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Volume 20 | Number 33 | 7 September 2010 | Pages 6817–7044
ISSN 0959-9428
FEATURE ARTICLE
Antonio Tilocca
Models of structure, dynamics and
reactivity of bioglasses: a review
PAPER
Irma Perez-Baena et al.
Single-chain polyacrylic nanoparticles
with multiple Gd(III) centres as
potential MRI contrast agents
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FEATURE ARTICLE
www.rsc.org/materials | Journal of Materials Chemistry
Models of structure, dynamics and reactivity of bioglasses: a review
Antonio Tilocca*
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Published on 16 June 2010 on http://pubs.rsc.org | doi:10.1039/C0JM01081B
Received 17th April 2010, Accepted 19th May 2010
DOI: 10.1039/c0jm01081b
Due to their high biocompatibility and osteoconductivity, bioactive silicate glasses are the core
components of biomaterials used to repair, restore and regenerate bone and tissues in the human body.
One of the key features, which control their bioactivity, is the fast surface dissolution in a biological
medium, with the release of critical amounts of ions in the surrounding environment. Being able to
understand these inorganic processes at the atomistic level is essential if a more rational approach to the
use of these materials is sought. Over the past five years, atomistic simulations of bioglasses have
revealed details of bulk structural features which affect the glass dissolution and thus its bioactivity,
such as the connectivity of the silicate network and the tendency to form chains, rings and clusters.
Further simulations have started to focus directly on the details of the glass surface and of its reactivity
in an aqueous environment. This article reviews recent computational approaches used to investigate
the properties of bioglasses crucial for their bioactive behaviour.
Introduction
Several different biomaterials are routinely employed to replace
injured or weakened tissues, restoring functionality to many
parts of the humany body.1,2 The discovery of bioactive glasses,
about 40 years ago,3 radically changed the field of biomaterials
for clinical implants, which until then was based on traditional
bioinert materials. The latter are metals, alloys or ceramics,
whose successful implant depends on a tight mechanical fit
within the host tissues. The lack of real chemical adhesion limits
the long-term durability of bionert implants, frequently resulting
in revision surgery. The work of Hench and co-workers highlighted the very different behaviour of some low-silica compositions of melt-derived soda-calcia phosphosilicate glasses, of
which 45S5 Bioglass (BG45) is the most representative
Department of Chemistry and Thomas Young Centre for Theory and
Simulations of Materials, University College London, 20 Gordon Street,
WC1H 0AJ London, U.K. E-mail: a.tilocca@ucl.ac.uk; Fax: +44 20
7679 4453; Tel: +44 20 7679 4558
Antonio Tilocca graduated with
Laurea (MSc) and PhD
degrees from University of Sassari, Italy. He held post-doctoral
positions at University of
Insubria at Como (Italy),
Princeton
University,
and
University College London,
where he became a Royal
Society University Research
Fellow in 2006. His current
research involves using classical
and ab initio simulations to
Antonio Tilocca
model structure, dynamics and
reactivity of materials, including
crystalline and amorphous oxides with applications in biomedicine
and catalysis.
6848 | J. Mater. Chem., 2010, 20, 6848–6858
member. These bioactive glasses are able, following contact with
body fluids, to form a film of bone-like mineral (crystalline
calcium phosphate, or apatite) on their surface, following a rapid
sequence of inorganic processes, involving ion release, hydrolysis
and partial dissolution.1,2 The growing apatite layer passivates
the glass against further degradation, preventing its complete
resorption: in this way, a stable interface is maintained long
enough to promote the subsequent interaction with collagen and
biomolecules, which ultimately results in a strong bonding
interface between the implanted glass and the living tissues.3,4
The bioactive response results in high biocompatibility, fast
integration and better stability of bioglass implants over time.5
Clinical applications of compact bioglasses are in middle-ear
prostheses, jaw, face and nose reconstruction, dental and non- or
low-load bearing implants in general.6,7 In fact, the low
mechanical strength limits the use of compact bioglasses in high
load-bearing cases, such as knee and hip replacement, which
require tougher bionert materials. However, bioglass particulates
and powders can be employed in orthopaedics as bone defect
fillers: even large bone cavities have been treated clinically with
bioglass granules.8 The most important clinical applications of
bioglass particulates are in the repair of periodontal defects,
whose treatment also benefits from the antibacterial action of the
glass, probably due to the alkaline environment created by the
initial ion release from the glass surface.9–11 Bioglass granules
have also been used to fill and repair defects in osteoplastic
frontal sinus surgery, where growth of new bone is again
accompanied by antimicrobial effects.12,13
BG45 particulates in these applications show superior
performances compared not only to bionert, but also to other
bioactive materials, such as synthetic apatite and apatite/
wollastonite (A/W) glass-ceramics. In particular, bone growth is
faster in bone defects filled with BG particles. In vivo studies
have highlighted new bone formation around the BG particles
and in the interparticle spaces, rapidly connecting and then
incorporating the particles at a significantly faster rate compared
to apatite and A/W, and suggested a key role of dissolved silicon to stimulate osteoblast activity and promote rapid bone
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growth.14,15 This osteoproduction ability, that is, the growth of
new bone on the surface of the particulates and throughout the
void space of the particulate array, as a consequence of enhanced
osteoblast activity, was identified as a special feature of BGs,
distinguishing them from other bioactive materials. The latter
share with BGs the osteoconductive properties (i.e., the ability to
produce a biocompatible interface for bonding with the living
tissues) but lack the enhanced activity of osteogenic cells in the
surrounding environment which create new bone not only on the
surface, but also away from the bone-implant interface.5,16
Besides promoting rapid bonding with bone, this property has
also been associated to the unique ability of a small range of BG
compositions (centered around the BG45 one) to form bonds
with soft tissues, such as muscles and ligaments, which is
exploited in some clinical applications.6 This enhanced (termed
class A) bioactivity leads to longer implant survivability,
compared to osteoconductive–only (class B) bioactive materials.17 Moreover, a link was found between osteoproduction and
tissue regeneration: the effect of BG particulates used to fill
a bone defect is essentially the in situ regeneration of new bone,
with the same structural and mechanical properties of the local
tissues to be repaired.18 This finding represented a significant step
forward in the field, as it highlighted the potential advantages of
focusing onto regenerating, rather than replacing, tissues, in
order to overcome the limits of first- (bioinert) and secondgeneration (bioactive) materials.5,18 Thereafter, a large body of
research work has focused on third-generation biomaterials, that
is, biocompatible materials able to enhance the activity of
osteogenic cells and, in practice, stimulate the body’s own repair
mechanisms to regenerate living tissues.
