks, they proposed that the
pathway of nucleation depends on the degree of supersaturation: (i) low-concentration
KDP solution (S < 3.0) to stable KDP crystal (tetrahedral structure), (ii) lowconcentration KDP solution to high-concentration KDP solution to a metastable KDP
crystal (monoclinic structure) to stable KDP crystal. Similar phenomena were also
observed by Zhang and co-workers [110] in the crystallisation process of gypsum
(CaSO4∙2H2O) using in-situ Raman spectroscopy.
By combining crystallisation assays equipped with potentiometry, conductivity, and pH
titration measurements with analytical ultracentrifuge (AUC), Gebauer and co-workers
[55] proposed the pre-nucleation clusters concept based on CaCO3 precipitation
process which has been discussed above in Section 3.2 Pre-Nucleation Clusters . The
combination of these techniques allows quantitative assessment of ion association
and thermodynamic solubility products in different stages of precipitation (mainly with
ion-selective electrodes) and targeted access to distinct precursor species and
intermediate stages (with AUC) [113].
5.4 Microfluidic Platforms
Microfluidic technology, e.g. single-phase microfluidics and droplet microfluidics
(Figure 14), provides an alternative platform for investigation of nucleation and growth
[114]. Compared to traditional platforms, microfluidic devices offer many advantages,
26
such as high surface-to-volume ratio, fast heat and mass transfer, small sample usage,
and high throughput [115]. Despite the intrinsic limitation of solid handling [116], it has
been reported that microfluidic devices can be successfully applied to the analysis of
nucleation and growth of proteins [117], pharmaceutical compounds [118], and
nanoparticles [119]. Microfluidic devices could be fabricated from various materials
(e.g. glass and silicon, PDMS, PMMA, Teflon PFA/FEP). The transparency of the
material to light, X-ray, and electron allows one to use most electron microscopy and
spectroscopy tools (Figure 15) [114,119–122].
Figure 14. (a) Typical single-phase microfluidics for continuous crystallization of active pharmaceutical ingredients
[123], (b) Typical droplet microfluidics for the investigation of nucleation kinetics of potassium nitrate crystals [124].
Figure 15. In-situ microfluidic cells used in spectroscopy and microscopy [122].
In order to obtain kinetic information of nucleation and growth process, microfluidic
devices usually are integrated with spectroscopic systems. Ioannis and co-workers
[125] have established a droplet-based microfluidic system including PTFE tubing as
the main reactor for online kinetic measurements in colloidal crystallisation. By using
on-line absorbance and PL modules, timescales for nucleation and growth of PbS QSs
have been determined (Figure 16a) and a two-stage reaction mechanism has been
27
revealed (Figure 16b and c). Sultana and Jensen [123] have adopted a single-phase,
PDMS microfluidic device and integrated in-situ optical microscope for determining the
size and polymorphic form of glycine crystals. As shown in Figure 17, habit evolution
of α-glycine over time can be monitored and its growth rates along the {011} and {010}
faces can be calculated by measuring lengths of crystals in the corresponding
directions. Because nucleation is a stochastic process, statistical measurements have
to be performed. Droplet microfluidic devices, e.g. microfluidic tubes [126,127] and
microfluidic chips [124,128] offer the possibility to perform high-throughput nucleation
studies. Rossi and co-workers [126] derived crystal primary nucleation kinetics by
probability distribution functions under stagnant (motionless droplet) and flow (moving
droplet) conditions:
𝑃𝑇(𝑡;𝑆, 𝑉) = 𝑀 + (𝑡;𝑆, 𝑉) 𝑀 = 1 ― exp[ ―𝐽(𝑆)𝑉𝑡]
14
where P is the theoretical probability that at a given time t at least one crystal is present
in a droplet of volume V containing a mixture at supersaturation S. 𝑀 + (𝑡;𝑆, 𝑉) is the
number of droplets in which at least a crystal forms within a time t and M is the overall
number of droplets. By using high resolution optical microscopy, primary nucleation
rates can be determined experimentally, as shown in Figure 18.
Figure 16. Nucleation and growth kinetic studies of PbS QDs using absorption and fluorescence measurements.
Temporal evolution of (a) absorption spectra at 130 °C, (b) position of the emission peak, and (c) average size of
PbS QDs [125].
28
Figure 17. Habit evolution of α-glycine over time when bipyramidal seeds were grown in the presence of 1% (S)glutamic acid (top row) and 2% (R,S)-methionine (bottom row). Scale bars are 10 μm [123].
Figure 18. (a) Droplet arrays in 1 mm PFA capillary tube, and (b) adipic acid nucleation rates determined by fitting
experimental points of the cumulative distribution function at different residence times for various supersaturations
with the theoretical cumulative distribution function.
Optical based techniques however provide limited information regarding compositional
29
and structural characteristics, and thus alternative techniques, e.g. X-ray, Raman, and
EM, are also adopted. Similar to the application for batch nucleation and growth
studies, microfluidic-coupled X-ray based techniques enable the collection of timeresolved, serial absorption/diffraction/scattering patterns from a stream containing
growing crystals, e.g. calcium carbonate crystals [129], proteins [130], and ZnO
nanoparticles [119]; microfluidic-coupled Raman spectroscopy enables the monitoring
of crystallisation conditions and polymorphic transformations of succinic acid crystals
[121]; microfluidic-coupled EM enables the tracking of morphological, structural and
chemical changes of solids in liquids in real time [131].
5.5 Machine-Learning (ML) for Experimental Data Mining
The advent of the in-situ techniques and high throughput microfluidic platforms for
nucleation and growth study leads to an exponential increase in the volume of data
sets. Taking full advantages of such data acquisition technologies and large data sets
requires advanced techniques from data science, such as Machine-Learning (ML)
[132–135]. The rationale behind the use of ML is to develop algorithms to learn and
improve its accuracy from large sets of data in order to predict efficiently useful
information, without or with limited human intervention. Compared with the
applications of ML in other areas, such as image and speech recognition [136,137]
and web-searches [138], the introduction of ML to materials science, especially to the
study of nucleation and growth, is still recent. In the realm of nucleation and growth, a
particular area of strength of ML is the image and spectral analysis of data from the
aforementioned data acquisition techniques [134,139]. Wijethunga and co-workers
[134] have developed a crystal face identification method in epitaxial crystal systems
(i.e. Acetaminophen (APAP) grown on D-mannitol (MAN), D-galactose (GAL), and
xylitol (XYL) substrates) based on Raman spectroscopy combined with ML (Figure 19).
By comparing the Raman spectra to those within the built library, the authors have
determined the identity of unknown crystal faces obtained under actual experimental
conditions, which helps to evaluate the morphologies applicable to control the
nucleation and growth. Yao and co-workers [139] applied U-Net neural network (a ML
model) for Au nanoparticle segmentation in liquid-phase TEM videos (Figure 20). They
have adopted three types of nanoscale dynamics, including motion, chemical reaction,
and self-assembly of nanoparticles as proof-of-concept tests and have mapped
interesting properties for anisotropic Au nanoparticles with different shapes, including
30
an unexpected kinetic pathway of nanoparticle assembly, i.e. first-order chaining
assembly.
The application of machine-learning aided experimental data mining for the nucleation
and growth study is still under active development. The success of such ML models
depends mainly on the quantity and quality of data sets (i.e. training, validation, and
testing sets), which are restricted by the temporal and spatial resolutions of
experimental techniques, and this turns out to be one of the major challenges in
material informatics [140]. Further advancement will also come from in-situ or
operando data acquisition and analysis from high resolution imaging and
spectroscopic techniques.
Figure 19. Comparing the results obtained with Raman indexing with respect to single crystal X-ray diffraction
(SCXRD) results of the APAP-XYL epitaxial crystal pair; (a) XYL face identified by SCXRD, (b) APAP face identified
by SCXRD, (c) comparison of the Raman spectra obtained for the APAP attached XYL face to the {0-10} face from
the Raman library, and (d) comparison of the Raman spectra obtained for the APAP face to the {001} face from
the Raman library. [134]
31
Figure 20. Schematic of U-Net-based image segmentation for liquid-phase TEM videos
6. Active Control of Nucleation and Growth
Apart from controlling temperature and chemical environments, several other active
control techniques (Figure 21) have been employed to manipulate the nucleation and
growth processes. Those are discussed in the following to highlight their effectiveness
for the control of nucleation and growth processes.
Figure 21. Controlled homogeneous N&G, heterogeneous N&G and heterogeneous N&G on the substrate via the
application of microwave, ultrasound, magnetic, laser, thermal fields and bio-functional ligands.
6.1 Magnetic Field
The main purpose of introducing a magnetic field during nucleation and growth in
solution is to utilise the Lorentz force and the magnetization force. The former is
32
induced by moving electrically conducting fluids, however, for non- or poorly
conducting solutions, the effect of Lorentz force on nucleation and growth may be
negligible. In contrast, magnetization force can be applied to even non-ferromagnetic
matters in the same direction with or the counter direction to the gravitational force in
the presence of an inhomogeneous magnetic field [141,142].
Recently, Wu and co-workers [143] have systemically investigated the effects of a high
magnetic field (HMF) on nucleation and growth of FePt nanoparticles via wet-chemical
synthesis. By applying HMF (up to 6 T) at different synthetic stages, they managed to
distinguish the function of HMF on nucleation and growth separately and proposed
potential mechanisms based on their experimental findings:
1. During the nucleation stage, if the process is assumed to follow homogeneous
nucleation under the CNT framework, nucleation rate can be described by combining
Equations Error! Reference source not found. and Error! Reference source not
found.
(
𝐽 = 𝐾exp ―
(
)
∆𝐺 ∗
16𝜋𝜎3𝑣2
= 𝐾exp ― 3 3
𝑘B𝑇
3𝑘𝐵𝑇 (ln𝑆)2
)
15
where both the interfacial tension σ and the supersaturation S can be altered by HMF.
They claim that the nucleation rate in Equation Error! Reference source not found.
could be affected by both the Lorentz force and the magnetization force: as both the
precursors and the nuclei can be magnetized, σ of FePt crystals will be influenced,
although the change may be small, by magnetic field induced Zeeman energy. Lorentz
force may increase the reduction reaction rate by controlling diffusion and convection,
therefore increasing local supersaturation in solution, which can also facilitate
nucleation, leading to overall reduction in grain size, particularly when HMF is applied
at the nucleation stage.
2. During the growth stage, the effects of HMF are more profound. While applying HMF
at only the growth stage, the grain size reduction phenomena were clearer with a
decrease in size of about 20% while the shape of FePt nanoparticles transforms from
cube-like to truncated-cube.
The effects of a magnetic field on growth are further demonstrated by Niu and coworkers [144] in their work on magnetic field-induced synthesis of cobalt
33
nanocrystallites, one of the pioneering reports on the effect of a magnetic field on
nucleation and growth. They synthesised Co nanoparticles in the presence of a
magnetic field (0.25 T) via solvothermal reduction and observed that the spherical
particles tend to align along the magnetic line of force and favour the formation of
linear chains. They claim that the experimental phenomena are observed because
magnetization force makes all the particles orientate along the direction of the force.
Thus dipole-directed self-assembly may occur through dipolar interaction along the
direction of the force, leading to the formation of linear chains. However, they have not
discussed the contribution of the Lorentz force, probably due to the low magnetic flux
density used. Similar phenomena are also observed for Fe3O4 nanowire synthesis
[145].
Besides the application of magnetic field for inorganic materials preparation in solution,
Yin [142] has reviewed the applications of magnetic field for protein crystallization, and
summarises the possible mechanisms related to quality control of protein crystals in
the presence of a magnetic field as follows.
1. The orientation effect: Under a magnetic field, the orientation effect can help to align
microcrystals to the same direction of the growing crystals, thus reduce mosaicity and
improve diffraction quality;
2. Convection control: Due to the magnetization force, the magnitude of effective
gravitational force can be reduced, therefore convection can be suppressed,
contributing to quality improvement of protein crystals; and
3. Reduction of sedimentation and containerless growth: Similar to mechanism 2, by
applying a gradient magnetic field, the magnetization force could reduce the effective
gravitational force, which can then induce levitation and magnetoconvection.
6.2 Ultrasonic Field
Application of ultrasound to nucleation and growth in solution can dramatically affect
the properties of final products. Nalesso and co-workers [146] have reviewed possible
mechanisms of sono-crystallisation in solution recently, at the moment, most theories
are based on the explanation of experimental phenomena. Hence, physical and
mathematical explanations of the process are still lacking.
34
Although the mechanism of using ultrasonic field to control nucleation and growth is
not fully understood, it is widely accepted that cavitation, i.e. the creation of micro gas
bubbles in liquid medium, plays an important role in both steps and all proposed
theories revolve around cavitation:
1. Each microcavity formed in the presence of ultrasonic field could act as an active
site of heterogeneous nucleation for crystallization [147];
2. Cavitation induced micro liquid streaming and turbulence help to enhance mass
transfer rates, subsequently accelerate diffusion controlled growth [148]; and
3. Cavitation could release shockwaves and create local zones with high pressure (~
1000 atm) and temperature (~ 5000 K). The released energy enhances mass transfer
rates and molecular collisions as well as lowers the critical free energy required for
nucleation in the whole system [149].
4. Released shockwaves and micro liquid streaming could assist or inhibit secondary
nucleation by fragmenting crystals or loosening assemblies of monomers [150].
Sonochemical synthesis technique has been adopted for controlled production of
various materials in solution. Dheyab and co-workers [151] recently reported the
formation of the Au shell on Fe3O4 core NPs using powerful ultrasound radiation. Two
positive effects on core@shell-type materials synthesis have been confirmed: 1) the
presence of an ultrasonic field maintains uniform disperse of NPs and avoids
agglomeration of clusters and 2) the presence of an ultrasonic field ensures a uniform
formation of an Au shell on Fe3O4 core. It is because the shockwaves and micro liquid
streaming generated drive Au clusters towards the Fe3O4 surface at very high
velocities, enabling precise control of heterogeneous nucleation on Fe3O4 surface,
rather than homogeneous nucleation in the bulk solution. The production of
biomolecule materials, e.g. lysozyme protein, could also benefit from introducing an
ultrasonic field. Mao and co-workers [152] demonstrated a positive nucleation
enhancement effect of ultrasonic in the lysozyme crystallization process. In the
presence of an ultrasonic field, energy released by the shockwaves could overcome
critical free energy required. Therefore, nucleation could happen under a relatively low
supersaturation, and metastable zone width becomes narrower. In addition, micro
liquid streaming and turbulence help to enhance mass transfer rates between solid
and liquid phases, so that nucleation is promoted. According to the LaMer theory,
35
small but monodispersed crystals will then be generated due to burst nucleation which
was well observed in their work.
6.3 Microwave Field
Microwave (MW) has been widely accepted as an alternative heating method for
volumetric heating with a much shorter heating time required (~ 200 ˚C/min heating
rates) compared with that of conventional heating methods (~ 20 ˚C/min heating rates)
[153]. Theoretically, microwave heating can be applied to any material containing
mobile electric charges, such as polar molecules or conducting ions in a solvent or a
solid. The heating mechanism can be described as follows: molecules and ions tend
to respond to the rapidly changing alternating electric field, therefore, rotation, friction,
and collision of molecules and ions lead to a local temperature increase [154].
Pioneering work on microwave-assisted synthesis can be traced back to 1980s when
Komarnemi and Roy [155] prepared titania gel spheres using a sol-gel method in a
microwave oven.
The effect of microwave field on nucleation and growth in solution can be summarised
via two mechanisms: 1) thermal effect, i.e. rapid heating, overheating, hot spots, and
selective heating [156], and 2) non-thermal microwave effects, i.e. mass transfer
enhancement due to the highly polarising field applied on polar molecules or
conducting ions which may increase the probabilities of effective contacts [157].
Jhung and co-workers [158] have explored the effects, mainly thermal effects, of
microwave irradiation on fast synthesis of porous materials by a hydrothermal method.
By switching between microwave irradiation and conventional electric heating, they
have quantitatively demonstrated that microwave irradiation accelerates both the
nucleation and growth rates of silicalite-1 and VSB-5, while the contribution to
synthesis time reduction by microwave irradiation is more significant in the nucleation
stage. It was also observed that the nucleation of silicalite-1 and VSB-5 crystals follows
the classical LaMer theory [30]. A higher population of nuclei with smaller sizes were
generated in the presence of MW due to the faster reaction rate and higher
supersaturation generated in solution with rapid heating.
Based on the ability of microwave field on nucleation and growth control, more focus
has been shifted to use MW for nanomaterials preparation recently [159–164]. Given
36
the rapid heating feature, Manno and co-workers [161] adopted MW to quickly create
a uniform temperature field (in 15 s vs more than 60 s with conventional heating) for
Ag nanoparticles synthesis via wet chemical reduction. The fast reduction and
nucleation under MW irradiation lead to a smaller but less poly-dispersed product, with
a decrease of 70% in size deviation and 58% in size. It agrees well with the LaMer
theory [30], in which burst nucleation leads to a large amount of smaller nuclei and
avoids the successive nucleation which ensure homogeneity of the resulting
nanoparticles. Given the selective heating feature, Gonzalez and co-workers [165]
reported the use of microwave activated chemical bath deposition (MW-CBD) to grow
a CuO film on conducting glass. This strategy is to suppress homogeneous nucleation
in solution but to promote heterogeneous nucleation on the substrate by preferentially
heating the conducting glass and increasing the temperature to initiate deposition and
nucleation. While using conventional heating, due to the heat transfer mechanism,
homogeneous nucleation in solution could not be avoided which results in material
waste and growth stoppage of the nanostructure as no more monomers are available
for the growth of nanostructures on a seeded substrate. A similar strategy was also
reported for the growth of ZnO nanostructures on Si substrate [166]. Limited evidence
has been released to demonstrate the non-thermal effect on nucleation and growth
control. Nyutu and co-workers [167] demonstrated that nanocrystalline tetragonal
barium titanate (BaTiO3) with particle sizes ranging from 30 to 100 nm could be
synthesised via microwave-hydrothermal routes. It was observed that the properties
of barium titanate, i.e. size, shape, and morphology, are influenced by microwave
frequency. They claimed that it is due to different transverse magnetic modes at
different frequencies. However, the information to support their statement is still limited.
