Documentn8

Effect of silica nanoparticles on morphology of segmented polyurethanes

Zoran S. Petrovica,*, Young Jin Choa, Ivan Javnia, Sergei Magonovb, Natalia Yerinab,Dale W. Schaeferc, Jan Ilavskyd, Alan Waddone

aKansas Polymer Research Center, Pittsburg State University, 1501 S. Joplin, Pittsburg, KS 66762, USAbDigital Instruments/Veeco Metrology Group, Santa Barbara, CA, USA

cDepartment of Chemical and Materials Engineering, University of Cincinnati, Cincinnati, OH 45221-0012, USAdPurdue University, West Lafayette, IN 47907, USA

eDepartment of Polymer Science and Engineering, University of Massachusetts, Amherst, MA 01003, USA

Received 17 October 2003; received in revised form 25 March 2004; accepted 5 April 2004

Abstract

Two series of segmented polyurethanes having soft segment concentration of 50 and 70 wt%, and different concentrations of nanometer-

diameter silica were prepared and tested. Atomic force microscopy revealed a strong effect of nanoparticles on the large-scale spherulitic

morphology of the hard domains. Addition of silica suppresses fibril formation in spherulites. Filler particles were evenly distributed in the

hard and soft phase. Nano-silica affected the melting point of the hard phase only at loadings .30 wt% silica. A single melting peak wasobserved at higher filler loadings. There is no clear effect of the filler on the glass transition of soft segments. Wide-angle X-ray diffraction

showed decreasing crystallinity of the hard domains with increasing filler concentration in samples with 70 wt% soft segment. Ultra small-

angle X-ray scattering confirms the existence of nanometer phase-separated domains in the unfilled sample. These domains are disrupted in

the presence of nano-silica. The picture that emerges is that nano-silica suppresses short-scale phase separation of the hard and soft segments.

Undoubtedly, the formation of fibrils on larger scales is related to short-scale segment segregation, so when the latter is suppressed by the

presence of silica, fibril growth is also impeded.

q 2004 Published by Elsevier Ltd.

Keywords: Segmented polyurethanes; Nanocomposites; Morphology

1. Introduction

In spite of the breadth of research in the field of

nanocomposites, only limited number of studies deal with

colloidal fillers for polyurethanes. In this work, we study the

effect of nearly monodisperse, unaggregated 12 nm-

diameter spherical silica particles on the structure and

properties of phase-separated segmented polyurethane (PU)

elastomers. The motivation for this work is positive

experience with silica reinforcement of analogous single-

phase PUs [1]. In this case, the addition of nano-silica

improved the strength by about three times and elongation at

break by about 600%.

Segmented polyurethane elastomers used in the present

study are block copolymers with alternating soft and hard

blocks that, due to structural differences, separate into two

phases or domains. Hard domains play the role of physical

cross-links and act as a high modulus filler, whereas the soft

phase provides extensibility [24]. The morphology of

segmented PUs depends on the relative amount of the soft

and hard phases. PUs with a 70 wt% soft segment

concentration (SSC) typically have globular hard domains

dispersed in the matrix of soft segments, while co-

continuous phases and even lamellar morphology have

been postulated in the samples with 50 wt%-SSC. Poly-

urethanes with 70 wt%-SSC are soft thermoplastic rubbers

whereas the ones with 50 wt%-SSC are hard rubbers, both

being of significant industrial importance [5]. These systems

are usually unfilled except for minor additives to improve

aging properties.

It is reasonable to expect that the effect of nanoscale

fillers in segmented PUs would be quite subtle due to the

intrinsic complexity of these systems. Since the hard

domains in our case are semi-crystalline they may form

large crystalline forms such as spherulites. It is of interest,

0032-3861/$ - see front matter q 2004 Published by Elsevier Ltd.

doi:10.1016/j.polymer.2004.04.009

Polymer xx (0000) xxxxxx

www.elsevier.com/locate/polymer

* Corresponding author. Tel.: 1-620-235-4928; fax: 1-620-235-4919.E-mail address: [email protected] (Z.S. Petrovic).