Besides the in situ tissue regeneration in bone defects filled with
BG powders, illustrated above, another exciting route to exploit
the 3rd-generation bioactive properties of BGs is in vitro tissue
engineering.19,20 In this case, a suitable scaffold is seeded with
patient or donor cells, which, if the conditions are favourable,
proliferate and grow 3-D tissue outside the body; at this stage the
scaffold containing the tissue-engineered matrix is implanted in
the patient, where it slowly degrades to non-toxic products, while
being replaced by connective tissues which integrate the new
tissue into the damaged site.
A critical issue is the ability of the scaffold material to guide
cellular attachment and promote bone growth. It has explicitly
been shown that the ions released by partial dissolution of BG45
activate genes that promote differentiation and proliferation of
osteogenic cells.21,22 Further desirable features of the scaffold are
good biodegradability and a highly porous structure: whereas
scaffolds made from sol–gel BGs have been shown to induce
mineralizations of osteogenic cells, and thus have strong
potential for tissue engineering,23,24 3D porous scaffolds based on
the original melt-derived BG45 have also been fabricated using
special methods, which additionally yield enhanced mechanical
properties due to partial crystallisation of the glass.19 Therefore,
there is still high interest in the same BG45 core composition,
which revolutionised the field of biomaterials 40 years ago.
Having established that the sodium, calcium and silica ions
released from the glass stimulate osteogenesis away from the
glass surface,21,22 the special properties of this composition must
reflect its ability to release critical amount of these ions in
the environment, creating favourable conditions for the cell
This journal is ª The Royal Society of Chemistry 2010
processes. An indication in this sense may come from the
different activity of different BG compositions, whose silica
release rate is different.16,25
These issues highlight the critical importance of the initial
inorganic stages which follow contact of the bioactive glass with
a physiological medium: these processes directly determine the
rate and the form in which Na+, Ca2+ and silicate ions are
dissolved, entering the surrounding environment, where they
promote apatite deposition and affect cell activity. Because
a fundamental understanding of how glasses interact with and
dissolve in an aqueous medium is lacking even for the simplest
compositions, it is not surprising that this kind of information is
still not available for complex multicomponent compositions
such as BGs. This is a field where the atomistic resolution of
molecular simulations plays an important role, by providing
access to structural and dynamical properties which are hardly
available through other experimental techniques. In the last five
years, classical26,27 (i.e., based on empirical potentials) and ab
initio28 simulations of bioactive glasses have started to unveil the
atomistic features of these complex materials with unprecedented
accuracy, and to use these data to identify the hidden links
between a glass composition and the corresponding biological
activity. In particular, a powerful combination of classical and ab
initio models, covering different space-time scales and levels of
accuracy, turns out to represent the best strategy, to overcome
the limits and make the most of the advantages of both
approaches. Based on the previous discussion, the target of these
computational investigations should be on properties which,
directly or indirectly, affect the dissolution of modifier cations
and of the phospho-silicate network in a biological medium.
Whereas indirect probes have thoroughly explored the bulk
bioglass structure in the short- and medium-range,29,30 the focus
of computational investigations has recently shifted towards the
glass surface,31 and its interface with an aqueous environment,32
in an attempt to directly look at the processes occurring in this
crucial region.
This paper will review recent computational efforts aimed at
exploring bulk and surface properties of bioactive glasses, illustrating the progress done so far, and the potential for further
advances.
Computational methods
Melt-and-quench MD of glasses
The natural approach to obtain a model of a melt-derived glass is
to simulate the quench-from-the-melt experimental synthesis.
Molecular Dynamics simulations have been successfully used for
this purpose in the last 35 years,33 and a large variety of meltderived glass compositions, ranging from silicate,34 to phosphate,35 to chalcogenide36 glasses, have been modelled in this
way. Starting from an initial random arrangement of atoms, MD
is used to heat the system to high temperature, then cool it
through the glass transition, down to room temperature. Two
main problems affect the MD melt-and-quench procedure: (i) the
relatively short time scales which can be reached in MD
simulations, of the order of 10–100 nanoseconds for classical
MD, impose cooling rates that are several orders of magnitude
faster than those used in practical glass synthesis; (ii) periodic
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boundary conditions, routinely employed to remove surface
effects in MD simulations,26 enforce structural consistency over
length scales close to the side of the MD box, and this consistency
is obviously fictitious in the case of amorphous materials.
Together with the limited size of the system, typically consisting
of few thousands of atoms enclosed in a simulation box of few
these effects can result in limited structural relaxation,
tens of A,
and lead to a final model with a higher fictive temperature than
the corresponding experimental composition.37 However, despite
these important differences, detailed investigations have shown
that the medium-range structure of silicate glass samples can be
determined with reasonable accuracy using cooling rates around
10 K/ps.38 This is supported by a very large number of computational studies of glasses using similar settings, which have
resulted in short- and medium-range structural features in
agreement with available experimental data. MD simulations are
therefore the most suitable computational tool to obtain
atomistic models of melt-derived glasses, provided that interatomic forces can be determined with sufficient accuracy: this last
requirement can be accomplished either by classical MD with an
accurate force field, or by ab initio MD.