6.4 Electric Field
Electric field applied to a system is actually a carrier of extra energy and will therefore
play a role in the nucleation process by affecting ions and other electrically charged
monomers [168]. Therefore, in the presence of an electric field, the chemical potential
difference based on CNT can be demonstrated as:
∆𝜇𝜀 = ∆𝜇 + 𝑐𝜀𝐸2
16
37
where E is the strength of the electric field, 𝑐𝜀 is a function of the relative permittivities:
𝑐𝜀 =
3𝜀0𝜀m(𝜀c ― 𝜀m)𝑣0
17
2(𝜀c + 𝜀m)
where 𝜀0 is the vacuum permittivity, 𝜀c and 𝜀m are the relative permittivity of the new
solid phase and bulk solvent, respectively.
Therefore, in the presence of an electric field, the critical free energy ∆G* in Equation
Error! Reference source not found. becomes:
∆𝐺 ∗ =
16𝜋𝜎3𝑣2
3(𝑘𝐵𝑇ln𝑆 + 𝑐𝜀𝐸2)
2
18
When 𝜀c > 𝜀m, 𝑐𝜀 in Equation Error! Reference source not found. is positive, the
critical free energy ∆G* is lower than that in the absence of electric field which means
the nucleation process is enhanced; when 𝜀c < 𝜀m, 𝑐𝜀 in Equation Error! Reference
source not found. is negative, the critical free energy ∆G* is lower than that in the
absence of electric field which means the nucleation process is suppressed; if 𝜀c = 𝜀m,
the electric filed does not influence nucleation.
Thus, for systems with existing ions or charged monomers, the application of an
electric field may offer an alternative method to control the nucleation and growth
processes by adjusting the electric field strength and the solvent relative permittivity.
Alexander and co-workers [169] recently reviewed different aspects of how electric
fields control crystallization with an emphasis on protein crystallization. Several
benefits can be summarised as follows:
1. Reduction of nucleation time, i.e. increase nucleation rate, by applying an electric
field when 𝑐𝜀 > 0 [170,171];
2. Locally controlled nucleation can be achieved by creating an inhomogeneous
electric field within a reactor [172,173];
3. Control of product crystal size, quality and yield by adjusting the effective
supersaturation which is the driving force of both nucleation and growth processes
[174,175];
4. Control of crystal orientation via the formation of dipoles in the presence of an
38
electric field [176] and polymorphism by hindering unwanted growth [177].
6.5 Photon Field
In addition to the external fields explored above, photons have also been utilised to
control the nucleation and growth processes of nanomaterials. Typically, lasers are
used to provide energy for nanoparticle formation. Various laser-assisted methods
have been developed to prepare nanoparticles, including but not limited to pulsed laser
ablation at the liquid-solid interface (Figure 22 and Figure 23), laser pyrolysis in the
gas phase (Figure 23), direct laser writing on solid surfaces (Figure 24), and laserinduced forward transfer through space (Figure 25). Recent progress and
development of the four laser-assisted methods for nanoparticle formation are
introduced in detail below with examples of more recent developments for controlling
the nucleation and growth characteristics.
6.5.1 Pulsed Laser Ablation or Deposition
Pulsed laser ablation or deposition (PLA or PLD) provides ample opportunities to
engineer the size and shape as well as physical and chemical properties of the assynthesized nanoparticles [178–180]. The fluence and wavelength of photons as well
as the pulse width and frequency can modulate the size of nanoparticles, while solvent
and solution species such as β-cyclodextrin as well as the solution ionic strength could
regulate the bimodal distribution of nanoparticles formed [181–184]. PLA or PLD was
first investigated by Okada and co-workers to generate nanomaterials [185]. Silicon
spherical particles in the size range between 20 and 500 nm were first fabricated using
pulsed Nd:YAG laser under an Ar atmosphere. Nanoparticles containing elements
other than Si were subsequently fabricated using PLA or PLD for various applications.
For example, FexOy nanoparticles were produced using an ultraviolet (UV) KrF
excimer laser by Shinde and co-workers [186]. A similar method using a UV laser was
employed to generate FeNi nanoparticles[187].
39
Figure 22. Illustration of (a) a pulsed laser deposition chamber [188], (b) a laser ablation system in solution [189],
and (c) a PLD method to generate mixed metal nanoparticles [190].
In addition to producing nanoparticles of containing a single metal, PLA or PLD can
also be used to prepare bi-metallic nanoparticle alloys by introducing metal salts
different from the metal target being hit by the laser in the bulk solution. AgNi alloy
nanoparticles were prepared using a continuous-wave (CW) CO2 laser (10600 nm)
and a pulsed Nd:YAG laser (1064 nm) to process AgNO3 and Ni precursors in ethylene
glycol by Poondi and co-workers [191]. The ratio of components in the resulting bimetallic nanoparticle can be tuned by the concentration of metal salts present in
solution [192,193].
Environmental parameters including pressure and temperature can be used to
modulate the properties of nanomaterials prepared using PLA or PLD. TiOx
nanoparticles synthesized using a Nd:YAG laser under varying helium pressures were
studied systematically. Seto and coworkers found that the physical properties of TiOx
nanoparticle depend on the pressure applied during the laser treatment process [194].
As the helium pressure increases, nanoparticles agglomerated to a higher extent.
Deposition of a film of gold nanoparticles via PLA of an Au nanoparticle solution using
a second harmonic nanosecond pulse Nd:YAG laser was also found to exhibit
pressure-dependent effect. The results indicated that the sizes of as-synthesized Au
nanoparticles were affected by the applied pressure, and the nanoparticle film density
changes from porous to dense as the pressure increases [195]. Apart from pressure,
40
other experimental parameters such as temperature were also investigated. Tsuji and
co-workers observed that an increase in temperature caused the primary particle size
to increase [196].
Figure 23. (a) Real-time shadowgraph and (b) scattering images of the laser-induced cavitation bubble during a
PLA process, and (c) time sequence of PLA events [197].
Apart from preparing nanoparticles free of capping agents, PLA or PLD can be used
to fabricate ligand-stabilized nanoparticles. Colloidal Au nanoparticles were prepared
via ablation of a gold metal plate in sodium dodecyl sulfate aqueous solution using a
532 nm second harmonic Nd:YAG laser. As the concentration of the solution species
became higher, smaller particles were achieved [198].
41
Complex nanostructures can be achieved by the combination of PLA with postmodification methods. For instance, Ni/NiO core-shell structures are synthesized via
PLA and subsequent annealing and oxidation by Sakiyama and co-workers [199].
CoPt alloys are successfully fabricated using a double harmonic pulse laser (532 nm)
ablation method by Seto and co-workers [200]. Upon annealing at 1273 K, CoPt/SiO2
core-shell nanoparticles can be fabricated [201]. Furthermore, carbon-encapsulated
magnetic nanoparticles such as Fe/C, Ni/C and Co/C could be obtained via ablation
of a [M(C5H5)2] precursor solution using a pulse Nd:YAG (355 nm) laser [202]. Fe and
Co nanoparticles have been synthesized using PLA for electrocatalytic oxygen
[189,203]. Clearly, combined processes offer great potential for controlled engineering
of a wide range of nanostructures.
The choice of solvent could play an important role in determining the properties of
PLA-derived nanoparticles. Amendola and co-workers prepared Ag nanoparticles
using a Nd:YAG laser without using reducing agents and stabilizing molecules in
various organic solvents including acetonitrile (ACN), N,N-dimethylformamide (DMF),
tetrahydrofuran (THF), and dimethyl sulfoxide (DMSO). The structure of resulting Ag
nanoparticles depends on the solvent used. Pure Ag nanoparticles free of adventitious
carbon were formed in ACN and DMF. Ag nanoparticles synthesized in THF were
partially covered with an amorphous carbon shell, while in DMSO the nanoparticles
were embedded completely in a carbon matrix [204].
Effect of laser wavelength on laser-prepared nanoparticles has also been explored.
Dikovska and co-workers indicated that Ag nanoparticles synthesized using PLA
method are affected by the processing wavelength. They subjected a silver target to
different harmonic pulse lasers ranging from 1064 nm to 266 nm. They reported that
shorter wavelength (266 nm) was better at generating smaller particles (4 nm in
diameter) that exhibited surface plasmon resonance [205].
In general, this PLA or PLD technique produces nanoparticles in a batch-wise fashion
by projection of a laser beam onto a solid target in a solution or directly at a colloidal
solution. Although PLA or PLD can generate nanoparticles with different compositions,
nanostructures and shapes with and without the use of a reducing agent and
stabilizing molecule, these methods are performed under an inert environment such
as Ar, N2 or He, under careful pressure control, and/or in a liquid solvent. The
modularity of this technique allows nanoparticles of different types of elements to be
42
prepared, yet liquid solvents necessary for this process could result in environmental
waste that might go against the development of green industrial practices. In order to
facilitate the translation of PLA or PLD into an industrial-relevant technique,
overcoming the abovementioned limitations is needed. Upon upgrading this technique
into a continuous production method under ambient condition, PLA or PLD has the
potential to mass produce nanoparticles in an industrial setting with tuneable physical
and chemical properties in a scalable fashion.
6.5.2 Laser Pyrolysis
Gas-phase laser pyrolysis generally requires the use of a sensitizer to absorb photons
and transfer the energy to vaporized reagents to generate nanoparticles that will be
collected downstream using filter membranes or other capturing means [206]. The
identity and vapour pressure of the sensitizer and carrier gas can therefore be used to
control the size of the as-prepared nanoparticles [207].
Figure 24. Illustration of a laser pyrolysis chamber [208].
The sensitizer used can be modulated to determine the physical and chemical
properties of the nanoparticles produced via laser pyrolysis. SF6 gas is a typical
43
sensitizer used in laser pyrolysis to generate magnetic nanoparticles and Si
nanoparticles. Si nanoparticles are prepared via pyrolysis using a continuous-wave
(CW) CO2 laser in the presence of SiH4 assisted by SF6 gas. Silane serves as a
precursor to form ceramic nanoparticles like SiC and SiO2 [208]. Si@C nanoparticles
have been prepared using laser pyrolysis as photocatalysts and as high-capacity anode
materials for lithium-ion batteries, respectively [206,209]. Complex nanoparticles made of
ZrO2, Y2O3:Ce, and TiCxNy can also be obtained using this method [210]. Most nanoparticles
fabricated using the laser pyrolysis method can be done in a reactor filled with metal
pentacarbonyls that serve as precursors of choice. Sulfur hexafluoride (SF6) is typically used
as a photosensitizer because most metal carbonyls do not absorb at 10600 nm.
Sensitizers and carrier gases other than SF6 have also been used in laser pyrolysis. FeC
nanoparticles can also be formed using this method by mixing Fe(CO)5 with C2H2 gas while
irradiated using a CW CO2 laser. Upon applying a CW CO2 laser on nebulized Fe(CO)5 aerogel
precursor, uniform Fe nanoparticles in the size range between 13 nm to 14 nm can be formed
[211]. Borsella and co-workers fabricated MoS2 nanoparticles via pyrolysis using a CW CO2
laser in the presence of Mo(CO)6 and H2S [212]. He and co-workers synthesized Ni
nanoparticles via pyrolysis using a CW CO2 laser and found that the size of nanoparticles
depends on several factors such as laser position, operating pressure, sheath, and purge gas
flow rates [213]. A one-step synthesis of carbon nanocapsules, Fe-containing nanotubes, and
Fe3C nanoparticles has been reported. The Bystrzejewski group used a CW CO2 laser to
irradiate ferrocene and MgO under an N2 flow. The obtained particles need to be further
treated using nitric acid prior to performance testing [214].
Laser pyrolysis is a promising technique to produce nanoparticles in large quantity, though the
volatility requirements on the precursors and sensitizers could limit the versatility of this
technique. However, laser pyrolysis generally involves the use of hazardous chemicals,
thereby posing potential safety concerns for upscaling. Significant capital investment is also
needed in the initial launch phase to set up multi-stage steel reactor chambers. The ability to
prepare multi-component nanoparticles with core-shell or complex structures is restricted to
the availability of suitable precursors, sensitizers, and carrier gases. One benefit of using laser
pyrolysis is that no liquid waste is generated during the process due to the nature of this gas
phase technique.
6.5.3 Direct Laser Processing on Substrates
Direct laser writing allows for direct patterning of surfaces with nanomaterials [215]. Previously
44
used to fabricate graphene-based materials, direct laser scribing is repurposed to enable
nanoparticle fabrication processes. Upon laser scribing, a precursor film, likely a lightabsorbing polymer layer, irradiated by the laser beam will transform into nanoparticles, with
the size controlled by laser treatment parameters and film thickness [216]. HAuCl3 precursor
and polyvinyl alcohol solution were first mixed together and then coated on a glass substrate.
A pulse near-IR (780 nm) Ti:Sapphire laser was used to write directly on the coated glass to
generate Au nanoparticles [217]. Surfaces decorated by nanoparticles generated using laser
direct writing have been used in the field of micro-supercapacitors and wave guides [218,219].
Few papers study the use of direct laser scribing or writing to fabricate nanoparticles as the
main application was focused on polymer carbonization to form graphene.
Figure 25. Schematic of (a) direct laser scribing process [220], (b) laser-induced graphene process [221], and (c)
roll-to-roll direct laser writing process [222].
Laser-induced graphene (LIG) processes could be classified as another direct surface
modification technique to generate graphene via carbonization of polyimide (PI). Recently, LIG
processes were utilized to fabricate nanoparticles. Tour et al. synthesized polyimide thin films
containing metal salts by mixing poly(pyromellitic dianhydrideco-4,40-oxidianiline amic acid)
(PAA) in NMP/aromatic solvent (80:20) with different metal (Co, Fe or Mo) acetylacetonates
under vacuum at 60 °C for 3 days, followed by an annealing step in a CVD quartz tube furnace
at 750 °C under Ar atmosphere. The LIG process was subsequently applied to generate
nanocrystals using a CW CO2 laser. The oxygen reduction reaction (ORR) performance of Co,
Mo, and Fe nanoparticles made via a LIG process were found to on par to state-of-the-art nonprecious metal (NPM) electrocatalysts made using other traditional batch methods [223].
Wang and co-workers prepared Co2+ gelatin hydrogel and further coated the hydrogel onto a
45
PI film surface. A CW CO2 laser was applied by focusing on the coated surface to form Co3O4.
After LIG patterning, a stretchable supercapacitor was generated [224].
The ability to achieve patterned interfaces in a one-step fashion without the use of masks is a
boon to surface science fields in terms of fabrication efficiency and user-friendliness, though
the precursor film preparation steps and the restriction on the precursor mixture could limit the
cost effectiveness and environmental friendliness as liquid toxic waste could be generated.
Specifically, tailored metal salts are needed for the time-consuming LIG process. If the
precursor film formation steps could become eco-friendlier and less complicated, this direct
laser writing method could allow for nanoparticles to be directly generated and deposited onto
a wide selection of substrates ranging from transparent to opaque materials and from
insulating to conducting surfaces in a green manner.
6.5.4 Laser-Induced Forward Transfer
Laser-induced forward transfer (LIFT) is a multistep process that transform a precursor film
into nanoparticles that are then deposited on a neighbouring substrate of choice [225].
Precursor film thickness, laser power, and rastering speed of the laser beam can tune the
nanoparticle size [226,227]. This technique can be coupled to pre- or post- laser treatment
step to generate laser-derived graphene for device fabrication and surface hydrophobicity
tuning [228].
Figure 26. Schematic of (a) the LIFT-assisted nanomaterial preparation (LANP) process, and (b) post laser
treatment to tune surface properties [229].
LIFT can serve as a one-step dry technique to generate carbon-supported metal
electrocatalysts at room temperature and atmospheric pressure within seconds in a green
manner. A 1064 nm CW Nd:YAG laser has been used previously to convert commercial PI
films into Janus graphene membranes in a one-step process for seawater desalination [230].
46
A wearable sweat sensor has been developed using LIFT graphene [231]. A binder-free
supercapacitor has been produced with enhanced conductivity and porosity due to the
underlying LIFT graphene network [232]. A superhydrophobic and oleophilic feature of LIFT
graphene can achieve oil-water separation for oil recycling [233]. Finely dispersed surfactantfree Pt NPs supported on a few-layer graphene carbon matrix are generated using a LIFTassisted nanomaterial preparation (LANP) method, a procedure inspired by the one-step LIFT
technique, as active and robust HER electrocatalysts. Apart from Pt nanoparticles, Ru and Ni
nanoparticles made using LANP have been demonstrated to be efficient electrocatalysts for
oxygen evolution reaction [229]. LIFT is an exciting up-and-coming technique that allows for
the facile synthesis of ligand-free nanomaterials supported on conductive carbon under
ambient condition at room temperature at standard pressure without generating any liquid
waste, though the scalability of this technique has rooms for improvement. One hurdle in
developing LIFT into a universal technique for nanoparticle synthesis is the limited array of
shapes, structures, and morphologies that can be generated. As local heating and rapid
cooling steps are involved, LIFT usually generates spherical nanospheres. This low-cost
electromagnetic wave coupled material transformation (ECMT) method does not require an
ultrahigh vacuum chamber (UHV) or a high-temperature quartz tube furnace. LIFT-derived
nanomaterials are also amenable to post-annealing treatments, thereby enriching the diversity
of nanoparticles to be fabricated and processed using LANP. In addition to zero liquid waste
being generated during the LIFT process, this technique could potentially be scaled up for
industrial applications by incorporating into a roll-to-roll printing or continuous extrusion system.
6.6 Bio-functional Capping Ligands
Capping ligands have longed been used to facilitate nanoparticle formation. Traditional
ligands include cetyltrimethylammonium bromide (CTAB), polyvinylpyrrolidone (PVP),
citrate, and their derivatives have been employed to produce metallic nanoparticles
[234]. The size and shape of which can further be tuned by the temperature, condition,
and kinetics of the reaction as well as the use of other shape-directing agents and
supercritical fluids [235]. Another exciting direction being actively explored is the use
of organometallic cages as nanocapsules for templated synthesis of size- and shapecontrolled nanoparticles via the confinement effect [236].The field of ligand-capped
nanoparticles has been well-described by many reviews, and here the discussion will
be geared toward more recent development on the use of biochemical entities to assist
the nanoparticle nucleation and growth process.