ARTICLE IN PRESS

therefore, to establish the effect of nano-silica on the two-

phase morphology. The filler may interact with the hard or

soft segments or both. Since silica has OH groups on the

surface, isocyanate may react with the particles thereby

aiding dispersion of the particles in the polymer. Thus, the

effect of the filler will be exerted through the adsorption of

the soft and hard segments on the silica surface as well as

through chemical bonding, potentially affecting the struc-

ture of both phases. With the advent of atomic force

microscopy (AFM) the morphological changes in the

polyurethane elastomers can be followed quite elegantly.

AFM, complemented with X-ray analysis, is used to observe

the changes in morphology over a wide range of length

scales.

2. Experimental

2.1. Materials

Polyurethanes were prepared from diphenylmethane

diisocyanate (MDI), polypropylene oxide (PPO) glycol,

and butane diol (BD). MDI was Isonate 125 M from Dow

Chemical; it was distilled under vacuum at 170 8C. PPO diolused in this work was Acclaim 2020 from Lyondell; It had

an OH number of 55 mg KOH/g, corresponding to the

molecular weight of 2040. BD was purchased from Aldrich;

it was distilled before use.

Colloidal silica, having a particle diameter of about

12 nm, was obtained from Nissan Chemical Co. as a 30 wt%

dispersion in methyl ethyl ketone (MEK).

2.2. Methods

Polyurethane/filler composites were prepared by mixing

the polyol with the filler solution, removing MEK by

distillation, and mixing with diisocyanate to obtain the

prepolymer, which was chain extended with BD. The

mixture was then poured into the mold to obtain 1 mm thick

sheets or thin films. Filler concentrations were 0; 5; 10; 20,

and 30 wt% where possible. Higher concentrations were

difficult to obtain because of the high viscosity of the polyol

with nanoparticles. Thermal measurements were carried out

using TA Instruments thermal analysis system consisting of

a 3100 Controller, managing DSC 2910, TMA 2940 and

DEA 2970 modules. The heating rate was 5 8C/min for allmethods. WAXD was performed with a Siemens D500

diffractometer in transmission mode, using Ni filtered

Cu Ka radiation from a sealed tube generator. Ultrasmall-angle X-ray scattering (USAXS) experiments were

performed using the Bonse-Hart double crystal X-ray

camera at the UNICAT beam line at Argonne National

Laboratory.

AFM was performed with a scanning probe microscope

(MultiModee Nanoscope IIIa, Digital Instruments/VeecoMetrology Group, Santa Barbara, CA). Measurements were

performed in tapping mode with free oscillating amplitude,

A0 in the 4060 nm range and set-point amplitude 0.40.05 nm. Such conditions of enhanced tip-sample force

interactions are most suitable for compositional imaging of

heterogeneous polymer samples as micro-segregated poly-

urethanes are. Etched Si probes (spring constant 50 N/m)were applied for imaging. Imaging was conducted on flat

surfaces prepared at2100 8C with an ultramicrotome MS-01(MicroStar Inc.) equipped with a diamond knife. Height and

phase images were simultaneously recorded on polymer

surfaces. Height images reflect surface morphology, whereas

phase images provide a sharp contrast of fine structural

features and emphasize differences in mechanical properties

of different sample components.

3. Results and discussion

In addition to nanometer-scale phase separation, seg-

mented polyurethanes may also display coarser morpho-

logical features such as spherulites or spherulite-like forms.

We have compared the morphology of four samples using

AFM: the polyurethanes having 70 wt%-SSC without nano-

particles and 70 wt%-SSC with 20 wt% nano-silica, as well

as the samples with 50 wt%-SSC without and with 20 wt%

nano-silica. X-ray diffraction was carried out on samples

with 0, 5, 10 and 20 wt% nano-silica in both series of PUs

(with 50 and 70 wt%-SSC). USAXS was completed on the

unfilled and filled samples with 50 wt% soft segment.

Simple calculations show that for filler particles arranged

on a cubic lattice, the inter-particle distance (surface to

surface) is about one diameter at 10 vol%, i.e. about 12 nm

in our case with 20 wt% (11.5 vol%) of nano-silica. Under

such circumstances, the separation of filler particles is on the

order of molecular dimensions and may also affect the

morphology and matrix behavior. The above calculation

illustrates the opportunities for modification of properties of

polymeric matrices with nano fillers.

