Fundamentals for the Compounding of
Nanocomposites to Enhance Electrical Insulation
Performance
Christopher Calebrese, Le Hui, Linda S. Schadler, J. Keith Nelson
Rensselaer Polytechnic Institute
Troy, NY
Abstract— Although it is undeniable that the promise of
enhanced dielectric properties through the use of nanotechnology
has generated worldwide interest in nanodielectrics in the last
decade, study of the experimental literature indicates that there
are numerous inconsistencies in the results obtained. In many
instances, it is likely that this is due to a lack of quality control
during the formulation of this new class of material. By
examining several nanocomposite examples, this contribution
seeks to shed some light on the likely causes for these
inconsistencies.
Through the paramount property of dielectric strength, it is
confirmed that poor dispersion and/or agglomeration is often the
cause of poor material performance. Examples are provided to
show how this can be rectified through the use of particle
functionalization and compatibilizers, the use of shear in
compounding, and the careful control of moisture. However,
good dispersion alone is not sufficient since some of the
techniques used may also lead to microcavity formation and
other
undesirable
phenomena.
The
optimization
of
nanocomposite compounding is intimately connected with the
need to quantify the resulting structure. Consequently, the paper
includes a brief discussion of the part played by
thermogravimetric and thermal analyses as well as the use of the
focused ion beam method to supplement scanning electron
microscopy as a viable alternative to (the more difficult)
transmission electron microscopy for the evaluation of dispersion
and percolation.
I.
INTRODUCTION
In contrast to micron fillers, nanofillers can increase the
breakdown strength of polymers and lead to orders of
magnitude improvement in voltage endurance [1,2]. These
materials can show dramatic changes in space charge behavior,
charge trapping and permittivity [3]. Nanoparticles can also
improve the mechanical and thermal properties of polymers
[4,5], and the discharge erosion properties [6].
The small size of nanoparticles relative to micron fillers
means that there are many more particles and much more
interfacial area per unit volume of filler, when the particles are
well dispersed. The particle-polymer interaction zone has a
finite thickness and, due to the large surface area in
nanocomposites, has been implicated in controlling the
dielectric response of nanocomposites.
As particle loading increases, the interaction zones can
begin to overlap, leading to effective percolation of the
interfacial areas at relatively low loadings [7]. As the interfacial
volume tends to have different properties than the bulk, such as
enhanced local conductivity, percolation of these areas can
have dramatic effects of the properties of the nanocomposites.
Though nanoparticle systems show improvements from
both an electrical and mechanical perspective, there are
sometimes conflicting reports regarding the effect of
nanoparticles in polymer composites. For example,
nanoparticles have been implicated in both increasing and
decreasing the breakdown strength in similar nanocomposites
[2,8,9]. While variations are to be expected in different
systems, the effect of processing on the final properties cannot
be overlooked. Two different processing methods can result in
different properties for the same system; this not only
complicates efforts to determine whether a particle system is
practically useful, but can also bias the conclusions drawn
when investigating the mechanisms leading to improved (or
degraded) properties. For example, large aggregates of
nanofillers should act similar to micron size particles, which
are known to degrade breakdown strength [9,10].
It is important that one carefully consider the processing
conditions used when making nanocomposites. In comparison
to microcompsosites, these systems present additional
challenges in processing. These include difficulty of dispersion,
high water uptake by nanoparticles due to large surface area
and potential changes in polymer microstructure. By way of
example and reference to the literature, the importance of
processing on the properties will be highlighted and relevant
methods of composite analysis regarding processing discussed.
II.
CHARACTERIZATION METHODS
A. Electron Microscopy
Scanning electron microscopy (SEM) of fracture surfaces is
a common method for analyzing dispersion, but this method is
not good for quantification and the classification of the
dispersion can be biased by fracture morphology and user
interpretation. Transmission electron microscopy (TEM) lends
itself well to dispersion quantification and provides good
resolution for very small particles. A drawback to TEM is the
difficulty in preparing specimens for analysis. Additionally,
one must be careful with interpretation of particle dispersion
when using TEM, as TEM samples have a finite thickness, but
the micrographs display the particles in two dimensions. As
illustrated in Figure 1, two materials with the same three-
dimensional dispersion will appear different when viewed only
on the surface, as in SEM, versus when a finite thickness is
viewed, such as in TEM.