Classical MD
Several interatomic potentials are available for classical MD
simulations of pure and modified silicate glasses,39–43 and, with
additional extensions, some have been specifically applied to
model bioactive glass compositions.44–47 The multicomponent
nature of these materials poses a serious challenge to standard
empirical force fields, as shown by the limited number of classical
MD studies of quaternary oxide glasses. A recent study has
shown that, for these systems, rigid-ion (RI) potentials do not
provide a satisfactory representation of medium-range structural
features, such as the inter-tetrahedral angle and connectivity.48
The reproduction of these properties, which critically affect the
glass dissolution and bioactivity, is substantially improved
through the explicit inclusion of the oxide ion polarisation in the
potential, in a shell-model (SM) approach.43–49 A comparison of
the process of glass-formation from the melt using RI and SM
potentials, using the corresponding ab initio MD data as an
unbiased reference, has shown that the better performances of
the SM potentials reflect a more accurate description of the
dynamical interconversion between Qn species during the cooling
of the melt (a Qn species is a Si or P atom bonded to n bridging
oxygens).48 Because the latter processes involve the transient
formation of structural defects, such as intermediate mis- (underand over-) coordinated Si and P,50,51 it is essential that the
structure and energetics of these defects is well accounted for by
the potential. The inclusion of polarisable oxide ions significantly
improves this feature with respect to the RI potential, and ultimately determines a more realistic description of the glass
formation, and thus a more accurate medium-range structure.48
Using SM potentials, the force acting on a polarisable atom
specifically depends (in an approximate, but effective fashion) on
the local environment surrounding it: this feature is important to
correctly describe metastable and distorted environments, such
as those found in disordered bulk phases and at surfaces. In
particular, the mean-field account of these effects, implicit in RI
potentials using partial ionic charges, does not seem sufficient to
6850 | J. Mater. Chem., 2010, 20, 6848–6858
fully reproduce the diverse bonding environments found in
bioactive glasses. Whereas these many-body effects are best
accounted for by ab initio calculations with explicit inclusion of
the electronic structure,28 polarisable potentials represent a valid
approximation,52 at least when one is mainly interested in
modelling the structure of multicomponent bioactive glasses. It
should be remarked that, whereas the use of an SM potential
would be recommended in all cases where the medium-range
structure of a melt-derived multicomponent glass is the main
target, RI potentials can still provide a reasonable alternative in
many cases, as shown by their overall good performance in
modeling binary and ternary oxide glasses.40,44,53,54
Ab initio MD
Ab initio (AI) MD, with the highly accurate quantum-mechanical calculation of ionic forces,28 represent the best computational approach to tackle challenging systems such as
bioglasses, without the bias and transferability issues affecting
calculations based on empirical potentials. In the Car–Parrinello
(CP) AIMD approach,55 electrons are considered as additional,
fictitious degrees of freedom whose motion is dynamically
coupled to the real ionic motion. The CP dynamics keeps the
electrons close to their ground state while the nuclei move, so
that repeated electronic minimisations to find the electronic
ground state for each new nuclear configuration visited during
the MD trajectory, as in standard AIMD, are avoided. Within
the typical framework of solid-state ab initio calculations,
involving plane-wave basis sets, pseudopotentials and Density
Functional Theory (DFT),56 this makes CPMD simulations very
efficient and suitable to tackle relatively large periodic systems,
although significantly smaller compared to those affordable by
classical MD. Because amorphous systems require relatively
large supercells, the CP method is a suitable tool to perform
AIMD of glasses, and its first applications in this sense date back
to 1995.57 In most cases, the calculations have involved a mixed
classical-AI approach, where the quench-from-the-melt is carried
out using classical MD, and the glass structure so generated is
then used as starting point for a CPMD run58–61 or for a static ab
initio structural optimisation.62 This approach only allows for
local, short-range relaxations, and does not produce an ab initio
model of the medium-range structure, which is entirely determined by the classical MD run, and thus by the quality of the
empirical potential used in the first stage. In any case, the small
size of the AIMD models, which – even using state-of-the-art
computational facilities and codes – must be limited to a few
hundreds of atoms due to their massive computational requirements, would hardly produce a statistically sound description of
medium-range features, such as those involving the glass
network connectivity. Mixed classical-AI models of bioactive
glasses are best suited and have been used to investigate their
short-range structure (e.g., the coordination enviroment of
modifier cations), as well as other features which have a local
character and mostly depend on the short-range structure, such
as vibrational and electronic density of states, and NMR
parameters.58–64
Models of the bulk glass obtained by full AIMD (that is, using
AIMD to perform the whole melt-and-quench procedure) are
less common, due to their substantially higher computational
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cost, and are especially useful to investigate with high accuracy
the structure and dynamics in the melt precursor, and the glass
formation mechanism:48,51,65 exploring the larger configurational
space accessible in the melt state can expose properties and
effects that are also relevant, but harder to detect, in the glass.
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AIMD of glass surfaces
Modelling the reactivity of bioglass surfaces is another case
where an AI approach is essential. Classical models using
empirical potentials are sufficiently adequate to reproduce the
structural relaxations at the dry surfaces of modified silicate
glasses,66,67 also including bioactive compositions.31,47 However,
ab initio methods are generally much better suited to model the
electronic rearrangements induced by the formation and
breaking of chemical bonds that accompany chemisorption and
dissolution processes at solid surfaces. CPMD is a well-established tool to investigate adsorption and reactivity at the surface
of crystalline68 and amorphous67,69,70 oxides, and it has recently
been applied to follow the hydration of the BG45 surface.32,71
The CP dynamics can be effectively employed as a means to
enhance the sampling of the configuration space, in order to
efficiently locate relevant minima characterising the reactivity of
adsorbed molecules. Special techniques, developed to model
activated processes and determine the corresponding energy
barriers, can also be used in combination with CP dynamics72–74
and have recently been applied to study the hydration of BG
surfaces.71 Alternative to CPMD simulations, ab initio structural
optimisations of cluster models, employing DFT with hybrid
(B3LYP) functionals, also provide a highly accurate picture on
the energetics of chemisorption on specific surface sites.75,76
There are some indications that the limited structural relaxation
inherent in the cluster approach can alter the surface reactivity
with respect to the ‘‘real’’ sample,76,77 and periodic B3LYP
calculations of extended surfaces78 would appear more realistic
from this perspective, but no applications to bioglass surfaces
have been reported so far.