Segmented polyurethanes are notoriously complicated

systems due to structural heterogeneity arising from the

distribution of the hard segment lengths and even the

possible existence of hard-segment homopolymers formed

at the given synthesis conditions. Also, isocyanates are

somewhat soluble in the soft segment and thus potentially

unavailable for the formation of the hard phase. The actual

soft-segment concentration, therefore is somewhat higher

than that calculated from stoichiometry. Finally, these

systems are rarely in equilibrium; their morphology is

dependent not only on the synthesis chemistry but also on

their thermal history.

Very large hard-segment rich structures have been

observed by Raman spectroscopy [6]. Also, a number of

morphological studies on similar polyurethane systems

have been carried out using electron microscopy but due to

the lack of contrast between phases the conclusions were

often ambiguous. AFM, however, offers unprecedented

Z.S. Petrovic et al. / Polymer xx (0000) xxxxxx2

ARTICLE IN PRESS

opportunities for revealing fine structure of the urethane

morphology without the need for special treatment of the

samples.

AFM images of the PU sample with 50 wt%-SSC (Fig. 1)

show spherulitic morphology. Height (Fig. 1(a)) and phase

(Fig. 1(b)(d)) images of 50 mm 50 mm surface reveal anumber of large spherulites with diameters up to 20 mm.The spherulites are surrounded by amorphous material,

which is the darker phase in both images. Bearing analysis

shows that an area occupied by bright-contrast features is

52%, consistent with the ratio of the components withsoft and hard segments. The fine structure of the spherulites

is best resolved in phase images (Fig. 1(b)(d)). It appears

that the spherulites are formed of fibrils that are more

densely packed in the center of spherulites. Phase image in

Fig. 1(d) shows individual fibrils at spherulite edges where

they are immersed in an amorphous background. The

diameter of the fibrils is 50120 nm range and their length

is a few microns.

At the moment, we can only speculate about the

structural organization observed in the AFM images.

Since the extended length of the hard and soft segments is

only about 10 nm (both segments have molecular weight

2 K), soft and hard segments must coexist in the fibrils as

well as in the amorphous regions. This picture is somewhat

different from the established view that co-continuous

sheet-like or lamellar phases exist at this concentration of

soft segments.

Morphology of PU with 50 wt%-SSC filled with 20 wt%

nano-silica is characterized by more globular domains with

amorphous materials between them (Fig. 2). The large-scale

phase image in Fig. 2(b) shows 110 mm domains withwell-defined boundaries. Some of the domains are slightly

elongated. Domains of the filled polymer are smaller than

those of the un-filled material but they are characterized by a

narrower size distribution. In the silica-loaded material,

there is no well-defined spherulitic structure. Only some

traces of tightly packed nano-fibrils with a width of 10

40 nm can be found. Nano-fibrils are supposed to consist of

almost pure hard segments. Due to interconnectivity of the

hard and soft segments and the size of the hard segment,

however, they may contain some soft segments. Indeed,

USAXS studies confirm this picture.

Silica nano-particles and their agglomerates in the filled

material are best resolved in high-resolution phase images

(Fig. 2(c) and (d)). The nano-particles are seen as bright

spots, especially, when compared to the surrounding

amorphous polymer. The particles are evenly distributed

Fig. 1. AFM images of the PU sample with 50 wt%-SSC. Image (a) is a height image. Images (b)(d) are phase images.

Z.S. Petrovic et al. / Polymer xx (0000) xxxxxx 3

ARTICLE IN PRESS

throughout the sample. The average particle size, which was

estimated with the particle analysis software of the

microscope manufacturer, is about 10 nm. This value is

close to a particle size of 12 nm, which was determined

from electron microscopy micrographs [7].

The morphology of the PU sample with 70 wt%-SSC

is revealed in the height (Fig. 3(a)) and phase (Fig.

3(b)(d)) images. In both cases, spherulites are seen as

bright round-shape regions with dimensions varying from

0.8 to 7 mm. The phase image is the most informative

regarding the morphology of this material. Spherulites,

being more dense structures, appear bright. Bearing

analysis of the phase image showed that dense areas

occupy 28%, which is close to the content of hard

segments, indicating that amorphous regions must contain

both hard and soft segments. Darker regions are the

amorphous phase that surrounds spherulites. These areas

contain regions with different contrast (marked by

arrows) that indicate inhomogeneity of the amorphous

material. The nature of this inhomogeneity is not known.