To alleviate problems that would arise from variations in
sample thickness, avoid imaging particles on different planes,
ease sample preparation or image particles impossible to see
using an SEM fracture surface, a combination of focused ion
beam milling (FIB) and scanning electron microscopy has
proven useful. FIB milling is used to cut a groove in the surface
of the polymer, exposing nanoparticles. The surface can then
be imaged using scanning electron microscopy.
also useful for determining moisture content in nanoparticles
and in polymer nanocomposites.
Differential scanning calorimetry (DSC) can give more
detailed information on water present in the material, as water
may exist in different environments which can change the
freezing point, and potentially the dielectric response, of the
water. The addition of nanoparticles can also change the
crystallinity of the polymer, either through direct interaction
with the polymer or through necessary changes in processing
parameters. The change in crystallinity can in turn be
responsible for changes in the nanocomposite behavior [14,15].
III.
Figure 1. Simulated images of a random dispersion of 5 wt% 12 nm
spherical silica nanoparticles in XLPE. Left: Simulation of SEM image. Right:
Simulation of 20 nm thick TEM image. Images are 400 x 400 nm.
B. Quantitative Dispersion Evaluation
In order to avoid subjective judgment of the mixing degree
of nanofillers in polymeric matrices, quantitative techniques
can be used. If there is sufficient contrast between the matrix
and the nanoparticle, the dispersion analysis can be automated.
The degree of mixing of particles in a polymer matrix can
be decomposed into two independent aspects: the dispersion
(how well individual particles are separated from one another)
and distribution (related to uniformity of spacing of particles
and agglomerates). Two quantification methods include the
quadrat method and nearest neighbor distance [11,12,13].The
quadrat method breaks images into cells of the same size and
counts the number of particles in each cell. Higher values of
skewness indicate a lower quality of mixing. The first nearest
neighbor distance method measures the average distance from
each particle to its nearest neighbor and scales this by the
average distance expected for a random distribution of the
same particle density. Values lower than 1 indicates clustering.
When using automated methods, skewness and first nearest
neighbor distances use cluster centers and not individual
particles. The skewness can give low values if well dispersed
agglomerates of similar size are present, and thus skewness and
first nearest neighbor distance can give seemingly conflicting
information. This can be avoided by quantifying the equivalent
radius of particles/clusters and fitting individual particles of
specified sizes to the clusters for nearest neighbor calculations.
C. Thermal Analysis
Thermal analysis can play a number of roles in analyzing
nanocomposites. In cases where mixing of nanoparticles may
include loss of particles or exact particle loading is not known
beforehand, thermogravimetric analysis (TGA) provides a
method for nanocomposite loading verification. This method is
DISPERSION AND PROCESSING
Owing to their small size and high surface area-to-volume
ratio, nanoparticles can be particularly difficult to disperse.
Mixing methods utilizing high shear forces have been found to
be particularly effective at dispersing nanoparticles. However,
shear mixing, particularly with high viscosity materials or
when using ceramic balls to aid in dispersion, can lead to large
mechanical forces and generate significant amounts of heat,
which can lead to degradation of the polymer or volatilization
of low molecular weight components. Molding at high
temperature for long times or vacuum processing can lead to
similar effects. Thus, careful control of processing is needed
for proper dispersion and maintenance of material properties.
A. Particle Dispersion
The effect of poor dispersion on the dielectric properties of
nanocomposites can be highlighted by examining a
polyamideimide (PAI)-alumina system. Alumina nanoparticles
with a nominal diameter of 50 nm were dispersed in PAI resin
using a dual asymmetric centrifuge. It was found for this
system that the mixing method leaves agglomerates. With the
addition of alumina balls to the container during mixing, the
problem of agglomeration was alleviated. Quantitative analysis
using the quadrat method and 1st nearest neighbor distances
shows improved distribution and reduced agglomeration when
using alumina balls for mixing (Table I). Examples of sections
of these materials, viewed using SEM, are shown in Figure 2.