Computational models of bioglasses
Focusing on the bioglass dissolution
The 45S5 Bioglass composition (45SiO2 – 24.5Na2O – 24.5CaO
– 6P2O5, wt%) lies at the center of the ternary diagram of Fig. 1.
As discussed in the Introduction, this melt-derived composition,
and some of the other compositions in region A of Fig. 1,
represent today the key reference for bioactive glasses, due to
their ability to regenerate, as well as replace, tissue. Following
dissolution of class-A bioglasses, specific amounts of Si, P, Na
and Ca ions are released from the glass, creating local concentration gradients in the physiological environment, which can
approach critical values needed to stimulate the cellular
activity.18,21 Because the partial dissolution of the glass, with the
associated ion release, turns out to govern both the apatite
deposition and the gene-activation processes, it is clear that
fundamental studies of bioglasses must primarily address the
features related to their dissolution. In a way, this simplifies the
issue, shifting the focus from the highly complex biochemical
transformations induced by the released ions, to the simpler –
from a computational viewpoint – inorganic dissolution steps.
This journal is ª The Royal Society of Chemistry 2010
Fig. 1 Kinetic diagram of bioactivity:1 only compositions inside region
B are bioactive and form a bond with bone. Bioactivity inside this region
increases going towards the centre: glasses in region A (such as 45S5
Bioglass) show the highest bioactivity, and are able to bond to both
hard and soft tissue. Glasses in region C, containing more than 60% SiO2,
are bio-inactive, those in region D are too soluble and thus quickly
resorbed, whereas compositions in region E do not form glasses.
Medium-range structure of bulk bioglasses
Given that the bioactivity level of a significant number of
different melt-derived glasses has been measured (Fig. 1), these
data provide a good reference for MD simulations, which can be
used to identify structural features linked to bioactivity, or to the
lack of it. Because the features relevant to the bioactivity span the
medium-range structure, they have commonly been investigated
using classical MD. Shell-model MD simulations were carried
out to compare the structural features of three melt-derived
compositions of different bioactivity, ranging from BG45, to
a less bioactive, class B, composition (BG55) and to a bioinactive
composition (BG65), containing 55 and 65 wt% SiO2, respectively.45,79 The MD models of the three structures are shown in
Fig. 2. The most evident structural difference is the much higher
fragmentation of the BG45 composition, with large void regions
occupied by Na and Ca cations; conversely, the bio-inactive
BG65 glass is characterized by a significantly cross-linked
phosphosilicate network, and BG55 represents an intermediate
situation. This visual difference can be quantified using the Qn
distributions extracted from the MD trajectories, shown in Fig. 3
for the three glasses. The BG45 structure is dominated by chains
of Q2 silicates, whereas both BG55 and BG65 structures are
predominantly Q3. The increasing cross-linking between the
silicate chains with increasing silica content, and with decreasing
bioactivity, is denoted by the significant fraction of Q4 species in
Fig. 2 Structure of (left) class-A bioactive BG45, (centre) class-B
bioactive BG55, and (right) bio-inactive BG65 glass, as obtained from
shell-model MD simulations. The phosphate and silicate tetrahedra are
shown as sticks, whereas green and cyan spheres denote sodium and
calcium cations, respectively. Reprinted with permission from ref. 45.
Copyright 2007 American Chemical Society.
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Fig. 3 Distribution of Qn species for the three glass compositions of
Fig.2. Reprinted from ref. 2, copyright 2009 Royal Society.
BG65 only. Analogously, whereas most phosphate groups are
isolated (orthophosphate) in BG45, an increasing fraction of
them is found linked to one, or even two silicon atoms in the less
bioactive compositions. In other words, isolated and highly
mobile phosphate groups appear as a predominant feature
associated to class A, but not class B, bioactive glasses.80,81
The glass network connectivity (NC), defined as the average
number of bridging oxygens bonded to a network-forming atom
T,82 is a useful parameter to condense the information contained
in the Qn distribution, with lower NC values denoting a more
fragmented structure. The general empirical correlation between
NC and the actual glass bioactivity,82,83 with a limiting value
around NC ¼ 3 separating bioactive from bio-inactive compositions (the NC for BG45 being around 2 and that for BG65
around 3.2), essentially reflects the higher solubility of lessinterconnected glass structures, but it does not provide much
more insight. In general, the release of soluble silica in solution,
also instrumental to the gene-activation properties, will be easier
when most Si are incorporated in silicate chains which do not
intersect. In this case, because it requires breaking Si–O–Si
bridges, silica dissolution will bear a lower energetic cost,
compared to a structure with a higher NC, where silicate chains
are cross-linked to each other, forming rings of different size. The
possible correlation between chain/ring structure, silica dissolution and glass bioactivity was previously inferred by comparing
the activation energy for silica release of glasses with different
bioactivity,84 and observing that the thermal condensation of
chains into closed rings of different sizes slows down dissolution
and reduces bioactivity.85 Whereas it is hard to actually measure
the density of chain and ring nanostructures in glasses using
experimental probes, extracting this information from MD
trajectories is relatively straightforward. Fig. 4 shows the distributions of ring sizes and of the length of non-intersecting chains
for the three glass models already discussed.79 This analysis fully
confirms the association between high bioactivity and predominance of non-interconnected silica chains in the bulk structure
(as for BG45) and the loss of bioactivity when these fragments
intersect and form closed rings (as for BG65). The faster dissolution of silica incorporated in chains than in ring structures
reflects the frequent termination of chains by Q1(Si), which
reduces the number of Si–O bonds that must be broken to detach
these fragments from the matrix and release them in solution.