Spherulites of PU with 70 wt%-SSC (Fig. 3) are more

compact than those of the polymer with 50 wt%-SSC

(Fig. 1). Differences are also found in the structure and

size of fibrils forming spherulites. In PU with 70 wt%-

SSC, there is a tendency toward radial growth of fibrils

from a nucleating center. These fibrils are smaller

(20 nm) and are densely packed as compared with the

50 wt%-SSC fibrils. The spherulite borders are well

defined with few, if any, nano-fibrils entering amorphous

phase. This picture is quite different from morphology of

50 wt%-SSC material.

The height and phase images of the PU 70 wt%-SSC

sample filled with silica nanoparticles (20 wt%) are

shown in Fig. 4. The morphology of this sample is

different from that of the non-filled material. The domain

structure is bimodal with large domains (1.52.5 mm)

coexisting with small structures 300400 nm in size.

This distribution is best seen in the phase images (Fig.

4(b) and (c)). Bearing analysis of both images shows that

bright domains cover 30 wt% of the area. Therefore, as

in previous samples, the ratio of spherulitic and

amorphous materials is consistent with the SSC.

Individual silica particles are distinguished as bright

spots in the phase images (Fig. 4(d) and (e)). Silica

particles are distributed rather homogenously. The

particle analysis gives an average size of silica particles

13 nm.In summary, AFM images demonstrate that the mor-

phology of PU samples depends on SSC and presence of

silica particles. Differences include size and size distri-

bution of spherulites, as well as the type and dimensions of

nanoscale fibrillar structures forming the spherulites.

Fig. 2. AFM images of the PU sample with 50 wt%-SSC and 20 wt% nano-silica. Image (a) is a height image. Images (b)(d) are phase images.


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3.1. Thermal behavior of the hard and soft segments in the

presence of nano-silica

Melting of segmented polyurethanes with MDI/BD hard

segments was studied by differential scanning calorimetry

(DSC). DSC does not reveal details of the sample

morphology but it indicates the degree of organizational

order of crystalline domains through the melting behavior of

the crystalline phase, and the degree of interaction between

particles and the soft or hard phase.

Usually two and sometimes three peaks were observed in

the DSC endotherms. This pattern was attributed to a

distribution of crystallite sizes, smaller crystallites having

lower melting points. Alternatively, some of the multiple

melting peaks could be attributed to the release of the

residual strain or packing disorder in the hard segments [8]

or to the presence of different crystal forms [9,10].

DSC curves of the 50 wt%-SSC polymers with different

silica content (Fig. 5) show two melting peaks at 201 and

221 8C and a shoulder at about 230 8C for samples with 0, 5and 10 wt% silica, while the samples with 20 and 30 wt%

filler display a single melting peak at 220 and 230 8C,respectively. The smaller peaks in the 10 wt% nanosilica

sample were the result of the smaller sample size. The

increase in size of the high temperature melting peak and

disappearance of the low temperature peaks may be

attributed to different morphologies of highly filled samples

as observed by AFM and SAXS (below). This result is

opposite from what we observed previously in nano-silica

filled polyethylene oxide [11], where both the degree of

crystallinity and the melting point decreased with increasing

nano-silica concentration. These PUs are more compatible

with the filler not only because of higher polarity of the

polymer but also as a result of possible chemical reaction of

isocyanates with hydroxyl groups on the surface of silica.

Lipatovs theory of filler reinforcement of polymers

predicts formation of a boundary layer of a matrix material

on the surface of the filler [12,13]. The thickness of the layer

depends on the strength of interaction, being greater for

stronger interaction. The properties of a polymer in the

boundary layer differ from those in the bulk of the matrix

material primarily due to the decreased mobility of chains

adsorbed on the filler surface, resulting in a higher glass

transition and perhaps lower crystallinity. Hard segments

may also be chemically bound to the surface of the nano-

silica leading to reduced mobility.

No obvious trends were observed in the glass transition

temperature Tg of the soft segment as measured by DSC(Fig. 6), thermo-mechanical, dynamic mechanical (Fig. 7)

and dielectric analysis. Tg of the PPO soft segment chains in

the series with 50 wt%-SSC varied slightly with filler

concentration (the value at 0 wt% filler may have been too

Fig. 3. AFM images of the PU sample with 70 wt%-SSC. Image (a) is a height image. Images (b)(d) are phase images.