47
Recently, cutting-edge progress has been made at the crossroad between
nanomaterials and biochemistry. Nucleic acids, proteins, and lipids are nanoscale
components critical to supporting life on Earth. Single-stranded DNA (ssDNA) has
been discovered to template the growth of nanoparticles into different sizes and
shapes [237]. Poly-A, poly-T, poly-G, and poly-C ssDNA of lengths between 15-30
nucleotides have been employed as shape-directing agents to toggle the shape of Au
nanoparticles between hexagons and stars as well as dumbbells and pyramids (Figure
27) [238]. Such tuneability on thickness and shape control is attributed to the binding
affinity of oligonucleotides to different crystal planes or faces of the seeds as
nucleation sites [239]. Using a combination of poly-A/T/G/C or oligonucleotides of
different lengths, the size and shape, such as nanoflowers, of Au nanoparticles can
be tailored [240]. Depending on the seed being used, Pd-Au bimetallic core-shell
nano-constructs can be fabricated via a DNA-mediated process [241].
48
Figure 27. Shape-directing effects of DNA oligomers on nanoparticle synthesis [238].
Peptides could potentially provide more control over the size and shape of resulting
nanoparticles when compared to nucleic acids [242,243].The number of naturally
occurring amino acids that make up proteins is significantly larger than the four
available to DNA. With the advent of incorporating artificial amino acids into peptides
via solid-phase peptide synthesis and via amber codon suppression, the binding
strength between peptides and nanoparticle seeds can be tuned precisely (Figure 28).
Lipids have long been known to form nanoscale micelles and vesicles that are used
as drug delivery vehicles [244]. In recent years, the core of lipid constructs can be
switched from liquids to solids. In other words, lipids can be used to coat the surface
of nanoparticles [245]. These nanoparticles have been used for photodynamic and
photothermal therapies as well as enabling theragnostic technologies for cancer
treatment [246].
49
Figure 28. Facet-dictating peptides displaying differential binding affinities towards various exposed crystal faces
of nanoparticles [242].
7. Practical Significance of Nucleation and Growth in Solution
Practical significance has continuously been motivating the studies about nucleation
and growth. Meanwhile, the knowledge from both classical and non-classical
nucleation and growth theories have guided the design and control over different
applications in real scenarios.
7.1 Uniform Lithium Deposition
The quality of Li metal anode (more specifically, the quality of the Li layer on it)
determines the performances of both Li-sulphur and Li-air batteries. The formation of
a uniform and compact Li deposition (i.e. large nuclei size and small nucleation
number density on the substrate) requires accurate control over nucleation and growth
during the Li plating process. Failed to do so may induce severe capacity loss due to
the formation of “dead Li”, more severely, leading to potential safety hazards [247].
Therefore, the control of heterogeneous nucleation and growth of Li shows essential
importance for Li batteries production.
A facile and effective method by merely tuning the deposition temperature was
50
recently proposed by Yan and co-workers [248]. The driving force for Li
electrodeposition can be divided into two main parts, namely the nucleation
overpotential and the plateaus overpotential which is mainly due to mass transfer of Li
ions from the bulk electrolyte to the solid-electrolyte interphase [249] (Figure 29c).
According to CNT, nucleation of a new solid phase needs to overcome a free energy
barrier (Equation Error! Reference source not found.). In the nucleation region, the
volume energy term is closely related to the nucleation overpotential [250]:
4𝜋𝑟3
4𝜋𝑟3
2
∆𝐺 = ―𝑛∆𝜇 + 𝜎𝐴 = ―
∆𝜇 + 4𝜋𝑟 𝜎 = ―
F𝜂 + 4𝜋𝑟2𝜎
3𝑣
3𝑣
𝑟∗ =
2𝜎𝑣
𝐹𝜂
19
20
where F is Faraday’s constant and η is the nucleation overpotential. At the same
current density, Li nucleation overpotential significantly decreases as the temperature
increases from 20 ˚C to 60 ˚C, which leads to a decrease in the free energy barrier
and a more lithiophilic surface (Figure 29c). From Equation Error! Reference source
not found., a clear relationship between critical nuclei size and nucleation
overpotential can be observed which also leads to a cubic relationship between
nucleation number density and nucleation overpotential if assuming spherical nuclei.
The plateaus overpotential in Figure 29c is mainly determined by the current density
and the diffusion properties of Li ions in bulk electrolyte in the post-nucleation growth
stage. At the same current density, plateau overpotential decreases with increasing
temperature, indicating that the Li growth process is promoted at high temperatures
(Figure 29d).
Due to the combined effects of elevated temperature on nucleation and growth stages,
large Li nuclei size and small nucleation number density could be achieved on the
substrate at elevated temperature (Figure 29a), detailed mechanisms of nucleation
and growth at high and low temperatures were proposed as shown in Figure 30. To
further support experimental results, computational simulation demonstrates
numerically the effects of temperature on nucleation, plateau overpotentials (Figure
29d), and nucleation number density (Figure 29b).
51
Figure 29. (a) Statistic histograms of Li nuclei size and nucleation density for Li plating at 0.05 mA cm-2. (b) Change
in Li nucleation densities with temperature. (c) Chronoamperometric comparison of Li nucleation at varied
temperature at 0.05 mA cm-2. (d) Change in nucleation overpotentials and experimental and simulated masstransfer overpotentials with temperature [248].
Figure 30. Schematic illustration of proposed Li nuclei generation and growth mechanism [248].
52
Another strategy for the formation of uniform deposition of Li is to modify the surface
condition of metallic current collectors. Wei and co-workers [251] reported a uniform
Li deposition method recently by coating the current collector, i.e. Cu foil (CF), with a
thin 3 ˚C GaInSnZn liquid-metal layer. Li deposition follows heterogeneous nucleation,
in which the surface condition plays a vital role. In traditional processes using uncoated
CF, due to the use of rough surface with defects which could act as nucleation sites,
Li preferentially nucleate and grow on these defects, resulting in non-uniform Li
deposition and even dendritic Li in the plating process. Therefore, a coating which may
ideally provide a smooth and lithiophilic surface could be a solution. They adopted a
gallium-based liquid-metal alloy as the coating material in their work. The contact
angle was 29.6˚ for uncoated CF, while the liquid-metal-coated Cu foil (LCF) showed
even better wettability with a contact angle close to 0 (Figure 31a). Meanwhile, from
SEM images (Figure 31c and d), it can be seen that the surface became much
smoother after coating compared with that of uncoated CF (Figure 31b). It could be
also be used to explain the decrease in contact angle observed. In CNT, according to
Equations Error! Reference source not found. and Error! Reference source not
found., a lithiophilic surface (contact angle 0 < θ < 90) could significantly reduce the
heterogeneous nucleation energy barrier. Therefore, the presence of the liquid-metal
layer could effectively lower the nucleation barrier and inhibit non-uniform nucleation
of Li from surface defects and growth of Li dendrites in the deposition process.
53
Figure 31. (a) Contact angles of liquid electrolyte on CF and LCF. (b) SEM image of CF. (c and d) SEM images of
LCF [251].
7.2 Synthesis of Supported Metal Catalysts
Supported metal nanoparticles are widely used and investigated as heterogeneous
catalysts in both academic research and industrial applications [252,253] However,
controlling the nucleation and growth steps to tune the size, polydispersity,
morphology, and structure of active sites of supported metal nanoparticles is an
ongoing challenge.
In order to achieve high metal loading while keeping high dispersity and small size of
metal nanoparticles on the support, Cho and co-workers [254] proposed a strategy by
inducing regioselective nucleation of inorganic precursors on the pore walls via surface
modification with basic groups, as shown in Figure 32. The ammonium group
increases the basicity of the porous environment, causing nucleation or local
precipitation of metal hydroxide which is later converted to oxide nanoparticles even
at a low concentration of the precursor species. This strategy managed to get rid of
homogeneous nucleated nanoparticles in the bulk solution which may attach/deposit
54
onto the supports, and introduce heterogeneous nucleation locally to the sites
functionalised with –C3H6–N+(Me)3(OH)- group.
Figure 32. Selective precipitation of metal nitrate precursors on mesopore walls can be realized by functionalization
of mesopore walls with –C3H6–N+(Me)3(OH)- groups [254].
The concept of “single-atom catalysis”, i.e. to downsize supported nanoparticles to the
atom scale to maximise metal atom efficiency, maintain catalytic performance, and
decrease costs, has attracted interests recently [255]. Huang and co-workers [256,257]
presented two examples recently about one-pot solution synthesis of supported
metal/metal oxide catalysts. The logic of their work is similar to that of Cho’ work [54]
which is to avoid homogeneous nucleation in solution in order to get monodispersed
particles/atoms on the supports. The first system they investigated is nitrogen (N)doped mesoporous carbon (NMC) supported atomically dispersed platinum (Pt)
catalysts (Pt/NMC-LT) [257]. Instead of functionalising the support, they employed
ethanol as a mild reducing agent and controlled the reaction temperature at -40 ˚C. It
can be seen from HAADF-STEM images in Figure 33a and b, under -40 ˚C, only
isolated Pt atoms are anchored on the surface of NMC substrates. However, under
room temperature, Pt sub-nanometre clusters were also observed (Figure 33b).
55
Figure 33. HAADF-STEM images of (a) Pt/NMC-LT and (b) Pt/NMC-RT. (c) Schematic illustration of two nucleation
pathways of Pt atoms in ethanol and NMC substrate reaction mixture. (d) Energy diagram of Path-2 for Pt–Pt dimer
formation at -40 ˚C (up panel) and RT (bottom panel). The initial state (IS), transition state (TS), and final state (FS)
are shown from left to right. The ethanol molecules bound with Pt atoms and the NMC substrate are highlighted by
spheres. C, N, Pt, O and H atoms are depicted by grey, blue, light blue, red, and white spheres, respectively [257].
As discussed above, supersaturation is introduced by chemical reaction (reduction)
using weak reductants, i.e. ethanol and decreasing reaction temperature to -40 ˚C
would decrease supersaturation thus increase the critical energy barrier. According to
CNT, the critical energy barrier for heterogeneous nucleation is usually lower than that
for homogeneous nucleation. If well controlled, the critical energy barrier in the system
could be maintained at a specific range to theoretically exclude the possible
involvement of homogeneous nucleation in the bulk solution.
Huang and co-workers [256] also extended the strategy for synthesis of nitrogendoped mesoporous carbon supported clustered CoOx composite catalyst (CoOx/NMC).
A two-step synthetic route for CoOx/NMC was adopted, including the nucleationinhibited solution synthesis of CoOOH/NMC at -40 ˚C and succeeding annealing
process at 500 ˚C under an argon atmosphere. Nucleation was enabled by the redox
reaction between CoCl2 and OH- released by NaBH4 hydrolysis at -40 ˚C. Similar
nucleation environment as their previous work [257] was created: low reaction
temperature and low reaction kinetics. The reaction rate was controlled by the limited
56
releasing of OH- ions as NaBH4 hydrolysis reaction is quite slow at -40 ˚C. They
managed to produce ultrafine CoOx clusters (2-3 nm) on the surface of NMC
substrates, as shown in Figure 34.
Figure 34. HAADF-STEM images at different magnifications of CoOx/NMC with supported ultrafine clusters (2-3
nm) [256].
However, the main issue with this strategy is that the process of catalyst synthesis is
rather time-consuming due to the low temperature and slow reaction kinetics. The
nucleation step requires 12 hours to finish in a typical procedure, as reported [256].
7.3 Morphology and Size Tuning
Inorganic materials exhibit a variety of morphology- and size-dependent properties at
the nanoscale. These properties would eventually determine the performance of these
materials or devices. Therefore, control over these properties via facile and robust
experimental methods is of practical importance in many industries.
By merely tuning precursor solutions for precipitation processes, Lai and co-workers
[258] have managed to manipulate inorganic materials to form either one-, two- or
three-dimensional structures. According to nucleation and growth theories discussed
above, supersaturation is the driving force for both nucleation and growth steps. For
minerals and electrolyte crystals, supersaturation, S, can be written as:
𝑆=
𝑎𝛼A𝑎𝛽B
1𝑣
𝑐𝛼𝐴𝑐𝛽𝐵
( ) ( )
𝐾𝑠𝑝
≈
𝐾𝑠𝑝
1𝑣
21
Where cA and cB can be considered as the concentration of metal cations and
57
dissociated reactant anions, respectively, v is the number of ions in the material’s
formula unit, and Ksp is the solubility product constant. From Equation Error!
Reference source not found., it can be seen that to regulate the concentration of
ions is crucial in controlling the supersaturation, thus the nucleation and growth.
Meanwhile, it is believed that the kinetic effects also influence the processes of
precipitation, by selecting reactants with different electrolytic dissociation values, 𝛼 =
𝐶𝐵 𝐶 , nucleation and growth rates can be controlled.
𝐴𝐵
Lai and co-workers [258] illustrated the formation mechanisms of various
morphologies via tuning two parameters simultaneously, i.e. supersaturation and
dissociation value, in Figure 35.
For weak electrolyte systems (𝛼 ≪ 1), due to the presence of non-equilibrium states,
reactants could slowly but continuously release new ions for the precipitation reaction,
meanwhile, due to the consumption of ions for the precipitation reaction, the reequilibrium of the weak electrolyte would happen and therefore could provide a
consistent driving force for the growth stage. More specifically, there are two scenarios:
1. When a low supersaturation was achieved through a weak electrolyte, it results in
1D growth of the product (Figure 35a, green reaction path),
2. When a high supersaturation was obtained via a weak electrolyte (a relative higher
α compared with scenario 1, but still much less than 1), it leads to 2D growth of the
product (Figure 35a, orange reaction path).
In contrast, for strong electrolyte-based reactants (𝛼 ≈ 1), the solute can completely,
or almost completely, release ions all at once. It results in the absence of a chemical
driving force within the growth stage so that the materials uniformly grow on each axis
and are prone to form 3D isotropic morphologies. There are also two scenarios:
1. When a low supersaturation was achieved through a strong electrolyte, due to their
relatively slow nucleation and growth rate, the precipitates usually have regular shapes
(Figure 35a, blue reaction path).
2. When a high supersaturation was achieved through a strong electrolyte, as both the
nucleation and growth happen very fast, a large number of small irregular particles
forms with the whole process difficult to control.
58
Figure 35. Mechanism of the formation of 1D, 2D, and 3D morphologies. (a) Schematic illustrations of the formation
of 1D, 2D and 3D structures with regular shapes. Green arrow = 1D reaction path; orange arrow = 2D reaction
path; blue arrow = 3D reacting path. TEM images of (b) a BaF2 tube, (c) a hollow BaF2 cube, (d) a porous CaF2
cube, and (e) a holey Co(OH)2 sheet [258].
Another example was reported by Wang and co-workers [72] about the synthesis of
silver particles with controlled morphologies by regulating the pH and reactant
concentrations. Although the strategy they used is slightly different from the one
proposed by Lai and co-workers [258], the key concept is still the same: controlling the
morphologies by tuning reaction kinetics and supersaturation. The relationship
between morphology and supersaturation is shown in Figure 36. At low driving force,
as shown in Equation Error! Reference source not found., when g value is equalto
2, growth follows the parabolic growth law. As nucleation is a rare event, the
integration-controlled growth mechanism would result in mono-crystalline polyhedral
crystals with smooth faces. At high driving force, the growth mechanism changes from
integration-controlled to diffusion-controlled which would result in morphologies of
dendrites and polycrystalline spherulites [259].
59
Figure 36. Morphology change of crystalline particles as a function of the driving force, i.e. supersaturation,
according to classical crystal growth theory [259].
The experimental findings for silver particles precipitation by the reduction of AgNO3
with ascorbic acid (AA) [72] also supported the classical crystal growth theory
discussed above. When constant pH value was used (pH = 1.5), polyhedral silver
particles were observed to be formed when the molar ratio of AA/AgNO3 is equal to
0.5:1 (Figure 37A); further increase the molar ratio of AA/AgNO3 to 5:1 and 10:1, i.e.
further increase the supersaturation, resulted in the formation of dendrites and
spherulites, respectively (Figure 37B and C).
Figure 37. SEM images of silver particles formed at pH 1.5 with different molar ratios of AgNO3/ascorbic acid
(mM/mM): (A) 10/5, (B) 10/50, and (C) 10/100 [72].
When the molar ratio of AA/AgNO3 was kept as a constant, i.e. 5:1, increasing the pH
value of the system changes the final product morphologies dramatically. Although the
oxidation potential of AA slightly decreases with increasing pH, at acidic conditions,
lower pH shifts the reaction equilibrium towards the reactants. Therefore,
supersaturation increases with an increase in pH which consequently results in a
60
gradual shift from integration-controlled growth to diffusion-controlled growth.
Correspondingly, polyhedral, hopper and dendritic crystals were observed,
respectively, as shown in Figure 38A - C. It also agrees well with the classical crystal
growth theory [55]. However, it was also observed that larger particles were produced
under high initial supersaturation which is against the classical nucleation and growth
theory. Wang and co-workers [72] claimed that it might be ascribed to higher
nucleation and aggregation rates within the framework of particle-based growth
hypotheses.
Figure 38. SEM images of silver particles formed at AgNO3/AA = 20 mM/100 mM, where initial pH of the AA solution
was varied at: (A) -0.19, (B) 0.14, (C) 1.39, (D) 1.94, (E) 2.59, (F) 9.16, and (G) 9.78 [72].
7.4 Surface Protection and Modification
The nucleation of CaCO3 on the surface is widely involved in the development of
unwanted inorganic foulants in desalination and the petroleum industries [260][261].
61
Suppressing nucleation, more particularly heterogeneous nucleation, of CaCO3 could,
therefore, be a cost-effective, energy-efficient solution to address inorganic fouling
issues in the water purification and energy fuel sectors.