The importance of MD structural models to expose these and
related features cannot be underestimated: whereas the network
6852 | J. Mater. Chem., 2010, 20, 6848–6858
Fig. 4 Distribution of ring sizes (top) and of chain lengths (bottom) for
the BG45, BG55 and BG65 compositions.79 Also shown are (top right)
examples of rings of size 4–6, and (bottom right) the non-crosslinked
chain fragments extracted from the BG45 model. Reproduced in part
from ref. 79, published by RSC.
connectivity and the corresponding potential bioactivity can in
some cases be estimated from the glass composition, a classification based on the NC is not always accurate. This reflects the
frequent failure of some basic assumptions needed to estimate
NC, such as regular coordination for network-forming ions and
homogeneous glass structure.30,83 The MD data provide a direct,
and therefore more accurate, measure of NC, and at the same can
yield a much deeper insight into the links between composition
and bioactivity. For instance, the empirical NC ¼ 3 upper limit
for bioactivity does not reveal the substantial structural difference between compositions with NC below and above that limit,
namely the dominance of chain vs. ring motifs in the structure,
which highlights the role of non-interconnected chain fragments
in the silica dissolution. Given the established function of dissolved modifier ions and silica species in the osteogenesis, the
presence of free (i.e., not bound to the glass matrix) di-, tri- and
tetramer silicate chains in the bulk BG45 glass (Fig. 4) suggests
that these dissolved fragments can directly reach and interact
with the cell membrane, and influence gene activation.
Using experimental data on in vitro or in vivo bioactivity,
these findings showed the effectiveness of using MD models to
expose the structural basis of a different bioactivity. On a similar
fashion, comparing the structural arrangement of modifier Na
and Ca cations coordinating silicate and phosphate in several
bulk structures of glasses with different bioactivity, suggested an
association between clustering of calcium cations and loss of
bioactivity.45,80,81 For instance, sodium modifier cations are
homogeneously distributed in the BG45 and BG55 models,
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whereas they start to aggregate in small clusters for the bioinactive BG65; on the other hand, isolated clusters of calcium
modifiers are already found in the bioactive compositions, but
a marked clustering behavior emerges only in BG65.45
Whereas the limited time scale and sample size of standard
MD simulations is not suitable to investigate phase separation
phenomena, the MD trajectories can provide a quantitative
measure of the tendency of a composition to form inhomogeneous nanodomains, for instance by comparing the cation
coordination environments to the hypothetical ones corresponding to an ideal uniform distribution.44,45,80,86 The analysis of
BG compositions containing variable amounts of phosphorus80,81 confirms that bioinactive compositions are characterised by nanoaggregates of calcium phosphate, separated from
silica-rich regions, as illustrated in Fig. 5.
The observed correlation between enhanced tendency to form
clusters and lower glass bioactivity reflects experimental results
showing the higher resistance to dissolution of phase-separated
glasses,87 and can be interpreted on the basis of the lower
mobility of ions trapped in segregated regions, whose formation
breaks the continuity of the modifier migration channels running
across the bulk structure.88 A similar correlation between ion
clustering and enhanced durability can be detected in MD
simulations of potentially bioactive fluoro-phosphosilicate
glasses:89,90 the strong affinity of fluoride for sodium or calcium
cations results in F removing Na+ and Ca2+ from silicate and
phosphate, with the formation of Na,Ca,F-rich regions, separated from the phosphosilicate network. An increasing amount
of CaF2 replacing CaO results in a higher dissolution rate, which
again can be associated to the reduced clustering measured by
MD. It is interesting to note that the nature of the clustering is
different in F-free and F-containing bioglasses: in the first,
strong Ca2+-PO43 affinity leads to calcium phosphate-rich
Fig. 5 Structures of BG65 (left) and of a [36.3 SiO2: 24.4 Na2O: 27.2
CaO: 12.1 P2O5] composition (right). The top panels only show the silicate network, whereas Ca (cyan) and P (yellow) atoms are also shown in
the bottom panels. Reproduced from ref. 81, Copyright 2008, with kind
permission of Societ
a Italiana di Fisica.
This journal is ª The Royal Society of Chemistry 2010
nanodomains,80 whereas in the latter, stronger Ca2+-F association results in the phosphate groups being actually depleted of
modifier cations, and moving to the silicate-rich region.89 In both
cases, however, ion clustering (as highlighted by the MD models)
leads to a reduced dissolution rate (as measured experimentally).
Models of the bioglass surface
Ab initio calculations of site reactivity: cluster models
Modelling the bulk structure of bioactive glasses is an important
and necessary step to understand at a fundamental level the
processes that occur once the glass is immersed in body fluids.
Bulk structural features such as network connectivity, distribution of Qn species and ion clustering, albeit useful to rationalise
the bioactive behavior, are indirect probes of the glass dissolution
process. More direct studies target the glass surface, that is the
region where the fundamental interactions with the surrounding
medium take place.