TABLE I.
QUANTIFCATION OF ALUMINA NANOPARTICLE DISPERSION IN
PAI FOR COMPOSITES MIXED WITHOUT AND WITH ALUMINA BALLS.
Skewness
1st Nearest Neighbor Index
No Alumina Balls
1.7
0.50
Alumina Balls
0.69
0.73
Figure 2. SEM images of well dispersed and poorly dispersed 5 wt %
alumina-PAI nanocomposites. Scale bar is 1 m.
The dispersion state of the system was found to be very
important in terms of breakdown strength (Figure 3a). In the
system with agglomeration, the breakdown strength was
reduced from 270 kV/mm in the unfilled material to 220
kV/mm with the addition of 5 wt % nanoparticles. However,
when the dispersion was improved, the breakdown strength
increased to 400 kV/mm.
For the same mixing procedure, agglomeration may
become more prevalent with increased loading. The PAIalumina system, mixed using alumina balls, shows an
improvement in AC breakdown strength above the base resin at
loadings of 2.5 and 7.5 wt % alumina but shows a drop at 10 wt
%. Analysis of the dispersion at this loading found
agglomerates in the system, which were the reason attributed to
the drop in breakdown strength. The effect of agglomeration
also manifests itself as a slight drop in the real permittivity as a
function of loading, as shown in Figure 3b. The agglomerates
reduce the effective interfacial area of the nanoparticles,
limiting the gains in permittivity.
B. FIB/SEM Imaging
The addition of fumed silica to PAI has also been
investigated. Individual particles for this system were 12 nm in
diameter, and could not be successfully imaged using direct
SEM imaging. TEM imaging of these materials, which are cast
as films, required epoxy embedding and microtoming. The use
of focused ion beam milling to cut a groove in the fracture
surface of the material allowed imaging using SEM. This
exposed particles on the surface and provided a flat section for
imaging. A comparison of TEM and FIB/SEM images are
shown in Figure 4. This FIB/SEM method can be a more
straightforward approach to dispersion analysis than TEM and
is also useful for quantification, as it provides a flat surface and
does not introduce bias seen in fracture surfaces.
80
350
70
(a)
(b)
60
Percent Change
DC Breakdown Strength
400
300
250
200
150
100
50
40
20
A crosslinked polyethylene (XLPE)-silica nanocomposite
system shows the effects of nanoparticles on processing. For
this system, crosslinking was achieved using dicumyl peroxide
(DCP) which has a boiling point of 130 oC. For a uniform
mixing of DCP in the materials, DCP was added at the end of
the mixing procedure (to avoid premature cross-linking during
compounding) and then stirred together with the mixture of
particles and PE for 4 min.
Mixing required temperatures below 130 oC to prevent loss
of DCP through volatilization and decomposition. Processing
at a temperature of 125 oC was found to produce the desired gel
content in the base polymer, but led to mechanical degradation
in 5 wt% and 12.5 wt% nanocomposites due to the increased
viscosity. An increase of the temperature to 128 oC and
sufficient preheat of the raw material was found to allow proper
crosslinking while minimizing material damage.
D. Water and Surface Treatment
10
50
-10
0
-20
No balls Alumina
balls
C. Material Damage and Defects
Successful processing of nanocomposites can be a complex
compromise
between
competing
requirements.
For
nanocomposite materials, as the filler content increases, the
mechanical properties of the polymer and its melt will change.
Nanofillers will reduce the mobility of polymer chains thus
increasing the modulus of the nanocomposites. The fillers will
also increase the relative magnitude of the viscous response of
the polymer melt. This is especially true for high aspect ratio
fillers, and processing temperatures that are effective for the
base resin may not work for nanocomposites.