Zhao and co-workers [262] proposed a novel method to control heterogeneous
nucleation of CaCO3 using polymer coatings via initiated chemical vapour deposition
(iCVD). For fouling tests, Cu/Ni alloy foils were selected as the substrates which have
a similar composition with the tube materials used in heat exchangers and four iCVD
polymers,
namely,
Polydivinylbenzene
trimethylcyclotrisiloxane)
(PV3D3),
(PDVB),
Poly(1,3,5-trivinyl-1,3,5-
Poly(1,3,5,7-tetra-vinyl-1,3,5,7-tetra-
methylcyclotetra-siloxane) (PV4D4) and Poly(1H,1H,2H,2H-perfuorodecyl acrylate)
(PPFDA) were selected as coatings based on their surface energy, film roughness,
and durability.
According to the classical heterogeneous nucleation theory (Section 2.1 Development
of CNT), by controlling the wetting conditions which is usually characterized by contact
angle measurements, the nucleation free energy barrier and nucleation rate of
heterogeneous nucleation can be tuned. It can be seen from Figure 39 (black squares)
that the contact angle is higher than 130˚ for all the four iCVD polymers, indicating that
all the surfaces are not favoured for CaCO3. If we adopt this contact angle as a
reference, and use Equations Error! Reference source not found. and Error!
Reference source not found. to calculate the heterogeneous nucleation energy
barrier, it can be obtained that:
∗
∗
∗
∆𝐺ℎ𝑒
= 𝜙∆𝐺ℎ𝑜
= 0.916∆𝐺ℎ𝑜
22
It means the free energy barrier reduction due to the presence of a foreign body is not
noticeable and these iCVD polymer coatings could effectively inhibit heterogeneous
nucleation of CaCO3.
62
Figure 39. (a) Contact angles of CaCO3 on iCVD polymers calculated from Young–Dupre equation (black squares)
and the energy barrier ratio of heterogeneous nucleation to homogeneous nucleation based on classical nucleation
theory (red circles), and (b) Contact angles of liquids with different known surface tension on iCVD polymer surfaces
[262].
The SEM images shown in Figure 40 further confirmed the hypothesis based on
classical nucleation theory. Compared with uncoated Cu/Ni surface (Figure 40a),
Cu/Ni surfaces coated with iCVD PV3D3, PV4D4 and PDVB (Figure 40b-d) show
significantly reduced amounts of CaCO3 crystals after the fouling test at 110 ˚C, while
iCVD PPFDA coated Cu/Ni surface (Figure 40e) shows promoted heterogeneous
nucleation of CaCO3 for the fouling tests which is due to the hydrolysis of acrylate
polymer in a hot aqueous solution. The loss of passivation leads to the corrosion of
Cu/Ni and further promotes the heterogeneous nucleation.
Figure 40. (a–e) Scanning electron microscopy (SEM) images for (a) uncoated Cu/Ni and (b–e) iCVD coated Cu/Ni
foil surfaces ((b) PV3D3, (c) PV4D4, (d) PDVB, and (e) PPFDA) after CaCO3 scaling tests at 110 ˚C. (f–j) Energy
dispersive X-ray (EDX) mapping images for (f) uncoated Cu/Ni and (g–j) iCVD coated Cu/Ni foil surfaces ((g)
PV3D3, (h) PV4D4, (i) PDVB, and (j) PPFDA) after CaCO3 scaling tests at 110 ˚C [262].
Unlike heterogeneous nucleation of CaCO3 in desalination and petroleum industries
63
which is undesirable, however, the heterogeneous nucleation of inorganic materials is
desired in some medical applications, such as calcium phosphate (the main
component of bone) formation on implant coating surfaces. It is usually considered as
a descriptor indicating whether successful implant osseointegration has been
achieved [263].
Golda-Cepa and co-workers [264] addressed experimentally and computationally the
necessity of treatment of implant coating surfaces, i.e. parylene C surface, in
promoting calcium phosphate formation. Due to the hydrophobicity native of parylene
C surface, it is a challenge for calcium phosphate to nucleate and grow
heterogeneously. According to the classical heterogeneous nucleation theory, a
hydrophobic surface (contact angle greater than 90˚) does not offer a significant
reduction of the free energy barrier. Consequently, it results in a relatively low calcium
phosphate nucleation rate which is comparable with the homogeneous nucleation rate
in the bulk solution. Even the calcium phosphate layer was formed on the surface, the
poor adhesion of calcium phosphate to the parylene C surface would affect its
performance. The strategy proposed by Golda-Cepa and co-workers [264] was to
substitute 50-60% native −Cl groups on the parylene C surface with −OH groups using
plasma treatment, which leads to increased wettability and biocompatibility of the
surface.
The hypothesis is that calcium phosphate formation on a plasma treated surface is
much faster due to the relatively low energy barrier and high nucleation rate according
to CNT. From the experimental characterisation results via SEM and contact angle
measurements, it can be found that after the plasma treatment, the parylene C surface
becomes rough in the nanoscale, with nanocorrugations in the range of 60-200 nm
(Figure 41a), and hydrophilic (Figure 41b), with a water contact angle θW of 0.1° and
the corresponding surface free energy (SFE) of 72.9 mJ/ m2 with 48.6 and 24.3 mJ/m2
polar (𝛾𝑝𝑠) and dispersive (𝛾𝑑𝑠) components, respectively.
64
Figure 41. Oxygen-plasma-modified parylene C surface: (A) SEM morphology, (B) polar and dispersive
components of the SFE determined from the contact angle measurements [264].
From SEM images, it can be clearly seen that the morphologies and sizes of formed
calcium phosphate particles varied on unmodified and plasma treated surfaces (Figure
42A). On unmodified parylene C surface, there are few, large crystallites with 1-3 μm
in diameter, while on the plasma-treated surface, a more significant number of
crystallites, with significantly smaller diameters of 200−500 nm, can be observed due
to the higher nucleation rate (Figure 42B). The phenomena observed agree well with
the classical crystal growth theory.
Figure 42. (A) SEM images of calcium phosphate crystallites formed on unmodified and oxygen plasma-modified
parylene C surfaces, (B) histograms quantifying the differences in size distribution of crystallites [264].
65
7.5 Nano-safety by Design
More and more promising nanomaterials have been introduced to our daily life. This
action was accompanied by concerns on the nanotoxicity underlying effects of
nanomaterials on animals and human beings [265]. In recent years, safe-by-design
nanomaterials has become the subject of rapidly increasing interest in various
research fields and a variety of strategies, including coating, size control, doping,
grafting, loading, managing shape and crystallinity, and reduction of persistence, have
been proposed to control and mitigate the potential hazards [266]. Among these, size
control and managing shape and crystallinity need to be achieved via the control of
nucleation and growth.
One of the most used techniques for nanoparticle size control is the addition of ligands
which affect both the nucleation (e.g. changing interfacial tension and thus nucleation
rate) and growth (e.g. inhibiting particle growth due to agglomeration) [49,267] As
mentioned above, gold nanoparticles (Ag NPs) are usually considered as
biocompatible materials and widely used in healthcare industries [7]. However,
whether ultrafine Au NPs, especially those used in bioimaging with the diameter less
than 1 nm, directly affect neuronal development is still unclear. Recently, Hu and coworkers [268] adopted an X-ray assisted protocol [269] for the ultrafine Au NPs
synthesis using mercaptoundecanoic acid (MUA) as the capping ligand. MUA, a longchain organic molecule with thiol groups, binds directly to Au. This interaction lowers
the interfacial tension, leading to a smaller particle size in the nucleation stage
(Equation Error! Reference source not found.) and prevents further growth of
particles due to coalescence and agglomeration as described in non-classical growth
theory. Size-dependent toxicity of Au NPs on C. elegans was also revealed by
investigating the neuronal cell viability, as shown in Figure 43. It is found that axonal
growth was significantly reduced by exposure to both bare and MUA coated Au NPs
(Figure 43a), but no apparent size-dependent effects were observed within the size
range investigated (6.45 ± 1.58 to 0.80 ± 0.12 nm). The effect on cell viability (using
the MTT assay), however, was found to be size-dependent, indicating that decreasing
particle size (i.e. increasing the MUA/Au NP ratio) decreases neuronal survival rate.
66
Figure 43. (a) Adverse effects on axonal growth upon exposure on Au NPs, and (b) Cellular viability of neurons
exposed to Au NPs indicated that small Au NPs reduced neuronal cell viability. T-test: *p < 0.05, **p < 0.01. Error
bars: ± SD.
Compared with the size-dependent toxicity of nanomaterials, few studies have
reported the influence of crystal structure on [266,270]. For example, titanium dioxide
(TiO2) particles have been reported to present crystal structure dependent cytotoxicity
[271] and genotoxicity [272]. As shown in Figure 44a, rutile nanoparticles (DJ3)
showed no significant difference (p > 0.05) in toxicity from the control, whereas
anatase nanoparticles (HR3) greatly inhibited algal growth by 70.5% at 1000 mgL−1.
The results in Figure 44b indicate that treatments with anatase and rutile nanoparticles
induced oxidative DNA damage, and a slightly higher level of oxidative DNA damage
was detected when treated with a mixture of anatase and rutile nanoparticles.
Figure 44. (a) Effects of oxide particles (1000 mgL−1) on algal growth as a function of alga survival under varied
treatment compared to control. * and ** denote significant differences from the control at 95% and 99% confidence
levels, respectively. The control was performed without particles [271]. (b) Induction of oxidative DNA damage by
either the anatase or rutile forms alone in comparison to an anatase–rutile mixture. Cells embedded in gel on slides
were treated for 1 h in total darkness with 20 μl of 10 μg/ml anatase-sized (200 nm) particles, or 20 μl of 10 μg/ml
rutile-sized (200 nm) particles, or with a mixture of 10 μl each. The DNA strand breaks were analysed by comet
assay with FPG digestion. *p < 0.001 compared to the untreated control; #0.05 > p > 0.001 compared with the
anatase or rutile forms alone [272].
67
Although different synthetic protocols have been developed to address the challenge
of controlling TiO2 polymorphism, size, and morphology (Figure 45) [273,274], most of
them are based on trial-and-error experience, methods based on the understanding
of the formation mechanism are still very limited [275,276]. Kinsinger and co-workers
[274] proposed a strategy to control the crystal structure of TiO2 by merely tuning the
pH value. Titanium (IV) bis(ammonium lactato) dihydroxide (TiBALDH) was used as
the precursor during the hydrothermal process. At near neutral pH conditions (e.g. pH
= 7.8), rutile nanoparticles were the predominant phase as the organic ligands are
relatively hydrolytically stable, leading to condensation through the corner-shared
bonds. Both rutile and anatase nanoparticles were observed when increasing the pH
value to 9. This phenomenon is due to the hydrolysis of organic ligands and
condensation reactions through the corner-shared bonds, which are competing
reactions. Further increasing the pH to 10 or 11, the hydrolysis rate of the organic
ligands increases significantly, enabling condensation through edge-shared bonds,
yielding anatase. The pH-dependent growth mechanisms were also revealed based
on experimental findings. Due to the low solubility of crystallites at low pH values, nonclassical particle attachment based growth dominates the formation of rutile
nanoparticles, while increasing the pH value to greater than 10, Ostwald ripening
under the classical growth framework became the predominant growth mechanism
due to the much higher solubility of TiO2 which favours the Ostwald ripening
mechanism. The phenomena of broad size distribution with increasing reaction time
supported the hypothesis of Ostwald ripening dominant growth.
68
Figure 45. TEM images of TiO2 synthesized at pH 7.8/150 ˚C (a-b). TEM images of rutile and anatase (circled)
TiO2 crystals synthesized at pH 9/150 ˚C for (c) 12 h and (d) 72 h. Selected area diffraction patterns and d-spacing
measurements (3.51 Å, (101) planes of anatase; 3.24 Å, (110) places of rutile) inserted for phase identification.
TEM images of anatase TiO2 crystals synthesized at pH 11/150 ˚C for (e) 12 h and (f) 72 h [274].
8. Summary and Outlook
For decades, classical nucleation and growth theories are still the only models often
invoked by both experimental and computational studies, as noted in all the case
studies in Section 7. However, precise control and manipulation of the processes are
increasingly important in order to produce low-dimensional solids of specific
functionalities with defined structure, crystallinity, crystalline orientation, size, shape
and/or the hosting environment, even from single atom upwards. Due to the complexity
and sensitivity of the local free-energy landscape during nucleation and growth,
classical theories are unable to consider the underlying mechanisms in sufficient detail.
In the past three decades, numerous implications of non-classical nucleation and
growth in diverse systems have emerged, followed by the development of non69
classical nucleation theories, such as two-step nucleation, pre-nucleation cluster and
non-classical growth theories, i.e. involving particle attachment and aggregation.
Nonetheless, many knowledge gaps and concerns remain. For instance, the two-step
nucleation mechanism was obtained and mainly observed in a protein solution, while
the pre-nucleation clusters concept was developed based on minerals, mainly calcium
carbonate. The general applicability of the concepts for other systems need to be
validated, which can then be coupled with CNT to generate a broad view of the
mechanism of nucleation. The structures of solvent and ions as well as forces at solidsolution interfaces during growth by particle attachment are still unknown. The
predictive power of these non-classical models will need to be tested in a wide context.
To address these knowledge gaps and concerns, in-situ experimental approaches are
critically important, as addressed in Section 5. More details of the cluster structure,
composition, thermodynamic and kinetic influences of its evolution, to be observed
under high temporal and spatial resolutions, will be needed using the state-of-art
techniques, including in-situ LP-TEM and in-situ synchrotron X-ray techniques, as well
as alternative platforms, such as microfluidic devices. Much improved understanding
and control of the processes can be achieved by close coupling of experiment,
simulation and even deep-learning techniques to pinpoint events at the atomic and
microscopic levels during nucleation and growth [277]. Furthermore, after
approximately 100 years of study on the topic, it is now highly significant to channel
the knowledge and skills base from laboratory to factory for sustainable advancement
of modern technologies.
Acknowledgements
Financial support is gratefully acknowledged from the EU Horizon 2020 SABYDOMA
Programme (Grand No. 862296); the RGG-EU Collaborative Programme initiative
(Grand No. E-HKU704/19); the National Science Foundation of China (NSFC:
22002132); the seed funding from Qingshan Lake SciTech City; the Hong Kong
Research Grants Council (RGC: ECS 27301120 & JLFS/P-704/18); the “Laboratory
for Synthetic Chemistry and Chemical Biology” funded by the Health@InnoHK and the
“Hong Kong Quantum AI Lab Ltd” funded by the AIR@InnoHK, launched by the
Innovation and Technology Commission (ITC); and the URC Platform Technology
70
Fund and the start-up support from the University of Hong Kong.
References
[1]
Handbook of Industrial Crystallization. 3rd ed. Cambridge: Cambridge
University Press; 2019. https://doi.org/DOI: 10.1017/9781139026949.
[2]
Sunagawa I. Natural crystallization. J Cryst Growth 1977;42:214–23.
https://doi.org/https://doi.org/10.1016/0022-0248(77)90197-X.
[3]
Giulietti M, Seckler MM, Derenzo S, Ré MI, Cekinski E. INDUSTRIAL
CRYSTALLIZATION AND PRECIPITATION FROM SOLUTIONS: STATE OF
THE TECHNIQUE . Brazilian J Chem Eng 2001;18:423–40.
[4]
Gao Z, Rohani S, Gong J, Wang J. Recent Developments in the Crystallization
Process: Toward the Pharmaceutical Industry. Engineering 2017;3:343–53.
https://doi.org/https://doi.org/10.1016/J.ENG.2017.03.022.
[5]
Cao S, Tao F (Feng), Tang Y, Li Y, Yu J. Size- and shape-dependent catalytic
performances of oxidation and reduction reactions on nanocatalysts. Chem
Soc Rev 2016;45:4747–65. https://doi.org/10.1039/C6CS00094K.
[6]
Wu K-J, Gao Y, Torrente-Murciano L. Continuous synthesis of hollow silver–
palladium nanoparticles for catalytic applications. Faraday Discuss
2018;208:427–41. https://doi.org/10.1039/C8FD00001H.
[7]
Howes PD, Chandrawati R, Stevens MM. Colloidal nanoparticles as advanced
biological sensors. Science (80- ) 2014;346:1247390.
https://doi.org/10.1126/science.1247390.
[8]
Li J, Wu Q, Wu J. Synthesis of Nanoparticles via Solvothermal and
Hydrothermal Methods BT - Handbook of Nanoparticles. In: Aliofkhazraei M,
editor., Cham: Springer International Publishing; 2016, p. 295–328.
https://doi.org/10.1007/978-3-319-15338-4_17.
[9]
Wu K-J, Torrente-Murciano L. Continuous synthesis of tuneable sized silver
nanoparticles via a tandem seed-mediated method in coiled flow inverter
reactors. React Chem Eng 2018;3:267–76.
https://doi.org/10.1039/C7RE00194K.
71
[10] Fiévet F, Ammar-Merah S, Brayner R, Chau F, Giraud M, Mammeri F, et al.
The polyol process: a unique method for easy access to metal nanoparticles
with tailored sizes, shapes and compositions. Chem Soc Rev 2018;47:5187–
233. https://doi.org/10.1039/C7CS00777A.
[11] Mishra CK, Sood AK, Ganapathy R. Site-specific colloidal crystal nucleation by
template-enhanced particle transport. Proc Natl Acad Sci 2016:201608568.
https://doi.org/10.1073/pnas.1608568113.
[12] Radisic A, Vereecken PM, Hannon JB, Searson PC, Ross FM. Quantifying
Electrochemical Nucleation and Growth of Nanoscale Clusters Using RealTime Kinetic Data. Nano Lett 2006;6:238–42.
https://doi.org/10.1021/nl052175i.
[13] Stefanescu DM. Nucleation and Growth Kinetics—Nanoscale Solidification BT
- Science and Engineering of Casting Solidification. In: Stefanescu DM, editor.,
Cham: Springer International Publishing; 2015, p. 29–59.
https://doi.org/10.1007/978-3-319-15693-4_3.
[14] Venables JA, Spiller GDT, Hanbucken M. Nucleation and growth of thin films.