ARTICLE IN PRESS

low due to experimental difficulties). Generally, it is

difficult to pinpoint the transition in these samples because

of the lower concentration of soft segments and the effect of

hard segments on their mobility. The glass transition with

70 wt%-SSC may even decrease with increasing silica

content, but the variations were within few degrees as

shown in Fig. 6. Thus, no increase of the soft segment Tgwas observed unlike with the single-phase PUs with PPO

chains. It appears that the hard/soft phase interaction is

stronger than the silica/soft interaction. Also, nanoparticles

may have introduced some extra free volume in the matrix,

which was reflected in lower density of the composites than

expected from individual densities of the matrix and filler.

Fig. 4. AFM images of the PU sample with 70 wt%-SSC and 20 wt% nano-silica. Image (a) is a height image. Images (b)(d) are phase images.

Fig. 5. DSC curves of the samples with 50 wt%-SSC showing the melting

region. Note that the reduced size of the endotherms for the 10 wt% sample

is due to small sample size.

Fig. 6. Effect of nano-silica concentration on soft segment Tg as measured

by DSC in series with 50 and 70 wt%-SSC.


ARTICLE IN PRESS

3.2. X-ray diffraction

WAXD shows significant change with loading for both

the 50 and 70 wt%-SCC materials (Figs. 8 and 9). There is a

crystalline peak at 19.4 degrees (4.6 A) in the un-filled

sample. This peak persists throughout the 50 wt%-SCC

series (5, 10, 20 wt% silica). By contrast, in the 70 wt%

series, there is a clear effect of the nano-spheres on the

crystalline component (Fig. 9). At zero loading, the

crystalline peak at 19.4 degrees is clear. This feature

progressively weakens and broadens with loading until by

20 wt% the trace appears to be wholly amorphous. This

result is consistent with the AFM images that indicate a

decrease in the hard domain size at 20 wt% loading in the

70 wt%-SSC-the size of the hard domains becomes too

small to give discrete WAXD peaks. Irrespective of the

details of interpretation, however, it is clear that the nano-

spheres are affecting the crystallization of the hard segment

when above 20 wt% loading levels in the 70 wt%-SSC,while no such interference was observed for the 50 wt%-

SSC.

3.3. Ultra small angle X-ray scattering

Ultra small angle X-ray scattering was used to assess the

effect of the filler particles on the morphology of the matrix

and to determine the degree of aggregation of the filler

particles. Three samples were studied, all with 50 wt%-SCC

and silica loadings of 0, 10 and 20 wt%. The data were

measured on samples of known thickness and density to

give the scattering cross section, dS; per unit samplevolume, V ; per unit solid angle, dV;

Iq ; dSVdV

1

The data are shown in Fig. 10, where Iq is plotted versus

Fig. 7. Effect of nano-silica concentration on soft segment Tg in series with

50 and 70 wt%-SSC as measured by DMA.

Fig. 8. Wide angle X-ray diffractograms of polyurethanes with with

50 wt%-SCC and different concentrations of nano-silica. Reheating the

sample without filler improves crystallinity.

Fig. 9. Wide angle X-ray diffractograms of polyurethanes with 70 wt%-

SCC and different concentrations of nano-silica.

Fig. 10. USAXS profile for filled and unfilled polyurethanes with 50 wt%-

SCC. Solid lines are unified fits the data.


ARTICLE IN PRESS

the scattering vector, q; which is related to the scattering

angle, u; as q 4p=lsinu=2: l is the incidentwavelength.

The profiles for the unfilled and filled samples are quite

different in the region q . 0:01 A21: For q , 0:001 A21;however, the profiles are similar, showing power-law

dependence with a power law exponent of about 24.0.The limiting slope of 24.0 is consistent with Porods lawfor scattering from an interface that is smooth on a length-

scale of 1=q: This scattering could to be due to asperities on

the sample surface, rather than the spherulitic features seen

by AFM, since the stringy structures would not be expected

to follow Porods law. This issue needs to be investigated

with an instrument capable of reaching smaller q-values. At

any rate, the scattering in small-q region is indicative of

morphological features in excess of 6 mm in radius.In the region around q 0:01 A21; scattering arises from

morphological features of the order of 100 A. Consider first

of all the unfilled sample where a broad maximum is

observed at qmax 0:035 A21 indicative of a Bragg spacingof 2p=0:035 A21 180 A: This feature is attributed tosegmental phase separation, but the data are not rich enough

to distinguish detailed morphology such as the difference

between lamellar and globular domains. At this point, we

cannot say whether the phase-separated domains exist

within one or both of the large-scale domains observed by

AFM. Very likely this short-scale domain structure

observed in USAXS exists within both of the large-scale

domains observed by AFM.