30
0
0.0%
Figure 4. Comparison of TEM image (left) and FIB/SEM image (right) of 5
wt % fumed silica in PAI.
2.5%
7.5%
10.0%
Alumina Loading (wt %)
AC Breakdown Strength
Real Permittivity (10^1 Hz)
Figure 3. (a) Effect of alumina balls during mixing on DC breakdown
strength of 5 wt % PAI-alumina nanocomposites and (b) change in AC
breakdown strength and real permittivity with increasing loading.
The presence of water on silica nanoparticles has been
found to make dispersion of nanoparticles more difficult,
leading to agglomeration. In the XLPE-silica system, silica
nanoparticles which were not dried could not be well dispersed,
while drying was found to reduce agglomeration [16]. Water
uptake on the surface of silica nanoparticles can also be
reduced by attaching a hydrophobic functional group such as
vinylsilane, which replaces silanol groups on the surface of the
nanoparticles and can also block water from getting to the
surface of the nanoparticles [17]. In addition to dispersion
effects, the presence of water in the nanocomposites is
important in determining the electrical behavior of the
nanocomposites. Silica nanocomposites can take up a
significant amount of water, leading to changes in the dielectric
properties of the nanocomposites [18].
In order to improve the compatibility of the particles with
the polymer matrix, functionalization has been applied to silica
nanoparticles. These surface treatments (Figure 5) consisted of
triethoxyvinylsilane
(TES),
n-(2-aminoethyl)
3aminopropyltrimethoxysilane
(AEAPS)
and
hexamethyldisilazane (HMDS). AEAPS and HMDS are polar
molecules and should not strongly bond with XLPE. TES is
non-polar and provides an opportunity for covalent bonding to
create a strong interface region. Untreated fillers were found to
improve the time to breakdown by two orders of magnitude,
and the surface treatment, in all cases, further increased the
time to breakdown.
REFERENCES
[1]
[2]
[3]
[4]
[5]
Figure 5. Fig.b Schematic depiction of the surface modifiers
(a)aminopropyltrimethoxysilane (AEAPS), (b) hexamethyldisilazane (HMDS)
and (c) triethoxyvinylsilane (TES) [10]
In contrast to the alumina-PAI system, no change in the
dispersion state can be detected with the addition of the above
surface treatments to the nanosilica. In this case, the dispersion
state is not the likely cause for the change in properties,
indicating that the interfacial effects are dominating. Along
with an improvement in voltage endurance, surface treated
silica has been shown to lower charge mobility and inhibit
charge injection into the composite as compared to the
untreated silica nanocomposites [19]. The addition of APTES
treated nanosilica has also been found to introduce trap sites at
the nanoparticle-polymer interface [20]. Furthermore, DSC has
been used to show that surface treatment can increase the
crystallinity in XLPE.
IV.
CONCLUSIONS
The addition of nanoparticles can change the dielectric
behavior of polymers. However, the response of the
nanocomposites can vary based on the processing parameters.
These include parameters such as dispersion method,
processing temperatures, particle drying and surface chemistry
modification. If processing is not well controlled, the same
system may give a widely varying response. Analysis of the
nanocomposite dispersion, water content, crystallinity and
other properties is important in optimizing the response of a
nanocomposite system. With further understanding of the
relationship between the interfacial chemistry and the dielectric
response, it should be possible to tailor the interfacial
properties not only to ensure good dispersion, but also to
selectively improve the dielectric response of the material.
ACKNOWLEDGMENTS
The authors would like to thank the Air Force Research
Laboratory and the Electric Power Research Institute for their
financial support and the RPI Nanotechnology Center for
facilities support.
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18]
[19]
[20]
Y. Hu, R. C. Smith, J. K. Nelson and L.S. Schadler, “Some
mechanistic understanding of the impulse strength of
nanocomposites,” 2006 Annual Report Conference on Electrical
Insulation and Dielectric Phenomena, pp. 31-34, October 2006.