Reports Prog Phys 1984;47:399–459. https://doi.org/10.1088/00344885/47/4/002.
[15] Haumesser P-H. Nucleation and growth of metals: from thin films to
nanoparticles. Elsevier; 2016.
[16] Guo C, Zhang Y, Guo Y, Zhang L, Zhang Y, Wang J. A general and efficient
approach for tuning the crystal morphology of classical MOFs. Chem Commun
2018;54:252–5. https://doi.org/10.1039/C7CC07698C.
[17] Rajaganapathy C, Vasudevan D, Selvakumar N. Investigation on Tribological
and mechanical behaviour of AA6082—Graphene based composites with Ti
particles. Mater Res Express 2020;7:76514. https://doi.org/10.1088/20531591/aba508.
[18] Zhang X, Li D. Metal-Compound-Induced Vesicles as Efficient Directors for
Rapid Synthesis of Hollow Alloy Spheres. Angew Chemie Int Ed
2006;45:5971–4. https://doi.org/https://doi.org/10.1002/anie.200601617.
[19] Gielen B, Jordens J, Thomassen LCJ, Braeken L, Van Gerven T.
72
Agglomeration Control during Ultrasonic Crystallization of an Active
Pharmaceutical Ingredient. Cryst 2017;7.
https://doi.org/10.3390/cryst7020040.
[20] Rautaray D, Ahmad A, Sastry M. Biosynthesis of CaCO3 Crystals of Complex
Morphology Using a Fungus and an Actinomycete. J Am Chem Soc
2003;125:14656–7. https://doi.org/10.1021/ja0374877.
[21] Rehnlund D, Ihrfors C, Maibach J, Nyholm L. Dendrite-free lithium electrode
cycling via controlled nucleation in low LiPF6 concentration electrolytes. Mater
Today 2018;21:1010–8.
https://doi.org/https://doi.org/10.1016/j.mattod.2018.08.003.
[22] Mullin JW. Nucleation. In: Mullin JWBT-C (Fourth E, editor. Crystallization,
Oxford: Elsevier; 2001, p. 181–215. https://doi.org/10.1016/B978-0750648332/50007-3.
[23] Cantor B, O’Reilly K. Solidification and casting. CRC press; 2016.
[24] Cantor B, Chang ITH, Knight P, Vincent AJB. Microstructural development in
equiatomic multicomponent alloys. Mater Sci Eng A 2004;375–377:213–8.
https://doi.org/10.1016/j.msea.2003.10.257.
[25] Volmer M, Weber Α. Keimbildung in übersättigten Gebilden. Zeitschrift Für
Phys Chemie 1926;119U:277–301. https://doi.org/https://doi.org/10.1515/zpch1926-11927.
[26] Becker R, Döring W. Kinetische Behandlung der Keimbildung in übersättigten
Dämpfen. Ann Phys 1935;416:719–52.
https://doi.org/10.1002/andp.19354160806.
[27] Frenkel J. A General Theory of Heterophase Fluctuations and Pretransition
Phenomena. J Chem Phys 1939;7:538–47. https://doi.org/10.1063/1.1750484.
[28] Zhang Z, Liu X-Y. Control of ice nucleation: freezing and antifreeze strategies.
Chem Soc Rev 2018;47:7116–39. https://doi.org/10.1039/C8CS00626A.
[29] Hamilton BD, Ha J-M, Hillmyer MA, Ward MD. Manipulating Crystal Growth
and Polymorphism by Confinement in Nanoscale Crystallization Chambers.
Acc Chem Res 2012;45:414–23. https://doi.org/10.1021/ar200147v.
73
[30] LaMer VK, Dinegar RH. Theory, Production and Mechanism of Formation of
Monodispersed Hydrosols. J Am Chem Soc 1950;72:4847–54.
https://doi.org/10.1021/ja01167a001.
[31] Whitehead CB, Özkar S, Finke RG. LaMer’s 1950 Model for Particle Formation
of Instantaneous Nucleation and Diffusion-Controlled Growth: A Historical
Look at the Model’s Origins, Assumptions, Equations, and Underlying Sulfur
Sol Formation Kinetics Data. Chem Mater 2019;31:7116–32.
https://doi.org/10.1021/acs.chemmater.9b01273.
[32] Erdemir D, Lee AY, Myerson AS. Nucleation of crystals from solution:
Classical and two-step models. Acc Chem Res 2009;42:621–9.
https://doi.org/10.1021/ar800217x.
[33] Erdemir D, Lee AY, Myerson AS. Crystal Nucleation. In: Lee AY, Myerson AS,
Erdemir D, editors. Handb. Ind. Cryst. 3rd ed., Cambridge: Cambridge
University Press; 2019, p. 76–114. https://doi.org/DOI:
10.1017/9781139026949.003.
[34] Schmitt JL, Whitten J, Adams GW, Zalabsky RA. Binary nucleation of ethanol
and water. J Chem Phys 1990;92:3693–9. https://doi.org/10.1063/1.457827.
[35] Huitema HEA, van der Eerden JP, Janssen JJM, Human H. Thermodynamics
and kinetics of homogeneous crystal nucleation studied by computer
simulation. Phys Rev B 2000;62:14690–702.
https://doi.org/10.1103/PhysRevB.62.14690.
[36] Kelton KF, Greer AL. Chapter 10 - Computer Models. In: Kelton KF, Greer
ALBT-PMS, editors. Nucleation Condens. Matter, vol. 15, Pergamon; 2010, p.
363–89. https://doi.org/https://doi.org/10.1016/S1470-1804(09)01510-7.
[37] Oxtoby DW. Nucleation of First-Order Phase Transitions. Acc Chem Res
1998;31:91–7. https://doi.org/10.1021/ar9702278.
[38] Yau S-T, Vekilov PG. Direct Observation of Nucleus Structure and Nucleation
Pathways in Apoferritin Crystallization. J Am Chem Soc 2001;123:1080–9.
https://doi.org/10.1021/ja003039c.
[39] Sleutel M, Van Driessche AES. Role of clusters in nonclassical nucleation and
growth of protein crystals. Proc Natl Acad Sci 2014;111:E546 LP-E553.
74
https://doi.org/10.1073/pnas.1309320111.
[40] Fornaro L, Ferreira D, Bentos Pereira H, Olivera A. Pre-nucleation and particle
attachment of bismuth tri-iodide onto graphene substrates. J Cryst Growth
2020;533:125454.
https://doi.org/https://doi.org/10.1016/j.jcrysgro.2019.125454.
[41] Naik AN, Patra S, Sen D, Goswami A. Evaluating the mechanism of nucleation
and growth of silver nanoparticles in a polymer membrane under continuous
precursor supply: Tuning of multiple to single nucleation pathway. Phys Chem
Chem Phys 2019;21:4193–9. https://doi.org/10.1039/c8cp06202a.
[42] Li J, Li Y, Li Q, Wang Z, Leonard Deepak F. Atomic-scale dynamic observation
reveals temperature-dependent multistep nucleation pathways in
crystallization. Nanoscale Horizons 2019;4:1302–9.
https://doi.org/10.1039/C9NH00308H.
[43] Lutsko JF. How crystals form: A theory of nucleation pathways. Sci Adv
2019;5:1–9. https://doi.org/10.1126/sciadv.aav7399.
[44] Jin B, Wang Y, Liu Z, France-Lanord A, Grossman JC, Jin C, et al. Revealing
the Cluster-Cloud and Its Role in Nanocrystallization. Adv Mater
2019;31:1808225. https://doi.org/10.1002/adma.201808225.
[45] Gebauer D, Cölfen H. Prenucleation clusters and non-classical nucleation.
Nano Today 2011;6:564–84. https://doi.org/10.1016/j.nantod.2011.10.005.
[46] Myerson AS, Trout BL. Nucleation from Solution. Science (80- )
2013;341:855–6. https://doi.org/10.1126/science.1243022.
[47] Wolde PR ten, Frenkel D. Enhancement of Protein Crystal Nucleation by
Critical Density Fluctuations. Science (80- ) 1997;277:1975 LP – 1978.
https://doi.org/10.1126/science.277.5334.1975.
[48] Mozaffari S, Li W, Thompson C, Ivanov S, Seifert S, Lee B, et al. Colloidal
nanoparticle size control: experimental and kinetic modeling investigation of
the ligand–metal binding role in controlling the nucleation and growth kinetics.
Nanoscale 2017;9:13772–85. https://doi.org/10.1039/C7NR04101B.
[49] Ortiz N, Skrabalak SE. Manipulating Local Ligand Environments for the
Controlled Nucleation of Metal Nanoparticles and their Assembly into
75
Nanodendrites. Angew Chemie Int Ed 2012;51:11757–61.
https://doi.org/10.1002/anie.201205956.
[50] Galkin O, Vekilov PG. Control of protein crystal nucleation around the
metastable liquid-liquid phase boundary. Proc Natl Acad Sci U S A
2000;97:6277–81. https://doi.org/10.1073/pnas.110000497.
[51] Bonnett PE, Carpenter KJ, Dawson S, Davey RJ. Solution crystallisation via a
submerged liquid–liquid phase boundary: oiling out. Chem Commun
2003:698–9. https://doi.org/10.1039/B212062C.
[52] Wolf SE, Leiterer J, Kappl M, Emmerling F, Tremel W. Early Homogenous
Amorphous Precursor Stages of Calcium Carbonate and Subsequent Crystal
Growth in Levitated Droplets. J Am Chem Soc 2008;130:12342–7.
https://doi.org/10.1021/ja800984y.
[53] Wolf SE, Müller L, Barrea R, Kampf CJ, Leiterer J, Panne U, et al. Carbonatecoordinated metal complexes precede the formation of liquid amorphous
mineral emulsions of divalent metal carbonates. Nanoscale 2011;3:1158–65.
https://doi.org/10.1039/C0NR00761G.
[54] Wallace AF, Hedges LO, Fernandez-Martinez A, Raiteri P, Gale JD,
Waychunas GA, et al. Microscopic Evidence for Liquid-Liquid Separation in
Supersaturated CaCO3 Solutions. Science (80- ) 2013;341:885–9.
https://doi.org/10.1126/science.1230915.
[55] Gebauer D, Völkel A, Cölfen H. Stable prenucleation calcium carbonate
clusters. Science (80- ) 2008;322:1819–22.
https://doi.org/10.1126/science.1164271.
[56] Navrotsky A. Energetic clues to pathways to biomineralization: Precursors,
clusters, and nanoparticles. Proc Natl Acad Sci U S A 2004;101:12096 LP –
12101. https://doi.org/10.1073/pnas.0404778101.
[57] Horn D, Rieger J. Organic Nanoparticles in the Aqueous Phase—Theory,
Experiment, and Use. Angew Chemie Int Ed 2001;40:4330–61.
https://doi.org/10.1002/1521-3773(20011203)40:23<4330::AIDANIE4330>3.0.CO;2-W.
[58] Pouget EM, Bomans PHH, Goos JACM, Frederik PM, de With G, Sommerdijk
76
NAJM. The Initial Stages of Template-Controlled CaCO3 Formation Revealed
by Cryo-TEM. Science (80- ) 2009;323:1455 LP – 1458.
https://doi.org/10.1126/science.1169434.
[59] Raiteri P, Gale JD. Water Is the Key to Nonclassical Nucleation of Amorphous
Calcium Carbonate. J Am Chem Soc 2010;132:17623–34.
https://doi.org/10.1021/ja108508k.
[60] Raiteri P, Gale JD, Quigley D, Rodger PM. Derivation of an Accurate ForceField for Simulating the Growth of Calcium Carbonate from Aqueous Solution:
A New Model for the Calcite−Water Interface. J Phys Chem C 2010;114:5997–
6010. https://doi.org/10.1021/jp910977a.
[61] Demichelis R, Raiteri P, Gale JD, Quigley D, Gebauer D. Stable prenucleation
mineral clusters are liquid-like ionic polymers. Nat Commun 2011;2:590–8.
https://doi.org/10.1038/ncomms1604.
[62] Stawski TM, van Driessche AES, Ossorio M, Diego Rodriguez-Blanco J,
Besselink R, Benning LG. Formation of calcium sulfate through the
aggregation of sub-3 nanometre primary species. Nat Commun 2016;7:11177.
https://doi.org/10.1038/ncomms11177.
[63] Sun S, Chevrier DM, Zhang P, Gebauer D, Cölfen H. Distinct Short-Range
Order Is Inherent to Small Amorphous Calcium Carbonate Clusters (<2 nm).
Angew Chemie Int Ed 2016;55:12206–9.
https://doi.org/10.1002/anie.201604179.
[64] Dey A, Bomans PHH, Müller FA, Will J, Frederik PM, de With G, et al. The role
of prenucleation clusters in surface-induced calcium phosphate crystallization.
Nat Mater 2010;9:1010–4. https://doi.org/10.1038/nmat2900.
[65] Krautwurst N, Nicoleau L, Dietzsch M, Lieberwirth I, Labbez C, FernandezMartinez A, et al. Two-Step Nucleation Process of Calcium Silicate Hydrate,
the Nanobrick of Cement. Chem Mater 2018;30:2895–904.
https://doi.org/10.1021/acs.chemmater.7b04245.
[66] Van Driessche AES, Van Gerven N, Bomans PHH, Joosten RRM, Friedrich H,
Gil-Carton D, et al. Molecular nucleation mechanisms and control strategies for
crystal polymorph selection. Nature 2018;556:89–94.
77
https://doi.org/10.1038/nature25971.
[67] Wu C-S, Hsieh P-Y, Yuyama K, Masuhara H, Sugiyama T. Pseudopolymorph
Control of l-Phenylalanine Achieved by Laser Trapping. Cryst Growth Des
2018;18:5417–25. https://doi.org/10.1021/acs.cgd.8b00796.
[68] Tsarfati Y, Rosenne S, Weissman H, Shimon LJW, Gur D, Palmer BA, et al.
Crystallization of Organic Molecules: Nonclassical Mechanism Revealed by
Direct Imaging. ACS Cent Sci 2018;4:1031–6.
https://doi.org/10.1021/acscentsci.8b00289.
[69] Gebauer D, Wolf SE. Designing Solid Materials from Their Solute State: A
Shift in Paradigms toward a Holistic Approach in Functional Materials
Chemistry. J Am Chem Soc 2019;141:4490–504.
https://doi.org/10.1021/jacs.8b13231.
[70] Gebauer D, Kellermeier M, Gale JD, Bergström L, Cölfen H. Pre-nucleation
clusters as solute precursors in crystallisation. Chem Soc Rev 2014;43:2348–
71. https://doi.org/10.1039/C3CS60451A.
[71] Lee AY, Erdemir D, Myerson AS. Crystals and Crystal Growth. In: Lee AY,
Myerson AS, Erdemir D, editors. Handb. Ind. Cryst. 3rd ed., Cambridge:
Cambridge University Press; 2019, p. 32–75. https://doi.org/DOI:
10.1017/9781139026949.002.
[72] Wang L, Andreassen J-P, Ucar S. Precipitation of silver particles with
controlled morphologies from aqueous solutions. CrystEngComm
2020;22:478–86. https://doi.org/10.1039/C9CE01601E.
[73] Shields SP, Richards VN, Buhro WE. Nucleation Control of Size and Dispersity
in Aggregative Nanoparticle Growth. A Study of the Coarsening Kinetics of
Thiolate-Capped Gold Nanocrystals. Chem Mater 2010;22:3212–25.
https://doi.org/10.1021/cm100458b.
[74] Fang J, Ding B, Gleiter H. Mesocrystals: Syntheses in metals and applications.
Chem Soc Rev 2011;40:5347–60. https://doi.org/10.1039/C1CS15043J.
[75] De Yoreo JJ, Gilbert PUPA, Sommerdijk NAJM, Penn RL, Whitelam S, Joester
D, et al. Crystallization by particle attachment in synthetic, biogenic, and
geologic environments. Science (80- ) 2015;349:aaa6760.
78
https://doi.org/10.1126/science.aaa6760.
[76] Randolph AD, Larson MA. Chapter 5 - CRYSTALLIZATION KINETICS. In:
Randolph AD, Larson MABT-T of PP (Second E, editors., Academic Press;
1988, p. 109–34. https://doi.org/https://doi.org/10.1016/B978-0-12-5796521.50011-9.
[77] Ohara M, Reid RC. Modeling crystal growth rates from solution. Englewood
Cliffs (N.J.): Prentice-Hall; 1973.
[78] Burton WK, Cabrera N, Frank FC, Mott NF. The growth of crystals and the
equilibrium structure of their surfaces. Philos Trans R Soc London Ser A, Math
Phys Sci 1951;243:299–358. https://doi.org/10.1098/rsta.1951.0006.
[79] Nyvlt J. The Kinetics of industrial crystallization. Amsterdam; New York; New
York: Elsevier ; Elsevier Science Pub. Co., Inc. [distributor]; 1985.
[80] Teng HH, Dove PM, De Yoreo JJ. Kinetics of calcite growth: surface
processes and relationships to macroscopic rate laws. Geochim Cosmochim
Acta 2000;64:2255–66. https://doi.org/https://doi.org/10.1016/S00167037(00)00341-0.
[81] Bharda AV, Jung HS. Liquid electron microscopy: then, now and future. Appl
Microsc 2019;49:9. https://doi.org/10.1186/s42649-019-0011-7.
[82] de Jonge N, Ross FM. Electron microscopy of specimens in liquid. Nat
Nanotechnol 2011;6:695–704. https://doi.org/10.1038/nnano.2011.161.
[83] KLEIN KL, ANDERSON IM, DE JONGE N. Transmission electron microscopy
with a liquid flow cell. J Microsc 2011;242:117–23.
https://doi.org/10.1111/j.1365-2818.2010.03484.x.
[84] de Jonge N, Poirier-Demers N, Demers H, Peckys DB, Drouin D. Nanometerresolution electron microscopy through micrometers-thick water layers.
Ultramicroscopy 2010;110:1114–9.
https://doi.org/https://doi.org/10.1016/j.ultramic.2010.04.001.