Computer simulations have started focusing on the fundamental interactions at silica surfaces, also relevant in the context
of bioactivity, since 1995. Earlier semiempirical molecular orbital
(MO) calculations of small clusters have studied the adhesion
and reactivity of small rings typically found on silicate surfaces,
such as the trisiloxane (3-M) unit.91 Even though these models
could not incorporate the influence of extended surface relaxation, they highlighted a few fundamental issues, which were
confirmed by subsequent more sophisticated calculations: due to
their high internal strain, hydrolysis of 3M-rings by water
dissociative adsorption was found to proceed with a very small
energy barrier, even when only a single water molecule is
involved.92 Even though the measured barrier was underestimated, this result reflects the experimental evidence that these
rings, initialy formed by thermal condensation of silanol (Si–OH)
groups on the silica surface, are rapidly rehydrolysed upon water
adsorption.93
High-temperature treatment also leads to the formation of
highly reactive disiloxane (2-M) rings on the silica surface.94 The
presence of 2-M rings on the dry amorphous SiO2 surface, where
they play an important role in optical fibers technology,95 has
encouraged several theoretical studies, where their reactivity was
typically probed through their interaction with a water molecule,
and the energetics and mechanism of hydrolytic ring-opening
was explored using CPMD and periodic surface cells,69,70 or
energy minimisation of embedded clusters.76,96 The wide range of
energy barriers measured by different methods highlights the
complexity of this apparently simple problem, from a computational perspective. By comparison with the experimental
hydrolysis rates, it would appear that using standard DFT and
periodic supercells gives more accurate results than cluster
calculations with hybrid functionals, illustrating the greater
importance, for these systems, of a realistic treatment of local
surface relaxations, through a large periodic supercell.76 The
observed dependence on the local geometric distortions also
indicates that the kinetic barrier to hydrolytic opening of small
rings can be significantly altered in different surface environments. This effect turns out to be especially important for the
present topic, because small, strained rings characterise the
surface of bioactive silicate glasses as well.
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Using ab initio MO calculations of cluster models of the
surface sites found on bioactive silicate materials, Sahai and
coworkers have proposed that exposed 3-M rings can attract and
guide the deposition of calcium phosphate in an aqueous environment at approximately neutral pH, such as that found in
a physiological medium.97,98
As shown in Fig. 6, this model involves an hydrated, but
otherwise unreacted, 3-M ring site: the structural arrangement of
the Si and O atoms of the closed ring was proposed as the key
feature favouring calcium phosphate nucleation on the biomaterial surface.97
The important role of Ca2+ ions incorporated in amorphous
silica surfaces was recently highlighted by Bolis et al.,75 who
combined experimental results on methanol adsorption on
Ca-modified amorphous silica with B3LYP cluster calculations.
Different cluster models were studied, to take into account the
heterogeneous distribution of Ca sites in bioactive calcium silicate glasses.99 In these models, a methanol molecule interacts
with a Ca2+ anchored on top of a hydrogenated 3-M or 4-M silica
ring (Fig. 7). The high binding energy of the Ca2+-CH3OH
adducts, around 1 eV, shows that Ca enhances the reactivity of
the surface: based on the ab initio reaction paths, the surface
will then contain both molecular and dissociated methanol
products.75
These models show that, despite the internal strain which
should in principle make them unstable, unreacted small rings
are key surface features of silicate biomaterials, as shown in both
Fig. 6 and 7. This suggests a different behavior of these sites in
the biomaterial surface, compared to the SiO2 surface, in which
small rings are rapidly opened after contact with water, as discussed before. Together with the substrate-dependence of the
Fig. 6 Models of calcium and phosphate attachment onto threemembered silicate rings. Si, P, O, Ca and H atoms are coloured blue, grey,
red, cyan and white, respectively. Reprinted from ref. 97, Copyright
(2005), with permission from Elsevier.
Fig. 7 Cluster models of methanol attachment on different surface sites
of Ca-modified silica. Reprinted in part with permission from ref. 75.
Copyright 2008 American Chemical Society.
6854 | J. Mater. Chem., 2010, 20, 6848–6858
kinetic barrier for the opening of 2-M rings, also discussed
before, these results highlight that one cannot simply extrapolate
the properties of the pure silica surface to the surface of bioglasses, and realistic/specific models of the surface of bioactive
glasses are highly needed. Cluster models have some limitations
in the case of multicomponent glasses, because of the very large
number of possible surface sites and environments, whose
relative relevance is hard to predict a priori. For instance, Rimola
et al. have shown that a large cluster model of the aluminosilicate
surface, including neighboring Brønsted and Lewis acid sites, is
needed to adequately reproduce the catalytic effect of the surface
on the peptide bond formation, whereas a small cluster including
either the Brønsted or Lewis site yields an inaccurate energetic
balance.77
Therefore, an effective approach to study surface reactivity
in bioglasses involves large-slab surface models (whose 2-D
periodicity allows the model to cover an adequate portion of the
heterogeneous surface and long-range relaxations), coupled with
finite-temperature MD, which improves the sampling of relevant
sites.
Ab initio calculations of site reactivity: 2-D slab models
In situ surface-analytic methods can characterise a silica surface
by examining the response to the interaction with a polar
molecular probe, such as water or methanol,100 but these
experiments essentially provide an average picture of the surface
sites. A more detailed, site-by-site characterisation can be performed using CPMD simulations in order to model the freshly
created, dry surface of BG45, identify the potential adsorption
sites, and probe their strength based on the reactivity with
water.72 A relaxed slab representing the BG45 surface exposes
undercoordinated Si atoms (Si3c), modifier cations and nonbridging oxygen (NBO) atoms, 2-M and 3-M rings (Fig.8).71 Due
to the small silica fraction of the bioactive composition, not all
dangling Si–O bonds created by the fracture can be passivated by
the surface relaxation, and some are either left exposed (Si3c) or
incorporated in strained small rings: in fact, small rings had been
identified in CPMD of the BG45 melt precursor,51 confirming
that their formation partially compensates the simultaneous
breaking of several Si–O bonds, which can occur either during
the melt dynamics or upon surface fracture.
Following a short room-temperature CPMD run to explore
the BG45 surface and locate stable adsorption sites of a single
water ‘‘probe’’, the strength of these sites was quantitatively
Fig. 8 Selected single-water adsorption structures on the BG45 surface,
as obtained by CPMD simulations.71 Si, O, Na, Ca and H atoms are
coloured blue, red, green, cyan and white, respectively, with Si in reactive
sites highlighted in light blue.