To further quantify the short-scale domain morphology

of the unfilled sample, the USAX data were fit to a simple

damped spherical-domain model [14]. If I1q;RG is thescattered intensity for uncorrelated domains of radius RG;

then the intensity for the correlated model is

Iq I1q;RG1 8wuq; j u

3sin 2qj2 2 cos 2qj2qj3 2

where 2j is the mean correlation distance between domainsand (w is the volume fraction of the minority phase.I1q;RG is assumed to follow a simple Guinier form [14].

I1q;RG G exp 2q2R2G3

!3

For q ! 1=RG; I1q;RG follows Guiniers law, so thecurvature at small q provides a measure of the size of the

domains. Guinier radius, RG; is the radius-of-gyration of

the domains, which for spherical domains of radius, R; is

RG 3=50:5R: The pre-factor, G; is a measure of thedegree of phase separation. Although a detailed model is

required to interpret this parameter, for spherical domains,

G can be estimated as

G wvSLD1 2 SLD22 4where w is the volume fraction of the minority phase, v is the

domain volume v 3=4pR3 and SLD1 and SLD2 are thescattering-length densities of the two phases.

The result of fitting the data for the unfilled samples in

the region of the maximum is shown in Table 1 and the

curve is plotted as a solid line in Fig. 10. The fitting

parameters are RG 31 A; G 16 cm21; j 153 A andf 0:14: Although, this analysis is approximate at best, itdoes show that the relevant length-scales are substantially

larger than the segment length and w is substantially lessthan the domain volume fraction calculated from the

composition w 0:43: In addition, G can be comparedto that expected for a fully phase separated system.

Plugging w 0:43; SLDhard 11.6 1011 cm22 andSLDsoft 9.3 1011 cm22 into Eq. (4) givesG 61 cm21, which is to be compared to the measuredvalue of 16 cm21. The diminished G shows that the

segments are not fully segregated. These observations all

imply substantial intermixing hard and soft segments in the

short-scale domains.

The addition of the silica filler particles leads to

substantial modification of the scattering profile as seen in

Fig. 10. The resulting profile shows no hint of the domain

structure seen in the unfilled samples even though the

scattered intensity is comparable to the unfilled case for

q . qmax: The absence of the correlation peak implies thatsegment domain structure is disrupted by the silica particles.

The scattering for q . 0:008 is consistent with scatteringfrom unaggregated silica particles of the order of 100 A in

diameter in a matrix of uniform SLD. To quantify the nature

of these particles, the data were fit to a simple Guinier-plus-

powerlaw profile [15] using code developed by Beaucage

[16] and implemented by UNICAT:

I1q;RG G exp 2q2R2G3

! B erfqRG

3

q

" #4FB; 5

where erf is the error function and FB is an uninteresting flat

background. The results of the fitting are captured in Table

1, where, in addition to the parameters discussed above, the

Porod constant, B; is included. The functional form of Eq.

(5) follows Guiniers law at small q and Porods law at large

q: The measured hard radii of R 87 and 101 A are foundto be substantially larger than that expected for nominal

120 A diameter particles. The difference is due to the fact

that the R 5=30:5 RG is weighted by the square of theparticle volume, so large-radius particles dominate the

average when the distribution of particle sizes is

polydisperse.

Insight into the particle size distribution comes from

Porod analysis. The Porod constant, B; is proportional to the

surface area per unit volume, Sv: That is,

B 2pSLD2 2 SLD12Sv 6The contrast in this case is between the matrix

(SLD1 1.01 1011 cm22) and the silica particles(SLD2 1.69 1011 cm22). The SLDs are calculated


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assuming a skeletal density of 2.0 g/cm3 for silica and

1.13 g/cm3 for the matrix whose chemical formula is

assumed to be C36.4O9.8H36.8N2. Table 2 shows the results

of the calculation of S and S0 where S is the surface area perunit sample mass and S0 is the surface area per unit mass ofsilica. The two differ by the silica volume fraction, f; whichis calculated from the densities as f r2 r1=r2 2 r1;where r is the sample density, r1 is the matrix density and r2is the silica density.