[85] Nishiyama H, Suga M, Ogura T, Maruyama Y, Koizumi M, Mio K, et al. Reprint
of: Atmospheric scanning electron microscope observes cells and tissues in
open medium through silicon nitride film. J Struct Biol 2010;172:191–202.
https://doi.org/https://doi.org/10.1016/j.jsb.2010.08.006.
79
[86] Evans JE, Jungjohann KL, Browning ND, Arslan I. Controlled Growth of
Nanoparticles from Solution with In Situ Liquid Transmission Electron
Microscopy. Nano Lett 2011;11:2809–13. https://doi.org/10.1021/nl201166k.
[87] Williamson MJ, Tromp RM, Vereecken PM, Hull R, Ross FM. Dynamic
microscopy of nanoscale cluster growth at the solid–liquid interface. Nat Mater
2003;2:532–6. https://doi.org/10.1038/nmat944.
[88] Zheng H, Smith RK, Jun Y, Kisielowski C, Dahmen U, Alivisatos AP.
Observation of Single Colloidal Platinum Nanocrystal Growth Trajectories.
Science (80- ) 2009;324:1309 LP – 1312.
https://doi.org/10.1126/science.1172104.
[89] Yuk JM, Park J, Ercius P, Kim K, Hellebusch DJ, Crommie MF, et al. HighResolution EM of Colloidal Nanocrystal Growth Using Graphene Liquid Cells.
Science (80- ) 2012;336:61 LP – 64. https://doi.org/10.1126/science.1217654.
[90] Ye X, Jones MR, Frechette LB, Chen Q, Powers AS, Ercius P, et al. Singleparticle mapping of nonequilibrium nanocrystal transformations. Science (80- )
2016;354:874 LP – 877. https://doi.org/10.1126/science.aah4434.
[91] Cho H, Jones MR, Nguyen SC, Hauwiller MR, Zettl A, Alivisatos AP. The Use
of Graphene and Its Derivatives for Liquid-Phase Transmission Electron
Microscopy of Radiation-Sensitive Specimens. Nano Lett 2017;17:414–20.
https://doi.org/10.1021/acs.nanolett.6b04383.
[92] Xu Z-L, Kim SJ, Chang D, Park K-Y, Dae KS, Dao KP, et al. Visualization of
regulated nucleation and growth of lithium sulfides for high energy lithium
sulfur batteries. Energy Environ Sci 2019;12:3144–55.
https://doi.org/10.1039/C9EE01338E.
[93] Nielsen MH, Li D, Zhang H, Aloni S, Han TY-J, Frandsen C, et al. Investigating
Processes of Nanocrystal Formation and Transformation via Liquid Cell TEM.
Microsc Microanal 2014;20:425–36. https://doi.org/DOI:
10.1017/S1431927614000294.
[94] Loh ND, Sen S, Bosman M, Tan SF, Zhong J, Nijhuis CA, et al. Multistep
nucleation of nanocrystals in aqueous solution. Nat Chem 2017;9:77–82.
https://doi.org/10.1038/nchem.2618.
80
[95] Li D, Nielsen MH, Lee JRI, Frandsen C, Banfield JF, De Yoreo JJ. DirectionSpecific Interactions Control Crystal Growth by Oriented Attachment. Science
(80- ) 2012;336:1014 LP – 1018. https://doi.org/10.1126/science.1219643.
[96] Wu S, Li M, Sun Y. In Situ Synchrotron X-ray Characterization Shining Light on
the Nucleation and Growth Kinetics of Colloidal Nanoparticles. Angew Chemie
Int Ed 2019;58:8987–95. https://doi.org/10.1002/anie.201900690.
[97] Sauter A, Roosen-Runge F, Zhang F, Lotze G, Jacobs RMJ, Schreiber F.
Real-Time Observation of Nonclassical Protein Crystallization Kinetics. J Am
Chem Soc 2015;137:1485–91. https://doi.org/10.1021/ja510533x.
[98] Chen T, Neville A, Sorbie K, Zhong Z. Using in situ synchrotron radiation wide
angle X-ray scattering (WAXS) to study CaCO3 scale formation at ambient
and elevated temperature. Faraday Discuss 2007;136:355–65.
https://doi.org/10.1039/B616546J.
[99] Abécassis B, Testard F, Kong Q, Francois B, Spalla O. Influence of Monomer
Feeding on a Fast Gold Nanoparticles Synthesis: Time-Resolved XANES and
SAXS Experiments. Langmuir 2010;26:13847–54.
https://doi.org/10.1021/la1020274.
[100] Beale AM, Weckhuysen BM. EXAFS as a tool to interrogate the size and
shape of mono and bimetallic catalyst nanoparticles. Phys Chem Chem Phys
2010;12:5562–74. https://doi.org/10.1039/B925206A.
[101] Mi J-L, Nørby P, Bremholm M, Becker J, Iversen BB. The formation
mechanism of bimetallic PtRu alloy nanoparticles in solvothermal synthesis.
Nanoscale 2015;7:16170–4. https://doi.org/10.1039/C5NR04459F.
[102] Koziej D. Revealing Complexity of Nanoparticle Synthesis in Solution by in Situ
Hard X-ray Spectroscopy—Today and Beyond. Chem Mater 2016;28:2478–
90. https://doi.org/10.1021/acs.chemmater.6b00486.
[103] Li T, Senesi AJ, Lee B. Small Angle X-ray Scattering for Nanoparticle
Research. Chem Rev 2016;116:11128–80.
https://doi.org/10.1021/acs.chemrev.5b00690.
[104] Polte J, Ahner TT, Delissen F, Sokolov S, Emmerling F, Thünemann AF, et al.
Mechanism of Gold Nanoparticle Formation in the Classical Citrate Synthesis
81
Method Derived from Coupled In Situ XANES and SAXS Evaluation. J Am
Chem Soc 2010;132:1296–301. https://doi.org/10.1021/ja906506j.
[105] Chen X, Schröder J, Hauschild S, Rosenfeldt S, Dulle M, Förster S.
Simultaneous SAXS/WAXS/UV–Vis Study of the Nucleation and Growth of
Nanoparticles: A Test of Classical Nucleation Theory. Langmuir
2015;31:11678–91. https://doi.org/10.1021/acs.langmuir.5b02759.
[106] Koerner H, MacCuspie RI, Park K, Vaia RA. In Situ UV/Vis, SAXS, and TEM
Study of Single-Phase Gold Nanoparticle Growth. Chem Mater 2012;24:981–
95. https://doi.org/10.1021/cm202633v.
[107] Abécassis B, Testard F, Spalla O, Barboux P. Probing in situ the Nucleation
and Growth of Gold Nanoparticles by Small-Angle X-ray Scattering. Nano Lett
2007;7:1723–7. https://doi.org/10.1021/nl0707149.
[108] Staniuk M, Hirsch O, Kränzlin N, Böhlen R, van Beek W, Abdala PM, et al.
Puzzling Mechanism behind a Simple Synthesis of Cobalt and Cobalt Oxide
Nanoparticles: In Situ Synchrotron X-ray Absorption and Diffraction Studies.
Chem Mater 2014;26:2086–94. https://doi.org/10.1021/cm500090r.
[109] Lee S, Wi HS, Jo W, Cho YC, Lee HH, Jeong SY, et al. Multiple pathways of
crystal nucleation in an extremely supersaturated aqueous potassium
dihydrogen phosphate (KDP) solution droplet. Proc Natl Acad Sci U S A
2016;113:13618–23. https://doi.org/10.1073/pnas.1604938113.
[110] Zhang Y, Xue D. In-situ micro-Raman spectroscopy study of gypsum
crystallization driven by chemical reaction. J Mol Struct 2020;1210:128043.
https://doi.org/https://doi.org/10.1016/j.molstruc.2020.128043.
[111] Xue D, Wang H. In-situ micro-spectroscopy technique for chemical bonding
during nucleation: A transition from soft bond to stiff bond. Sci China Technol
Sci 2020. https://doi.org/10.1007/s11431-020-1535-1.
[112] Weber E, Weiss IM, Cölfen H, Kellermeier M. Recombinant perlucin
derivatives influence the nucleation of calcium carbonate. CrystEngComm
2016;18:8439–44. https://doi.org/10.1039/C6CE01878E.
[113] Kellermeier M, Cölfen H, Gebauer D. Chapter Three - Investigating the Early
Stages of Mineral Precipitation by Potentiometric Titration and Analytical
82
Ultracentrifugation. In: De Yoreo JJBT-M in E, editor. Res. Methods Biominer.
Sci., vol. 532, Academic Press; 2013, p. 45–69.
https://doi.org/https://doi.org/10.1016/B978-0-12-416617-2.00003-5.
[114] Lignos I, Maceiczyk R, DeMello AJ. Microfluidic Technology: Uncovering the
Mechanisms of Nanocrystal Nucleation and Growth. Acc Chem Res
2017;50:1248–57. https://doi.org/10.1021/acs.accounts.7b00088.
[115] Shi HH, Xiao Y, Ferguson S, Huang X, Wang N, Hao HX. Progress of
crystallization in microfluidic devices. Lab Chip 2017;17:2167–85.
https://doi.org/10.1039/c6lc01225f.
[116] Wu K, Kuhn S. Strategies for solids handling in microreactors. Chim Oggi
2014;32:62.
[117] Chen DL, Gerdts CJ, Ismagilov RF. Using Microfluidics to Observe the Effect
of Mixing on Nucleation of Protein Crystals. J Am Chem Soc 2005;127:9672–
3. https://doi.org/10.1021/ja052279v.
[118] Simone E, McVeigh J, Reis NM, Nagy ZK. A high-throughput multi-microfluidic
crystal generator (MMicroCryGen) platform for facile screening of
polymorphism and crystal morphology for pharmaceutical compounds. Lab
Chip 2018;18:2235–45. https://doi.org/10.1039/c8lc00301g.
[119] Herbst M, Hofmann E, Förster S. Nucleation and Growth Kinetics of ZnO
Nanoparticles Studied by in Situ Microfluidic SAXS/WAXS/UV-Vis
Experiments. Langmuir 2019;35:11702–9.
https://doi.org/10.1021/acs.langmuir.9b01149.
[120] Junius N, Jaho S, Sallaz-Damaz Y, Borel F, Salmon JB, Budayova-Spano M.
A microfluidic device for both on-chip dialysis protein crystallization and: In situ
X-ray diffraction. Lab Chip 2020;20:296–310.
https://doi.org/10.1039/c9lc00651f.
[121] Pallipurath AR, Flandrin P-B, Wayment LE, Wilson CC, Robertson K. In situ
non-invasive Raman spectroscopic characterisation of succinic acid
polymorphism during segmented flow crystallisation. Mol Syst Des Eng
2020;5:294–303. https://doi.org/10.1039/C9ME00103D.
[122] Yu XY, Liu B, Yang L. Imaging liquids using microfluidic cells. Microfluid
83
Nanofluidics 2013;15:725–44. https://doi.org/10.1007/s10404-013-1199-4.
[123] Sultana M, Jensen KF. Microfluidic continuous seeded crystallization:
Extraction of growth kinetics and impact of impurity on morphology. Cryst
Growth Des 2012;12:6260–6. https://doi.org/10.1021/cg301538y.
[124] Laval P, Crombez A, Salmon JB. Microfluidic Droplet Method for Nucleation
Kinetics Measurements. Langmuir 2009;25:1836–41.
https://doi.org/10.1021/la802695r.
[125] Lignos I, Stavrakis S, Kilaj A, deMello AJ. Millisecond-Timescale Monitoring of
PbS Nanoparticle Nucleation and Growth Using Droplet-Based Microfluidics.
Small 2015;11:4009–17. https://doi.org/10.1002/smll.201500119.
[126] Rossi D, Gavriilidis A, Kuhn S, Candel MA, Jones AG, Price C, et al. Adipic
Acid Primary Nucleation Kinetics from Probability Distributions in DropletBased Systems under Stagnant and Flow Conditions. Cryst Growth Des
2015;15:1784–91. https://doi.org/10.1021/cg501836e.
[127] Gerard CJJ, Ferry G, Vuillard LM, Boutin JA, Ferte N, Grossier R, et al. A
Chemical Library to Screen Protein and Protein–Ligand Crystallization Using a
Versatile Microfluidic Platform. Cryst Growth Des 2018;18:5130–7.
https://doi.org/10.1021/acs.cgd.8b00572.
[128] Teychené S, Biscans B. Crystal nucleation in a droplet based microfluidic
crystallizer. Chem Eng Sci 2012;77:242–8.
https://doi.org/10.1016/j.ces.2012.01.036.
[129] Levenstein MA, Anduix-Canto C, Kim YY, Holden MA, González Niño C,
Green DC, et al. Droplet Microfluidics XRD Identifies Effective Nucleating
Agents for Calcium Carbonate. Adv Funct Mater 2019;29:1–12.
https://doi.org/10.1002/adfm.201808172.
[130] Lau BTC, Baitz CA, Dong XP, Hansen CL. A complete microfluidic screening
platform for rational protein crystallization. J Am Chem Soc 2007;129:454–5.
https://doi.org/10.1021/ja065855b.
[131] De Jonge N, Peckys DB, Kremers GJ, Piston DW. Electron microscopy of
whole cells in liquid with nanometer resolution. Proc Natl Acad Sci U S A
2009;106:2159–64. https://doi.org/10.1073/pnas.0809567106.
84
[132] Noack MM, Yager KG, Fukuto M, Doerk GS, Li R, Sethian JA. A Kriging-Based
Approach to Autonomous Experimentation with Applications to X-Ray
Scattering. Sci Rep 2019;9:1–19. https://doi.org/10.1038/s41598-019-48114-3.
[133] Yablon D, Chakraborty I. Machine learning to enhance atomic force
microscopy analysis and operation. Mach Learn 2020.
[134] Wijethunga TK, Stojaković J, Bellucci MA, Chen X, Myerson AS, Trout BL.
General Method for the Identification of Crystal Faces Using Raman
Spectroscopy Combined with Machine Learning and Application to the
Epitaxial Growth of Acetaminophen. Langmuir 2018;34:9836–46.
https://doi.org/10.1021/acs.langmuir.8b01791.
[135] Liotti E, Arteta C, Zisserman A, Lui A, Lempitsky V, Grant PS. Crystal
nucleation in metallic alloys using x-ray radiography and machine learning. Sci
Adv 2018;4:1–10. https://doi.org/10.1126/sciadv.aar4004.
[136] Liu S, Tian Y. Facial Expression Recognition Method Based on Gabor Wavelet
Features and Fractional Power Polynomial Kernel PCA BT - Advances in
Neural Networks - ISNN 2010. In: Zhang L, Lu B-L, Kwok J, editors., Berlin,
Heidelberg: Springer Berlin Heidelberg; 2010, p. 144–51.
[137] Waibel A, Lee K-F. Readings in speech recognition. Elsevier; 1990.
[138] Pazzani M, Billsus D. Learning and Revising User Profiles: The Identification of
Interesting Web Sites. Mach Learn 1997;27:313–31.
https://doi.org/10.1023/A:1007369909943.
[139] Yao L, Ou Z, Luo B, Xu C, Chen Q. Machine Learning to Reveal Nanoparticle
Dynamics from Liquid-Phase TEM Videos. ACS Cent Sci
2020:acscentsci.0c00430. https://doi.org/10.1021/acscentsci.0c00430.
[140] Schmidt J, Marques MRG, Botti S, Marques MAL. Recent advances and
applications of machine learning in solid-state materials science. Npj Comput
Mater 2019;5. https://doi.org/10.1038/s41524-019-0221-0.
[141] Qi J, Wakayama NI. The combined effects of magnetic field and magnetic field
gradients on convection in crystal growth. Phys Fluids 2004;16:3450–9.
https://doi.org/10.1063/1.1778402.
[142] Yin D-C. Protein crystallization in a magnetic field. Prog Cryst Growth Charact
85
Mater 2015;61:1–26.
https://doi.org/https://doi.org/10.1016/j.pcrysgrow.2015.03.001.
[143] Wu C, Wang X, Pei W, Zhao D, Wang K, Li G, et al. Tailoring the shape and
size of wet-chemical synthesized FePt nanoparticles by controlling nucleation
and growth with a high magnetic field. Nanoscale 2019;11:15023–8.
https://doi.org/10.1039/C9NR04565A.
[144] Niu H, Chen Q, Zhu H, Lin Y, Zhang X. Magnetic field-induced growth and selfassembly of cobalt nanocrystallites. J Mater Chem 2003;13:1803–5.
https://doi.org/10.1039/B303024E.
[145] Wang J, Chen Q, Zeng C, Hou B. Magnetic-Field-Induced Growth of SingleCrystalline Fe3O4 Nanowires. Adv Mater 2004;16:137–40.
https://doi.org/10.1002/adma.200306136.
[146] Nalesso S, Bussemaker MJ, Sear RP, Hodnett M, Lee J. A review on possible
mechanisms of sonocrystallisation in solution. Ultrason Sonochem
2019;57:125–38. https://doi.org/https://doi.org/10.1016/j.ultsonch.2019.04.020.
[147] Bund RK, Pandit AB. Sonocrystallization: Effect on lactose recovery and
crystal habit. Ultrason Sonochem 2007;14:143–52.
https://doi.org/https://doi.org/10.1016/j.ultsonch.2006.06.003.
[148] Gajendragadkar CN, Gogate PR. Ultrasound assisted intensified recovery of
lactose from whey based on antisolvent crystallization. Ultrason Sonochem
2017;38:754–65. https://doi.org/https://doi.org/10.1016/j.ultsonch.2016.08.011.
[149] Li H, Li H, Guo Z, Liu Y. The application of power ultrasound to reaction
crystallization. Ultrason Sonochem 2006;13:359–63.
https://doi.org/https://doi.org/10.1016/j.ultsonch.2006.01.002.
[150] Sander JRG, Zeiger BW, Suslick KS. Sonocrystallization and
sonofragmentation. Ultrason Sonochem 2014;21:1908–15.
https://doi.org/https://doi.org/10.1016/j.ultsonch.2014.02.005.