R.C. Smith, C. Liang, M. Landry, J.K Nelson, and L.S. Schadler,
"The mechanisms leading to the useful electrical properties of
polymer nanodielectrics," IEEE T. Dielect. El. In., vol.15, pp.187196, February 2008.
J.K. Nelson and J.C. Fothergill, “Internal charge behaviour of
nanocomposites,” Nanotechnology, vol. 15, pp. 586-595, March
2004.
P. C. Irwin, Y. Cao, A. Bansal and L. S. Schadler, “Thermal and
mechanical properties of polyimide nanocomposites,” 2003 Annual
Report Conference on Electrical Insulation and Dielectric
Phenomena, pp. 120—123, October 2003.
Z. Han, C. Diao, Y. Li and H. Zhao, “Thermal properties of
LDPE/silica nanocomposites,” 2006 Annual Report Conference on
Electrical Insulation and Dielectric Phenomena, pp. 310-312, October
2006.
T. Tanaka, “Dielectric nanocomposites with insulating properties”
IEEE T. Dielect. El. In., vol. 12, pp.914-928, 2008.
J. Y. Li, L. Zhang, and S. Ducharme, “Electric energy density of
dielectric nanocomposites,” Appl. Phys. Lett., vol. 90, 132901, March
2007.
T. Imai, F. Sawa, T. Ozaki, T. Shimizu, S. Kuge, M. Kozako and T.
Tanaka, “Effects of epoxy/filler interface on properties of nano or
micro composites”, IEEJ Transactions on Fundamental and Materials,
vol. 126, pp. 84-91, 2006.
S. Singha and M. J. Thomas, “Dielectric properties of epoxy
nanocomposites,” IEEE T. Dielect. El. In., vol. 15, pp. 12—23,
February 2008.
M. Roy, J. K. Nelson, R. K. MacCrone and L. S. Schadler,
“Candidate mechanisms controlling the electrical characteristics of
silica/XLPE nanodielectrics,” J. Mater. Sci., vol. 42, pp. 3789–3799,
June 2007.
N. A. C. Cressie, Statistics for spatial data, John Wiley, 1991.
D. Kim, J. S.Lee, C. M. F. Barry and J. Mead, “Microscopic
measurement of the degree of mixing for nanoparticles in polymer
nanocomposites by TEM Images,” Microsc. Res. Techniq., vol. 70,
pp. 539-546, June 2007.
G. Ayala, I. Epifanio, A. Simo and V. Zapater, “Clustering of spatial
point patterns,” Comput. Stat. Data. An., vol. 50, pp 1016-1032,
February 2006.
A. S. Vaughan, S. G. Swingler and Y. Zhang, “Polyethylene
Nanodielectrics: The Influence of Nanoclays on Structure Formation
and Dielectric Breakdown,” IEEJ Transactions on Fundamental and
Materials, vol. 126, pp. 1057-1063, 2006
R.C. Smith, Mechanistic electrical behavior of crosslinked
polyethylene, PhD Thesis, Rensselaer Polytechnic Institute, 2009.
M. Roy, An Examination of the Potential for Nanocomposites in the
Formulation of HV Cable Insulation, PhD Thesis, Rensselaer
Polytechnic Institute ,2009.
J. C. Salamone, Polymeric Materials Encyclopedia, CRC Press, Boca
Raton, 2006, pp. 2378-2379.
C. Zou, J.C. Fothergill, and S.W. Rowe, “The effect of water
absorption on the dielectric properties of epoxy nanocomposites,”
IEEE T. Dielect. El. In., vol. 15, pp. 106-117, February 2008.
R. K. MaCrone, J. K. Nelson, R. C. Smith and L. S. Schadler. “The
use of electron paramagnetic resonance in the probing of the nanodielectric interface,” IEEE T. Dielect. El. In., vol. 15, pp. 197-204,
February 2008.
R. C. Smith, L. Hui, J. K. Nelson and L. S. Schadler. Interfacial
charge behavior in nanodielectrics,” 2009 Annual Report Conference
on Electrical Insulation and Dielectric Phenomena, pp. 650—653,
October 2009.