In a generic sense [17], the surface area can be related to

the mean chord, d2; of the filler (particle) phase as

d2 4fSv

7

where f is the volume fraction filler and Sv rS is thesurface area per unit sample volume. The mean chord of a

spherical particle of radius R is 4R=3 from pure geometry, so

R 3fSv

8

This value is also tabulated along with the matrix chord, d1;

which is also calculated from Sv and the volume fraction

filler:

d1412f

Sv9

This calculation gives an average hard radius for the two

samples of 47 A, somewhat less than that expected based on

the nominal size of the particles. Here, the discrepancy is

attributed to the fact that the surface area is related to the

first reciprocal moment of the size distribution, which is

dominated by the small particles. In addition, errors are

introduced through the assumed density of the silica

particles.

Since the data are on an absolute scale, it is possible to

use the Porod invariant, Qp; to calculate the contrast,

lSDL2 2 SLD1l:

Qp ;1

0dqq2Iq 10a

Qp 2p2SLD2 2 SLD12f12 f: 10bSo,

Sv pf12 fB=Qp: 11In this method, the densities of the phases need not be

known. Since the sample and matrix density are known, the

skeletal density, r2; of the silica particles can be calculated.The details of how r2; and surface area are extracted self-consistently from the measured QP and B are given by

Schaefer et al. [18,19]. To summarize, self-consistency is

impressed on Eqs. (6) and (11). First, QP is determined by

integrating the measured SAXS data [Eq. (10(a))] in the q-

region where the particles scatter. Assuming some value for

r2 (say 2 g/cm3), one then calculates w from r2; the

measured matrix density r1 and the measured sampledensity r: The matrix density is taken to be that of thecorresponding unfilled PU. One then calculates an interim

contrast, lSLD2 2 SLD1l, using Eq. (10(b)). A newapproximation to SLD2 (and therefore r2; since thecomposition of silica is known) is then obtained from this

interim contrast and the SLD1 calculated from the known

density and composition of the matrix. The cycle is repeated

until convergence is obtained on values of SLD2 and f:Typically about 550 iterations are needed to achieve

convergence. The surface area per unit volume, Sv; follows

from either Eq. (6) or (11) using the measured value of B:

The outcome of this exercise is tabulated in Table 3. The

resulting r2 1:6 g=cm3; substantially smaller than thatassumed for Table 2. The resulting particle radius, however,

is only 10 wt% larger than Table 2, (average 53 A), butstill less than the nominal radius.

The distribution of particle sizes can be extracted from

Table 1

Parameters from a unified fit to the filled and unfilled samples

Loading (wt%) SCC wt% r (g/cm3) r1 (g/cm3) G (cm21) R (A) B (cm21 A24) P j (A) f

0 50 1.13 16 40 153 0.14

10 50 1.19 1.13 291 101 6.10 1025 420 50 1.24 1.13 328 87 7.51 1025 4

f is the volume fraction of the minority phase, r is the sample density, r1 is the matrix density (unfilled PU), G is the Gunier pre-factor, B is the Porod

constant, R is the effective domain hard radius, and j is the correlation range.

Table 2

Porod analysis assuming a silica skeletal density of 2.0 g/cm3

Loading

(wt%)

r2(g/cm3)

S

(m2/g)

S0

(m2/g)

d2(A)

d1(A)

R

(A)

f

10 2.0 38 358 87 1001 42 0.126

20 2.0 69.5 284 102 505 52.7 0.065

f is the volume fraction silica. S is the surface area per gram sample, S0

is the surface area per gram silica. d1 and d2 are the matrix and particle

chords. r2 is the assumed silica skeletal density. R is the particle hard

radius.