[151] Dheyab MA, Aziz AA, Jameel MS, Khaniabadi PM, Mehrdel B. Mechanisms of
effective gold shell on Fe3O4 core nanoparticles formation using
sonochemistry method. Ultrason Sonochem 2019:104865.
https://doi.org/https://doi.org/10.1016/j.ultsonch.2019.104865.
86
[152] Mao Y, Li F, Wang T, Cheng X, Li G, Li D, et al. Enhancement of lysozyme
crystallization under ultrasound field. Ultrason Sonochem 2020;63:104975.
https://doi.org/https://doi.org/10.1016/j.ultsonch.2020.104975.
[153] Chikan V, McLaurin JE. Rapid Nanoparticle Synthesis by Magnetic and
Microwave Heating. Nanomaterials 2016;6.
https://doi.org/10.3390/nano6050085.
[154] Zhu Y-J, Chen F. Microwave-Assisted Preparation of Inorganic Nanostructures
in Liquid Phase. Chem Rev 2014;114:6462–555.
https://doi.org/10.1021/cr400366s.
[155] Komarneni S, Roy R. Titania gel spheres by a new sol-gel process. Mater Lett
1985;3:165–7. https://doi.org/https://doi.org/10.1016/0167-577X(85)90151-X.
[156] Wang Y, Liu X, Han X, Godin R, Chen J, Zhou W, et al. Unique hole-accepting
carbon-dots promoting selective carbon dioxide reduction nearly 100% to
methanol by pure water. Nat Commun 2020;11:2531.
https://doi.org/10.1038/s41467-020-16227-3.
[157] de la Hoz A, Díaz-Ortiz Á, Moreno A. Microwaves in organic synthesis.
Thermal and non-thermal microwave effects. Chem Soc Rev 2005;34:164–78.
https://doi.org/10.1039/B411438H.
[158] Jhung SH, Jin T, Hwang YK, Chang J-S. Microwave Effect in the Fast
Synthesis of Microporous Materials: Which Stage Between Nucleation and
Crystal Growth is Accelerated by Microwave Irradiation? Chem – A Eur J
2007;13:4410–7. https://doi.org/10.1002/chem.200700098.
[159] Bilecka I, Niederberger M. Microwave chemistry for inorganic nanomaterials
synthesis. Nanoscale 2010;2:1358–74. https://doi.org/10.1039/B9NR00377K.
[160] Chatel G, Varma RS. Ultrasound and microwave irradiation: contributions of
alternative physicochemical activation methods to Green Chemistry. Green
Chem 2019;21:6043–50. https://doi.org/10.1039/C9GC02534K.
[161] Manno R, Sebastian V, Irusta S, Mallada R, Santamaria J. Ultra-Small Silver
Nanoparticles Immobilized in Mesoporous SBA-15. Microwave-Assisted
Synthesis and Catalytic Activity in the 4-Nitrophenol Reduction. Catal Today
2020. https://doi.org/https://doi.org/10.1016/j.cattod.2020.04.018.
87
[162] Yang Y, Hu Y, Xiong X, Qin Y. Impact of microwave power on the preparation
of silver nanowires via a microwave-assisted method. RSC Adv 2013;3:8431–
6. https://doi.org/10.1039/C3RA00117B.
[163] Yamauchi T, Tsukahara Y, Yamada K, Sakata T, Wada Y. Nucleation and
Growth of Magnetic Ni−Co (Core−Shell) Nanoparticles in a One-Pot Reaction
under Microwave Irradiation. Chem Mater 2011;23:75–84.
https://doi.org/10.1021/cm102255j.
[164] Seol SK, Kim D, Jung S, Hwu Y. Microwave synthesis of gold nanoparticles:
Effect of applied microwave power and solution pH. Mater Chem Phys
2011;131:331–5.
https://doi.org/https://doi.org/10.1016/j.matchemphys.2011.09.050.
[165] Gonzalez B, Zumeta I, Díaz-Solís M, Hernández-Torres J, Zamora-Peredo L,
Vigil E. Nanostructured CuO film grown from solution by preferential
microwave heating of the conducting glass substrate. Mater Lett
2020;270:127687. https://doi.org/https://doi.org/10.1016/j.matlet.2020.127687.
[166] Rana A ul HS, Kang M, Kim H-S. Microwave-assisted Facile and Ultrafast
Growth of ZnO Nanostructures and Proposition of Alternative Microwaveassisted Methods to Address Growth Stoppage. Sci Rep 2016;6:24870.
https://doi.org/10.1038/srep24870.
[167] Nyutu EK, Chen C-H, Dutta PK, Suib SL. Effect of Microwave Frequency on
Hydrothermal Synthesis of Nanocrystalline Tetragonal Barium Titanate. J Phys
Chem C 2008;112:9659–67. https://doi.org/10.1021/jp7112818.
[168] Kashchiev D. Chapter 21 - Electric field. In: Kashchiev DBT-N, editor., Oxford:
Butterworth-Heinemann; 2000, p. 315–29.
https://doi.org/https://doi.org/10.1016/B978-075064682-6/50022-6.
[169] Alexander LF, Radacsi N. Application of electric fields for controlling
crystallization. CrystEngComm 2019;21:5014–31.
https://doi.org/10.1039/C9CE00755E.
[170] Moreno A, Sazaki G. The use of a new ad hoc growth cell with parallel
electrodes for the nucleation control of lysozyme. J Cryst Growth
2004;264:438–44.
88
https://doi.org/https://doi.org/10.1016/j.jcrysgro.2003.12.071.
[171] Fallah-Joshaqani S, Hamdami N, Keshavarzi E, Keramat J, Dalvi-Isfahan M.
Evaluation of the static electric field effects on freezing parameters of some
food systems. Int J Refrig 2019;99:30–6.
https://doi.org/https://doi.org/10.1016/j.ijrefrig.2018.12.011.
[172] Li F, Lakerveld R. Influence of Alternating Electric Fields on Protein
Crystallization in Microfluidic Devices with Patterned Electrodes in a ParallelPlate Configuration. Cryst Growth Des 2017;17:3062–70.
https://doi.org/10.1021/acs.cgd.6b01846.
[173] Li F, Lakerveld R. Electric-Field-Assisted Protein Crystallization in Continuous
Flow. Cryst Growth Des 2018;18:2964–71.
https://doi.org/10.1021/acs.cgd.8b00095.
[174] Taleb M, Didierjean C, Jelsch C, Mangeot JP, Capelle B, Aubry A.
Crystallization of proteins under an external electric field. J Cryst Growth
1999;200:575–82. https://doi.org/https://doi.org/10.1016/S00220248(98)01409-2.
[175] Hou D, Chang H-C. ac field enhanced protein crystallization. Appl Phys Lett
2008;92:223902. https://doi.org/10.1063/1.2938887.
[176] Nanev CN, Penkova A. Nucleation of lysozyme crystals under external electric
and ultrasonic fields. J Cryst Growth 2001;232:285–93.
https://doi.org/https://doi.org/10.1016/S0022-0248(01)01169-1.
[177] Adrjanowicz K, Paluch M, Richert R. Formation of new polymorphs and control
of crystallization in molecular glass-formers by electric field. Phys Chem Chem
Phys 2018;20:925–31. https://doi.org/10.1039/C7CP07352F.
[178] Amendola V, Meneghetti M. Laser ablation synthesis in solution and size
manipulation of noble metal nanoparticles. Phys Chem Chem Phys
2009;11:3805–21. https://doi.org/10.1039/B900654K.
[179] Piotto V, Litti L, Meneghetti M. Synthesis and Shape Manipulation of
Anisotropic Gold Nanoparticles by Laser Ablation in Solution. J Phys Chem C
2020;124:4820–6. https://doi.org/10.1021/acs.jpcc.9b10793.
[180] Rehbock C, Merk V, Gamrad L, Streubel R, Barcikowski S. Size control of
89
laser-fabricated surfactant-free gold nanoparticles with highly diluted
electrolytes and their subsequent bioconjugation. Phys Chem Chem Phys
2013;15:3057–67. https://doi.org/10.1039/C2CP42641B.
[181] Nichols WT, Sasaki T, Koshizaki N. Laser ablation of a platinum target in
water. III. Laser-induced reactions. J Appl Phys 2006;100:114913.
https://doi.org/10.1063/1.2390642.
[182] Shih C-Y, Streubel R, Heberle J, Letzel A, Shugaev M V, Wu C, et al. Two
mechanisms of nanoparticle generation in picosecond laser ablation in liquids:
the origin of the bimodal size distribution. Nanoscale 2018;10:6900–10.
https://doi.org/10.1039/C7NR08614H.
[183] Sylvestre J-P, Kabashin A V, Sacher E, Meunier M, Luong JHT. Stabilization
and Size Control of Gold Nanoparticles during Laser Ablation in Aqueous
Cyclodextrins. J Am Chem Soc 2004;126:7176–7.
https://doi.org/10.1021/ja048678s.
[184] Yang S, Cai W, Zhang H, Xu X, Zeng H. Size and Structure Control of Si
Nanoparticles by Laser Ablation in Different Liquid Media and Further
Centrifugation Classification. J Phys Chem C 2009;113:19091–5.
https://doi.org/10.1021/jp907285f.
[185] Okada R, Iijima S. Oxidation property of silicon small particles. Appl Phys Lett
1991;58:1662–3. https://doi.org/10.1063/1.105129.
[186] Shinde SR, Kulkarni SD, Banpurkar AG, Nawathey-Dixit R, Date SK, Ogale
SB. Magnetic properties of nanosized powders of magnetic oxides synthesized
by pulsed laser ablation. J Appl Phys 2000;88:1566–75.
https://doi.org/10.1063/1.373856.
[187] Niu X, Murray PT, Sarangan A. Synthesis of Fe–Ni bimetallic nanoparticles
from pixel target ablation: plume dynamics and surface characterization. J
Nanoparticle Res 2012;14:1017. https://doi.org/10.1007/s11051-012-1017-z.
[188] Reisinger D, Schonecke M, Brenninger T, Opel M, Erb A, Alff L, et al. Epitaxy
of Fe3O4 on Si(001) by pulsed laser deposition using a TiN/MgO buffer layer.
J Appl Phys 2003;94:1857–63. https://doi.org/10.1063/1.1587885.
[189] Blakemore JD, Gray HB, Winkler JR, Müller AM. Co3O4 Nanoparticle Water90
Oxidation Catalysts Made by Pulsed-Laser Ablation in Liquids. ACS Catal
2013;3:2497–500. https://doi.org/10.1021/cs400639b.
[190] Blumenfeld CM, Lau M, Gray HB, Müller AM. Mixed-Metal Tungsten Oxide
Photoanode Materials Made by Pulsed-Laser in Liquids Synthesis.
ChemPhysChem 2017;18:1091–100. https://doi.org/10.1002/cphc.201601285.
[191] Poondi D, Dobbins T, Singh J. A novel laser-liquid-solid interaction technique
for synthesis of silver, nickel and immiscible silver-nickel alloys from liquid
precursors. J Mater Sci 2000;35:6237–43.
https://doi.org/10.1023/A:1026701915796.
[192] Hunter BM, Blakemore JD, Deimund M, Gray HB, Winkler JR, Müller AM.
Highly Active Mixed-Metal Nanosheet Water Oxidation Catalysts Made by
Pulsed-Laser Ablation in Liquids. J Am Chem Soc 2014;136:13118–21.
https://doi.org/10.1021/ja506087h.
[193] Torres-Mendieta R, Ventura-Espinosa D, Sabater S, Lancis J, Mínguez-Vega
G, Mata JA. In situ decoration of graphene sheets with gold nanoparticles
synthetized by pulsed laser ablation in liquids. Sci Rep 2016;6:30478.
https://doi.org/10.1038/srep30478.
[194] Harano A, Shimada K, Okubo T, Sadakata M. Crystal phases of TiO 2 ultrafine
particles prepared by laser ablation of solid rods. J Nanoparticle Res
2002;4:215–9.
[195] Kawakami Y, Seto T, Yoshida T, Ozawa E. Gold nanoparticles and films
produced by a laser ablation/gas deposition (LAGD) method. Appl Surf Sci
2002;197–198:587–93. https://doi.org/https://doi.org/10.1016/S01694332(02)00342-2.
[196] Tsuji M, Seto T, Otani Y. Effect of surrounding gas temperature on the
morphological evolution of TiO2 nanoparticles generated by laser ablation in
tubular furnace. J Nanoparticle Res 2012;14:674.
https://doi.org/10.1007/s11051-011-0674-7.
[197] Zhang J, Claverie J, Chaker M, Ma D. Colloidal Metal Nanoparticles Prepared
by Laser Ablation and their Applications. ChemPhysChem 2017;18:986–1006.
https://doi.org/10.1002/cphc.201601220.
91
[198] Mafuné Fumitaka, Kohno J, Takeda Y, Kondow T. Full Physical Preparation of
Size-Selected Gold Nanoparticles in Solution: Laser Ablation and LaserInduced Size Control. J Phys Chem B 2002;106:7575–7.
https://doi.org/10.1021/jp020577y.
[199] Sakiyama K, Koga K, Seto T, Hirasawa M, Orii T. Formation of Size-Selected
Ni/NiO Core−Shell Particles by Pulsed Laser Ablation. J Phys Chem B
2004;108:523–9. https://doi.org/10.1021/jp035339x.
[200] Seto T, Koga K, Akinaga H, Takano F, Orii T, Hirasawa M. Laser ablation
synthesis of monodispersed magnetic alloy nanoparticles. J Nanoparticle Res
2006;8:371–8. https://doi.org/10.1007/s11051-005-9010-4.
[201] Seto T, Koga K, Takano F, Akinaga H, Orii T, Hirasawa M, et al. Synthesis of
magnetic CoPt/SiO2 core-shell nanoparticles. J Phys Conf Ser 2007;59:255–8.
https://doi.org/10.1088/1742-6596/59/1/054.
[202] Park JB, Jeong SH, Jeong MS, Kim JY, Cho BK. Synthesis of carbonencapsulated magnetic nanoparticles by pulsed laser irradiation of solution.
Carbon N Y 2008;46:1369–77.
https://doi.org/https://doi.org/10.1016/j.carbon.2008.05.011.
[203] Amendola V, Riello P, Meneghetti M. Magnetic Nanoparticles of Iron Carbide,
Iron Oxide, Iron@Iron Oxide, and Metal Iron Synthesized by Laser Ablation in
Organic Solvents. J Phys Chem C 2011;115:5140–6.
https://doi.org/10.1021/jp109371m.
[204] Amendola V, Polizzi S, Meneghetti M. Free Silver Nanoparticles Synthesized
by Laser Ablation in Organic Solvents and Their Easy Functionalization.
Langmuir 2007;23:6766–70. https://doi.org/10.1021/la0637061.
[205] Dikovska AO, Alexandrov MT, Atanasova GB, Tsankov NT, Stefanov PK.
Silver nanoparticles produced by PLD in vacuum: role of the laser wavelength
used. Appl Phys A 2013;113:83–8. https://doi.org/10.1007/s00339-013-7834-9.
[206] Sourice J, Quinsac A, Leconte Y, Sublemontier O, Porcher W, Haon C, et al.
One-Step Synthesis of Si@C Nanoparticles by Laser Pyrolysis: High-Capacity
Anode Material for Lithium-Ion Batteries. ACS Appl Mater Interfaces
2015;7:6637–44. https://doi.org/10.1021/am5089742.
92
[207] Bouhadoun S, Guillard C, Dapozze F, Singh S, Amans D, Bouclé J, et al. One
step synthesis of N-doped and Au-loaded TiO2 nanoparticles by laser
pyrolysis: Application in photocatalysis. Appl Catal B Environ 2015;174–
175:367–75. https://doi.org/https://doi.org/10.1016/j.apcatb.2015.03.022.
[208] D’Amato R, Falconieri M, Gagliardi S, Popovici E, Serra E, Terranova G, et al.
Synthesis of ceramic nanoparticles by laser pyrolysis: From research to
applications. J Anal Appl Pyrolysis 2013;104:461–9.
https://doi.org/https://doi.org/10.1016/j.jaap.2013.05.026.
[209] Figgemeier E, Kylberg W, Constable E, Scarisoreanu M, Alexandrescu R,
Morjan I, et al. Titanium dioxide nanoparticles prepared by laser pyrolysis:
Synthesis and photocatalytic properties. Appl Surf Sci 2007;254:1037–41.
https://doi.org/https://doi.org/10.1016/j.apsusc.2007.08.036.
[210] Audren A, Ha-Thi MH, Coste S, Leconte Y. Synthesis of New Materials by
Laser Pyrolysis: ZrO2, Y2O3:Ce and TiC x N y Nanoparticles. J Nanosci
Nanotechnol n.d.;10:6216–21.
[211] Grimes CA, Qian D, Dickey EC, Allen JL, Eklund PC. Laser pyrolysis
fabrication of ferromagnetic γ′-Fe4N and FeC nanoparticles. J Appl Phys
2000;87:5642–4. https://doi.org/10.1063/1.373419.
[212] Borsella E, Botti S, Cesile MC, Martelli S, Nesterenko A, Zappelli PG. MoS2
nanoparticles produced by laser induced synthesis from gaseous precursors. J
Mater Sci Lett 2001;20:187–91. https://doi.org/10.1023/A:1006760317763.
[213] He Y, Li X, Swihart MT. Laser-Driven Aerosol Synthesis of Nickel
Nanoparticles. Chem Mater 2005;17:1017–26.
https://doi.org/10.1021/cm048128t.
[214] Bystrzejewski M, Hübers HW, Huczko A, Gemming T, Büchner B, Rümmeli
MH. Bulk synthesis of carbon nanocapsules and nanotubes containing
magnetic nanoparticles via low energy laser pyrolysis of ferrocene. Mater Lett
2009;63:1767–70. https://doi.org/https://doi.org/10.1016/j.matlet.2009.05.030.
[215] Chrisey DB. The Power of Direct Writing. Science (80- ) 2000;289:879 LP –
881. https://doi.org/10.1126/science.289.5481.879.
[216] Nishiyama H, Umetsu K, Kimura K. Versatile direct laser writing of non93
photosensitive materials using multi-photon reduction-based assembly of
nanoparticles. Sci Rep 2019;9:14310. https://doi.org/10.1038/s41598-01950630-1.