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compared based on the corresponding water adsorption energy
(Eads).71 The strongest sites are the Si3c, where an adsorbed water
spontaneously dissociates forming two silanols, provided that
a Lewis base, typically an NBO, is available to accept the water
proton, according to the general scheme:
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A + H2O + Si–NBO ¼ A–OH + Si–NBO–H
(1)
where A is the acidic site, such as Si3c. Molecular adsorption is
observed on other sites: strong molecular adsorption modes (Eads
0.8–1.3 eV) involve the molecule donating one or two
hydrogen bond (Hb) to exposed NBOs, and coordinating one of
more Na or Ca cations, which behave as Lewis acids (Fig. 8, left
panel, and Fig. 9). The high hydrophilicity of exposed modifier
cations, together with the fragmented nature of the glass structure, provide suitable pathways for water penetration inside the
surface, where the molecule can enter open patches rich in Na or
Ca (Fig. 9): as discussed below, this feature can play a key role in
the glass dissolution.
On the other hand, 2-M and 3-M rings represent weaker
adsorption sites on the BG45 surface: the initial adsorption of
water on a small ring, as in the right panel of Fig.8, is often
followed by the molecule migrating to another, stronger site,
such as the Na+/Ca2+-NBO pair. Accurate determination of the
energy profiles for the water dissociative adsorption – ring
opening reaction71 showed that, whereas the internal strain of the
2-M ring still makes it thermodynamically favourable, the
process is hindered by a kinetic barrier of 0.62 eV. The barrier is
almost twice as high as that calculated within the same computational framework for hydrolytic 2-M ring opening on pureSiO2 glasses:70 this important difference reflects the different
local structure of BG45, whose fragmented and flexible character
reduces the geometrical strain on exposed 2-M rings, compared
to the more rigid SiO2.76 Similar considerations apply to 3-M
rings. Also taking into account the models discussed before and
exemplified in Fig. 6, 7, the higher kinetic stability of small rings
exposed on bioglass surfaces can have important consequences
for the bioactive behaviour of these materials. However, the
discussion so far has only concerned gas-phase adsorption; the
surface reactivity can be significantly altered in the actual interface with bulk liquid water.
This possibility was tested in CPMD simulations of the liquid
water-BG45 interface.32 Large-scale CPMD simulations (the
hydrated system contained up to 355 atoms) were needed to
study this interface, in the first atomistic model of the BG surface
immersed in a realistic aqueous environment (Fig. 10).32
Fig. 9 CPMD snapshot showing water penetration inside the BG45
surface.71 Atom colours as in Fig.8.
This journal is ª The Royal Society of Chemistry 2010
Cooperative interactions between water molecules favour
water dissociation and hydroxylation of exposed NBOs, but do
not lead to opening of small rings, at least on the CPMD timescale. This also seems to reflect the low affinity of these rings for
water, compared to more hydrophylic surface sites, such as
modifier cations. Therefore, even if the thermodynamic driving
force will eventually result in their opening, it is plausible that
a fraction of the 2-M and 3-M rings initially formed will survive
unreacted on the fully hydrated BG45 surface (with some degree
of protonation of the associated NBOs, see Fig. 11) long enough
to act as templates in the bioactive mechanism.97,98
Compared to gas-phase adsorption, water dissociation is more
likely in the liquid film in contact with the surface: dissociation
typically occur at exposed Si–NBOs, which are tranformed into
Si–OH silanols, while the resulting OH is stabilized by an acidic
site, as in Scheme 1. Besides Si3c, the BG45-liquid water interface
provides two additional routes for this process: (i) the required
local Lewis acidity is provided by a group of 2–3 modifier
cations: structures with the OH at the centre of a triangle
formed by Na+ and Ca2+ ions are frequently observed (Fig. 11,
bottom panels); (ii) a chain of proton hoppings along H-bonded
water molecules essentially shifts the OH charge to a different
region, where it is again stabilised by modifier cations.32 The
balance between these effects is probably dependent on the glass
Fig. 10 CPMD model of the water-BG45 interface. Reprinted with
permission from ref. 32. Copyright 2009 American Chemical Society.
Fig. 11 Reactive dynamics of a water dimer interacting with a 2-M ring
on the BG45 surface (top view): the atoms involved in the process are
highlighted as ball-and-stick. Atoms colours as in Fig. 8. Reprinted with
permission from ref. 32. Copyright 2009 American Chemical Society.
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composition, but the net result is that, mostly through the
participation of Na and Ca Lewis acids, NBOs exposed on BG
surfaces will be immediately protonated upon immersion in
aqueous body fluids.
The CPMD simulations of the extended interface also yielded
insight into the BG45 dissolution mechanism. The strong
hydrophilicity of Na+,Ca2+ cations balances the low affinity of
water for the exposed siloxane fragments.101,102 This effect, as
noted before, combines with the high fragmentation of the BG45
silicate network to attract H2O molecules towards Na-rich
patches on the surface (as in Fig.9), which allow them to penetrate and easily access the inner glass regions, without need to
break or significantly distort Si–O–Si bonds. The facile penetration of water contributes to the fast initial dissolution of BG45,
which is a key feature of this biomaterial. In agreement with
other simulations,47,103 the CP models highlighted a significant
sodium enrichment of the upper surface layers, compared to the
bulk. Based on these results, the mechanism of Na+/H+ ion
exchange, which is the first stage of the glass surface degradation,1 involves dominant Na+-H2O interactions established
through sodium enrichment of the surface, which promotes
water transport inside the glass structure. Dissociation of these
molecules at Na+-NBO acid–base pairs leads to Na+-OH
complexes, before Na+ release. Whereas interfacial ion exchange
occurs on longer time scales and is not observed during the MD
dynamics, CP models of the ion-exchanged surface32 showed that
stronger interactions between water and the phosphosilicate
network are established after Na release, as if these direct interactions were initially screened by the presence of the more
hydrophilic Na cations in the outer layers.