Table 3

Porod analysis using the Porod invariant to calculate the skeletal density,

r2; of silica

Loading

(wt%)

S

(m2/g)

S0

(m2/g)

d2(A)

d1(A)

R

(A)

r2(g/cm3)

f

10 70.5 409 59.7 508 44.8 1.64 0.11

20 95.1 313 81.4 258 60.8 1.58 0.24


ARTICLE IN PRESS

the scattering data if a form is assumed for the distribution

functions. We used standard least-squares fitting procedures

and assumed a Gaussian distribution of the particle

volumes. The scattering cross section is modeled as

Iq SLD2 2 SLD12N1

0lFq; rl2v2r Prdr 12

where Fq; r is the form factor of a sphere of radius r; N isthe total number of particles, v is the particle volume, and

Pr is the probability of observing a particle of size r: Thefitting code is implemented as part of the Irena software

provided by UNICAT [20]. A Gaussian form of width s isassumed for the volume distribution function

vrPr 12ps2

1=2exp 2

2r 2 2r02s2

$ %13

The resulting distribution, using the skeletal densities from

Table 3, is shown in Fig. 11 for the 20 wt% silica sample.

Comparison of the two data sets indicates a number-average

mean radius of about 65 A for both, quite close to the

nominal size of the silica used. The distribution is 25%

broader, however, for the 20 wt% sample, which indicates a

small degree of aggregation at higher loading. (Table 4).

Overall, the USAXS data confirm the presence of phase-

separated domains in the unfilled samples. The presence of

even 10 wt% silica, however, disrupts the short-scale

segment domains. The silica is highly dispersed at both

loadings with a mean radius of 65 A. A Gaussian

distribution of particle sizes with a full-width-at-half-height

comparable to the mean fits the data. The broad distribution

of particle sizes accounts for the fact that the mean radius

calculated from Guinier analysis is considerably larger than

that calculated from Porod analysis.

4. Conclusion

It has been shown that addition of nanoparticles radically

alters the morphology of the hard phase both at 50 and

70 wt% SSC by suppressing the formation of fibrils within

spherulites and decreasing hard domain size. A single

melting peak in DSC suggests that either the distribution of

crystallite sizes is narrower or that a single type of

crystalline structure is formed at higher filler loadings.

There was no clear effect of the filler on the glass transition

of soft segments. Wide-angle X-ray diffraction showed

decreasing crystallinity of the hard domains with increasing

filler concentration in samples with 70 wt%-SSC.

USAXS provides a link between the presence of the

silica and the alteration of the large-scale fibrillar mor-

phology. Even a small amount of silica disrupts the short-

scale phase-separated morphology attributed to segment

phase separation in unfilled PU. Apparently, the large-scale

morphology results from the short-scale domain growth in

the same way that lamellar crystals result from short-scale

segregation of crystalline and amorphous regions in semi-

crystalline polymers. When the short-scale domain structure

is disrupted, fibrillar growth is impeded.

Acknowledgements

The UNICAT facility at the Advanced Photon Source

(APS) is supported by the US DOE under Award No.

DEFG02-91ER45439, through the Frederick Seitz

Materials Research Laboratory at the University of Illinois

at Urbana-Champaign, the Oak Ridge National Laboratory

(US DOE contract DE-AC05-00OR22725 with UT-Battelle

LLC), the National Institute of Standards and Technology

(US Department of Commerce) and UOP LLC. The APS is

supported by the US DOE, Basic Energy Sciences, Office of

Science under contract No. W-31-109-ENG-38.

Fig. 11. Particle volume distribution obtained by fitting the USAX data to a

Gaussian distribution of particle volumes. Parameters are collected in Table

4.

Table 4

Results of least squares analysis of the USAX profile assuming a Gaussian

distribution of particle volumes

Loading (wt%) r (g/cm3) s A r0 (A) S0 (m2/g) 3=Sv 0 (A) f

10 1.6 33.9 65.5 442 41 0.11

20 1.6 25.7 66.0 358 53 0.21

The quotient 3=Sv0 is the particle hard radius assuming spherical

particles. Sv0 is the surface to volume ratio of the silica particles. Sv 0 is

calculated from the particle size distribution in Fig. 11.


ARTICLE IN PRESS

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Effect of silica nanoparticles on morphology of segmented polyurethanesIntroductionExperimentalMaterialsMethods

Results and discussionThermal behavior of the hard and soft segments in the presence of nano-silicaX-ray diffractionUltra small angle X-ray scattering

ConclusionAcknowledgementsReferences

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