[217] Blasco E, Müller J, Müller P, Trouillet V, Schön M, Scherer T, et al. Fabrication
of Conductive 3D Gold-Containing Microstructures via Direct Laser Writing.
Adv Mater 2016;28:3592–5. https://doi.org/10.1002/adma.201506126.
[218] Gao W, Singh N, Song L, Liu Z, Reddy ALM, Ci L, et al. Direct laser writing of
micro-supercapacitors on hydrated graphite oxide films. Nat Nanotechnol
2011;6:496–500. https://doi.org/10.1038/nnano.2011.110.
[219] Abou Khalil A, Bérubé J-P, Danto S, Desmoulin J-C, Cardinal T, Petit Y, et al.
Direct laser writing of a new type of waveguides in silver containing glasses.
Sci Rep 2017;7:11124. https://doi.org/10.1038/s41598-017-11550-0.
[220] Nian Q, Wang Y, Yang Y, Li J, Zhang MY, Shao J, et al. Direct Laser Writing of
Nanodiamond Films from Graphite under Ambient Conditions. Sci Rep
2014;4:6612. https://doi.org/10.1038/srep06612.
[221] Luong DX, Yang K, Yoon J, Singh SP, Wang T, Arnusch CJ, et al. LaserInduced Graphene Composites as Multifunctional Surfaces. ACS Nano
2019;13:2579–86. https://doi.org/10.1021/acsnano.8b09626.
[222] Ye R, James DK, Tour JM. Laser-Induced Graphene. Acc Chem Res
2018;51:1609–20. https://doi.org/10.1021/acs.accounts.8b00084.
[223] Ye R, Peng Z, Wang T, Xu Y, Zhang J, Li Y, et al. In Situ Formation of Metal
Oxide Nanocrystals Embedded in Laser-Induced Graphene. ACS Nano
2015;9:9244–51. https://doi.org/10.1021/acsnano.5b04138.
[224] Wang W, Lu L, Xie Y, Mei X, Tang Y, Wu W, et al. Tailoring the surface
morphology and nanoparticle distribution of laser-induced graphene/Co3O4 for
high-performance flexible microsupercapacitors. Appl Surf Sci
2020;504:144487.
https://doi.org/https://doi.org/10.1016/j.apsusc.2019.144487.
[225] Serra P, Piqué A. Laser-Induced Forward Transfer: Fundamentals and
Applications. Adv Mater Technol 2019;4:1800099.
https://doi.org/10.1002/admt.201800099.
94
[226] Zhang J, Ren M, Li Y, Tour JM. In Situ Synthesis of Efficient Water Oxidation
Catalysts in Laser-Induced Graphene. ACS Energy Lett 2018;3:677–83.
https://doi.org/10.1021/acsenergylett.8b00042.
[227] Han X, Ye R, Chyan Y, Wang T, Zhang C, Shi L, et al. Laser-Induced
Graphene from Wood Impregnated with Metal Salts and Use in
Electrocatalysis. ACS Appl Nano Mater 2018;1:5053–61.
https://doi.org/10.1021/acsanm.8b01163.
[228] Ye R, James DK, Tour JM. Laser-Induced Graphene: From Discovery to
Translation. Adv Mater 2019;31:1803621.
https://doi.org/10.1002/adma.201803621.
[229] Mo X, Chan KC, Tse ECM. A Scalable Laser-Assisted Method to Produce
Active and Robust Graphene-Supported Nanoparticle Electrocatalysts. Chem
Mater 2019;31:8230–8. https://doi.org/10.1021/acs.chemmater.9b03669.
[230] Li G, Law W-C, Chan KC. Floating, highly efficient, and scalable graphene
membranes for seawater desalination using solar energy. Green Chem
2018;20:3689–95. https://doi.org/10.1039/C8GC01347K.
[231] Li G, Mo X, Law W-C, Chan KC. Wearable Fluid Capture Devices for
Electrochemical Sensing of Sweat. ACS Appl Mater Interfaces 2019;11:238–
43. https://doi.org/10.1021/acsami.8b17419.
[232] Li G, Mo X, Law W-C, Chan KC. 3D printed graphene/nickel electrodes for
high areal capacitance electrochemical storage. J Mater Chem A
2019;7:4055–62. https://doi.org/10.1039/C8TA11121A.
[233] Li G, Mo X, Wang Y, Chan C-Y, Chan KC. All 3D-Printed
Superhydrophobic/Oleophilic Membrane for Robotic Oil Recycling. Adv Mater
Interfaces 2019;6:1900874. https://doi.org/10.1002/admi.201900874.
[234] Pillai ZS, Kamat P V. What Factors Control the Size and Shape of Silver
Nanoparticles in the Citrate Ion Reduction Method? J Phys Chem B
2004;108:945–51. https://doi.org/10.1021/jp037018r.
[235] Lane MKM, Zimmerman JB. Controlling metal oxide nanoparticle size and
shape with supercritical fluid synthesis. Green Chem 2019;21:3769–81.
https://doi.org/10.1039/C9GC01619H.
95
[236] Qiu L, McCaffrey R, Jin Y, Gong Y, Hu Y, Sun H, et al. Cage-templated
synthesis of highly stable palladium nanoparticles and their catalytic activities
in Suzuki–Miyaura coupling. Chem Sci 2018;9:676–80.
https://doi.org/10.1039/C7SC03148C.
[237] Song T, Tang L, Tan LH, Wang X, Satyavolu NSR, Xing H, et al. DNAEncoded Tuning of Geometric and Plasmonic Properties of Nanoparticles
Growing from Gold Nanorod Seeds. Angew Chemie Int Ed 2015;54:8114–8.
https://doi.org/10.1002/anie.201500838.
[238] Wang Z, Tang L, Tan LH, Li J, Lu Y. Discovery of the DNA “Genetic Code” for
Abiological Gold Nanoparticle Morphologies. Angew Chemie Int Ed
2012;51:9078–82. https://doi.org/10.1002/anie.201203716.
[239] Wu J, Tan LH, Hwang K, Xing H, Wu P, Li W, et al. DNA SequenceDependent Morphological Evolution of Silver Nanoparticles and Their Optical
and Hybridization Properties. J Am Chem Soc 2014;136:15195–202.
https://doi.org/10.1021/ja506150s.
[240] Wang Z, Zhang J, Ekman JM, Kenis PJA, Lu Y. DNA-Mediated Control of
Metal Nanoparticle Shape: One-Pot Synthesis and Cellular Uptake of Highly
Stable and Functional Gold Nanoflowers. Nano Lett 2010;10:1886–91.
https://doi.org/10.1021/nl100675p.
[241] Satyavolu NSR, Pishevaresfahani N, Tan LH, Lu Y. DNA-encoded
morphological evolution of bimetallic Pd@Au core-shell nanoparticles from a
high-indexed core. Nano Res 2018;11:4549–61.
https://doi.org/10.1007/s12274-018-2035-7.
[242] Ramezani-Dakhel H, Bedford NM, Woehl TJ, Knecht MR, Naik RR, Heinz H.
Nature of peptide wrapping onto metal nanoparticle catalysts and driving
forces for size control. Nanoscale 2017;9:8401–9.
https://doi.org/10.1039/C7NR02813J.
[243] Tan YN, Lee JY, Wang DIC. Uncovering the Design Rules for Peptide
Synthesis of Metal Nanoparticles. J Am Chem Soc 2010;132:5677–86.
https://doi.org/10.1021/ja907454f.
[244] Krishnamurthy S, Vaiyapuri R, Zhang L, Chan JM. Lipid-coated polymeric
96
nanoparticles for cancer drug delivery. Biomater Sci 2015;3:923–36.
https://doi.org/10.1039/C4BM00427B.
[245] Miesen TJ, Engstrom AM, Frost DC, Ajjarapu R, Ajjarapu R, Lira CN, et al. A
hybrid lipid membrane coating “shape-locks” silver nanoparticles to prevent
surface oxidation and silver ion dissolution. RSC Adv 2020;10:15677–93.
https://doi.org/10.1039/D0RA01727B.
[246] Xie W, Guo Z, Gao F, Gao Q, Wang D, Liaw B, et al. Shape-, size- and
structure-controlled synthesis and biocompatibility of iron oxide nanoparticles
for magnetic theranostics. Theranostics 2018;8:3284–307.
https://doi.org/10.7150/thno.25220.
[247] Yang H, Guo C, Naveed A, Lei J, Yang J, Nuli Y, et al. Recent progress and
perspective on lithium metal anode protection. Energy Storage Mater
2018;14:199–221. https://doi.org/https://doi.org/10.1016/j.ensm.2018.03.001.
[248] Yan K, Wang J, Zhao S, Zhou D, Sun B, Cui Y, et al. Temperature-dependent
Nucleation and Growth of Dendrite-Free Lithium Metal Anodes. Angew
Chemie - Int Ed 2019;94025:11364–8. https://doi.org/10.1002/anie.201905251.
[249] Biswal P, Stalin S, Kludze A, Choudhury S, Archer LA. Nucleation and Early
Stage Growth of Li Electrodeposits. Nano Lett 2019;19:8191–200.
https://doi.org/10.1021/acs.nanolett.9b03548.
[250] Liu L, Yin Y-X, Li J-Y, Wang S-H, Guo Y-G, Wan L-J. Uniform Lithium
Nucleation/Growth Induced by Lightweight Nitrogen-Doped Graphitic Carbon
Foams for High-Performance Lithium Metal Anodes. Adv Mater
2018;30:1706216. https://doi.org/10.1002/adma.201706216.
[251] Wei C, Fei H, An Y, Tao Y, Feng J, Qian Y. Uniform Li deposition by regulating
the initial nucleation barrier via a simple liquid-metal coating for a dendrite-free
Li–metal anode. J Mater Chem A 2019;7:18861–70.
https://doi.org/10.1039/c9ta06663b.
[252] Qin Y, Han X, Gadipelli S, Guo J, Wu S, Kang L, et al. In situ synthesized lowPtCo@porous carbon catalyst for highly efficient hydrogen evolution. J Mater
Chem A 2019;7:6543–51. https://doi.org/10.1039/C8TA12263F.
[253] Guo J, Gadipelli S, Yang Y, Li Z, Lu Y, Brett DJL, et al. An efficient carbon97
based ORR catalyst from low-temperature etching of ZIF-67 with ultra-small
cobalt nanoparticles and high yield. J Mater Chem A 2019;7:3544–51.
https://doi.org/10.1039/C8TA10925G.
[254] Cho J, Xu L, Jo C, Ryoo R. Highly monodisperse supported metal
nanoparticles by basic ammonium functionalization of mesopore walls for
industrially relevant catalysis. Chem Commun 2017;53:3810–3.
https://doi.org/10.1039/C7CC00479F.
[255] Wang A, Li J, Zhang T. Heterogeneous single-atom catalysis. Nat Rev Chem
2018;2:65–81. https://doi.org/10.1038/s41570-018-0010-1.
[256] Huang K, Wang R, Zhao S, Du P, Wang H, Wei H, et al. Atomic species
derived CoOx clusters on nitrogen doped mesoporous carbon as advanced
bifunctional electro-catalysts for Zn-air battery. Energy Storage Mater 2020.
https://doi.org/https://doi.org/10.1016/j.ensm.2020.03.026.
[257] Huang K, Wang R, Wu H, Wang H, He X, Wei H, et al. Direct immobilization of
an atomically dispersed Pt catalyst by suppressing heterogeneous nucleation
at −40 °C. J Mater Chem A 2019;7:25779–84.
https://doi.org/10.1039/C9TA07469D.
[258] Lai W-HH, Wang YY-XX, Wang YY-XX, Wu M, Wang J-ZZ, Liu H-KK, et al.
Morphology tuning of inorganic nanomaterials grown by precipitation through
control of electrolytic dissociation and supersaturation. Nat Chem
2019;11:695–701. https://doi.org/10.1038/s41557-019-0298-6.
[259] Sunagawa I, editor. Crystal growth. Cryst. Growth, Morphol. &amp; Perfect.,
Cambridge: Cambridge University Press; 2005, p. 20–59. https://doi.org/DOI:
10.1017/CBO9780511610349.006.
[260] Zhao J, Wang M, Lababidi HMS, Al-Adwani H, Gleason KK. A review of
heterogeneous nucleation of calcium carbonate and control strategies for scale
formation in multi-stage flash (MSF) desalination plants. Desalination
2018;442:75–88. https://doi.org/https://doi.org/10.1016/j.desal.2018.05.008.
[261] Vazirian MM, Charpentier TVJ, de Oliveira Penna M, Neville A. Surface
inorganic scale formation in oil and gas industry: As adhesion and deposition
processes. J Pet Sci Eng 2016;137:22–32.
98
https://doi.org/https://doi.org/10.1016/j.petrol.2015.11.005.
[262] Zhao J, Wang M, Jebutu MS, Zhu M, Gleason KK. Fundamental nanoscale
surface strategies for robustly controlling heterogeneous nucleation of calcium
carbonate. J Mater Chem A 2019;7:17242–7.
https://doi.org/10.1039/C9TA04341A.
[263] Huang L, Zhou B, Wu H, Zheng L, Zhao J. Effect of apatite formation of
biphasic calcium phosphate ceramic (BCP) on osteoblastogenesis using
simulated body fluid (SBF) with or without bovine serum albumin (BSA). Mater
Sci Eng C 2017;70:955–61.
https://doi.org/https://doi.org/10.1016/j.msec.2016.05.115.
[264] Golda-Cepa M, Riedlová K, Kulig W, Cwiklik L, Kotarba A. Functionalization of
the Parylene C Surface Enhances the Nucleation of Calcium Phosphate:
Combined Experimental and Molecular Dynamics Simulations Approach. ACS
Appl Mater Interfaces 2020;12:12426–35.
https://doi.org/10.1021/acsami.9b20877.
[265] Wang Y, Santos A, Evdokiou A, Losic D. An overview of nanotoxicity and
nanomedicine research: principles, progress and implications for cancer
therapy. J Mater Chem B 2015;3:7153–72.
https://doi.org/10.1039/C5TB00956A.
[266] Reijnders L. Chapter 10 - Safer-by-design for nanomaterials. In: Rajendran S,
Mukherjee A, Nguyen TA, Godugu C, Shukla RKBT-N, editors. Micro Nano
Technol., Elsevier; 2020, p. 215–37.
https://doi.org/https://doi.org/10.1016/B978-0-12-819943-5.00010-5.
[267] Lee J, Yang J, Kwon SG, Hyeon T. Nonclassical nucleation and growth of
inorganic nanoparticles. Nat Rev Mater 2016;1:16034.
https://doi.org/10.1038/natrevmats.2016.34.
[268] Hu C-C, Wu G-H, Lai S-F, Muthaiyan Shanmugam M, Hwu Y, Wagner OI, et
al. Toxic Effects of Size-tunable Gold Nanoparticles on Caenorhabditis
elegans Development and Gene Regulation. Sci Rep 2018;8:15245.
https://doi.org/10.1038/s41598-018-33585-7.
[269] Lai S-F, Chen W-C, Wang C-L, Chen H-H, Chen S-T, Chien C-C, et al. One99
Pot Tuning of Au Nucleation and Growth: From Nanoclusters to Nanoparticles.
Langmuir 2011;27:8424–9. https://doi.org/10.1021/la200861e.
[270] Mahaye N, Thwala M, Cowan DA, Musee N. Genotoxicity of metal based
engineered nanoparticles in aquatic organisms: A review. Mutat Res Mutat
Res 2017;773:134–60.
https://doi.org/https://doi.org/10.1016/j.mrrev.2017.05.004.
[271] Ji J, Long Z, Lin D. Toxicity of oxide nanoparticles to the green algae Chlorella
sp. Chem Eng J 2011;170:525–30.
https://doi.org/https://doi.org/10.1016/j.cej.2010.11.026.
[272] Gurr J-R, Wang ASS, Chen C-H, Jan K-Y. Ultrafine titanium dioxide particles
in the absence of photoactivation can induce oxidative damage to human
bronchial epithelial cells. Toxicology 2005;213:66–73.
https://doi.org/https://doi.org/10.1016/j.tox.2005.05.007.
[273] Zhang M, Chen T, Wang Y. Insights into TiO2 polymorphs: highly selective
synthesis, phase transition, and their polymorph-dependent properties. RSC
Adv 2017;7:52755–61. https://doi.org/10.1039/C7RA11515F.
[274] Kinsinger NM, Wong A, Li D, Villalobos F, Kisailus D. Nucleation and Crystal
Growth of Nanocrystalline Anatase and Rutile Phase TiO2 from a WaterSoluble Precursor. Cryst Growth Des 2010;10:5254–61.
https://doi.org/10.1021/cg101105t.
[275] Li D, Soberanis F, Fu J, Hou W, Wu J, Kisailus D. Growth Mechanism of
Highly Branched Titanium Dioxide Nanowires via Oriented Attachment. Cryst
Growth Des 2013;13:422–8. https://doi.org/10.1021/cg301388e.
[276] Tarasov A, Goertz V, Goodilin E, Nirschl H. Hydrolytic Stages of Titania
Nanoparticles Formation Jointly Studied by SAXS, DLS, and TEM. J Phys
Chem C 2013;117:12800–5. https://doi.org/10.1021/jp312443u.
[277] Sosso GC, Chen J, Cox SJ, Fitzner M, Pedevilla P, Zen A, et al. Crystal
Nucleation in Liquids: Open Questions and Future Challenges in Molecular
Dynamics Simulations. Chem Rev 2016;116:7078–116.
https://doi.org/10.1021/acs.chemrev.5b00744.
100
Declaration of interests
☒ The authors declare that they have no known competing financial interests or personal
relationships that could have appeared to influence the work reported in this paper.
☐The authors declare the following financial interests/personal relationships which may be
considered as potential competing interests:
On behalf of all authors, I declare there is no known competing financial interests or personal relationships
that could have appeared to influence the work reported in this paper.
Signed: (ZX Guo)
; Date: 30 July 2020
Ps. If all signatures are required, we can submit this later. This is to speed up the process.
101