Extended slab models: classical MD
The ab initio models are invaluable to probe the activity of
individual sites identified on the surface. This local information
can be used (in a multi-scale approach) to compare the extended
surface structure of two compositions of different bioactivity, in
order to complete the conclusions made on the basis of their bulk
structure. Whereas classical simulations are not adequate to
study reactivity, they can provide an accurate representation of
the distorted bonding and coordination environments found on
the dry BG surfaces, thus enabling the generation of larger
statistical samples, needed to compare two surfaces of different
compositions. Classical SM-MD was recently used to model the
surfaces of BG45 and BG65 glasses.31 The main sites found on
these surfaces are consistent with the ab initio models; based on
the ab initio data regarding their activity, several conclusions can
then be drawn from the concentration of these sites in the SMMD samples of the two surfaces. Sodium enrichment is observed
in the surface of both BG45 and BG65 glasses, but the actual
sodium concentration in the surface of BG45 is much higher
(Table 1). The two surfaces contain similar amounts of Ca2+ and
NBO ions, whereas the concentration of Si3c, 2-M and 3-M rings
is higher in the bio-inactive BG65. Besides these residual defects,
surface relaxation restores the bulk network connectivity to
a large extent, with only a slight decrease in the surface NC. For
the BG45 surface, this decrease results in a higher fraction of
isolated orthosilicate (SiO44) tetrahedra on the surface than in
the bulk. Direct release of these free silicate species in solution, as
6856 | J. Mater. Chem., 2010, 20, 6848–6858
Table 1 Concentration (nm3) of relevant sites in the top layers of BG45
and BG65 surface models. Reproduced with permission from ref. 31.
Copyright 2010 American Chemical Society
site
BG45
BG65
Na+
Ca2+
Si3c
NBO
2MR
3MR
7.0
2.3
0.13
11.75
0.17
0.58
4.3
2.48
0.64
10.67
0.32
1.18
of other small chains, contributes to the fast initial degradation
of BG45, and can affect the processes occurring at the cell
walls of living tissues, where they are rapidly transported.
The surface compositions in Table 1 also show that the fast
degradation of the BG45 glass reflects a higher density of Na+NBO pairs, whose role in enhancing the surface hydrophilicity
had been revealed by the ab initio calculations. Combined with
the high fragmentation of the glass network at the BG45 surface,
this will make the initial attack by the contact solution much
more effective compared to BG65. Table 1 does not support
a similar role for Ca2+-NBO pairs, at least in the initial degradation stages, which are mostly driven by the Na+-H2O interactions. Based on the site-by-site water dissociative behaviour
emerged in the CPMD simulations, one can translate the site
density in Table 1 into density of silanol groups formed after
immersion: the small difference, estimated in this way, between
BG45 and BG65 surfaces31 points out that the silanol density
alone cannot explain the special bioactivity of BG45. It is the
combination of marked surface hydroxylation with the high
network fragmentation and sodium content, together with the
presence of free silicate fragments, which determines the BG45
properties.
Finally, the higher density of small rings observed on
the surface of bio-inactive composition is not completely
unexpected, looking at the ring distributions in Fig. 4. This
result, however, would appear incompatible with their suggested
role as template for Ca-P deposition. A possible explanation
involves a different reactivity of these rings in BG45 and BG65: it
has been reported that Ca-P deposition does not depend on the
mere presence or concentration of small rings on the glass surface
before contact with body fluids, but it requires a specific structural transformation of these units following immersion.104
Final remarks
The ability of the dissolution products of class-A bioglasses to
activate genes which stimulate repair of living tissues emphasizes
the need to understand at a fundamental level the structural and
dynamical features which affect glass dissolution in an aqueous
medium. Modelling these complex systems and effects requires
a combination of computational approaches, covering different
scales. Classical MD simulations using polarisable potentials
have proven adequate to explore bulk structural features in the
medium-range and link them to the experimental dissolution rate
of different compositions. Ab initio techniques have allowed the
study of the site-by-site reactivity of the surface of these materials.
This information is essential to discuss larger slab models of the
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surface, obtained using classical MD. The observation that
surface relaxation tends to restore the bulk structure to a large
extent supports the importance of focusing on indirect, bulk
structural features to rationalise the properties of these glasses,
but of course direct probes of surface reactivity are indispensable.
Further progress in this field, towards modelling glass dissolution in a realistic medium, and including the interaction with
biomolecules, depends on advances in computational power and
methodologies. With the continuous growth in the number of
available processors, an important challenge involves adapting
parallel simulation codes to make effective use (i.e., scale linearly
with the number of CPUs) of this increasingly powerful, and also
rapidly changing, hardware. A key issue is the development of
portable linear-scaling algorithms which would allow the codes to
continue to scale in future hardware architectures.105 Whereas
these advances are likely to allow future full-AIMD simulations
of the glass dissolution in realistic simulated body fluid,
a different strategy is needed in order to incorporate in the
models biological processes and interactions with biomolecules.
In this case, hybrid QM/MM approaches,106 in which different
parts of the systems are modelled with different levels of
accuracy, seem to represent a more effective route, for instance
combining an ab initio treatment of reactive parts with a forcefield description of unreactive regions. Further multiscale
strategies must also be considered, for instance the derivation of
high-quality and reactive forcefields from quantum-mechanics
calculations.41,107,108
Acknowledgements
The author would like to acknowledge financial support
from Royal Society (University Research Fellowship) and
EPSRC (First Grant EP/F020066/1), and collaboration with
A. N. Cormack and N. H. de Leeuw.
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