Surface Science 596 (2005) 187–196
www.elsevier.com/locate/susc
Using spectroscopic ellipsometry for quick prediction
of number density of nanoparticles bound to
non-transparent solid surfaces
Rajendra R. Bhat, Jan Genzer
*
Department of Chemical & Biomolecular Engineering, North Carolina State University, 911 Partners Way,
Raleigh, NC 27695-7905, USA
Received 5 May 2005; accepted for publication 14 September 2005
Available online 5 October 2005
Abstract
We report on the use of spectroscopic ellipsometry (SE) in predicting number density of nanoparticles bound to the
surfaces decorated with either organic monolayers or surface-grafted polymers. Two systems are considered that comprise citrate-stabilized gold nanoparticles adsorbed on: (1) 3-aminopropyltriethoxysilane (APTES) self-assembled
monolayer (SAM), and (2) surface-tethered polyacrylamide (PAAm). Number density of gold nanoparticles on the surface is varied systematically by gradually increasing either the concentration of APTES molecules in the SAM or molecular weight of grafted PAAm. The adsorption of gold nanoparticles on APTES gradient surfaces is monitored via
atomic force microscopy (AFM), near-edge X-ray absorption fine structure (NEXAFS) spectroscopy, and SE. The partition of gold nanoparticles on PAAm gradient assemblies is characterized by AFM, ultraviolet–visible (UV–vis) spectroscopy, and SE. By correlating the results obtained from the various techniques on nanoparticle coatings, we derive
an empirical linear relationship between the number density of nanoparticles on surfaces and cos (D) parameter measured in SE. Excellent agreement between nanoparticle number density determined experimentally from AFM scans
and that predicted by SE proves the potential of SE as a quick, predictive technique to estimate number density of
nanoparticles bound to solid, non-transparent substrates.
2005 Elsevier B.V. All rights reserved.
Keywords: Ellipsometry; Self-assembly; Nanoparticles; Polymer brush; Gradient; Atomic force microscopy; NEXAFS; APTES
1. Introduction
*
Corresponding author. Tel.: +1 919 515 2069; fax: +1 919
515 3465.
E-mail address: [email protected] (J. Genzer).
URL: http://scf.che.ncsu.edu (J. Genzer).
In the past two decades nanoscience has
emerged as a major research area due to the promises shown by nanostructures—both in terms of
0039-6028/$ - see front matter 2005 Elsevier B.V. All rights reserved.
doi:10.1016/j.susc.2005.09.014
188
R.R. Bhat, J. Genzer / Surface Science 596 (2005) 187–196
understanding physics at the molecular level and
developing novel applications by utilizing the unusual material properties observed at this length
scale [1–3]. Nanoparticles, which form one of the
major thrust areas in the field of nanoscience,
can be conveniently synthesized in the size range
of 1–100 nm, thus bridging the gap between molecular and mesoscopic systems that can be assembled by bottom–up and top–down approaches,
respectively. A large variety of nanoparticles made
up of metals [4], semiconductors [5], or polymers
[6] have been synthesized and were shown to possess extraordinary optical [7] and electronic [8]
characteristics. The properties of these nanosized
objects can be modulated by varying the particle
size and shape, and the particle organization in
the material. One of the first milestones on the
pathway towards eventual utilization of the exciting properties of nanoparticles in functional devices is the assembly of particles in two (2D) and
three (3D) dimensional arrays on solid substrates
[1,9,10]. Such an assembly provides a conduit
whereby unique properties of nanostructures can
be linked to the macroscopic world. Towards this
end, a number of approaches based on covalent
[11] or electrostatic [1] interaction between particles and a monomeric [1,11,12] or polymeric
[13–15] film anchored to a substrate have been
developed [1,3]. In order to reproducibly fabricate
the nanostructures and understand the origin of
their novel properties, it is necessary to fully characterize them. A few analytical and imaging techniques are currently employed to examine the
organization of particles on surfaces. Chief among
them are scanning [12,16] and transmission electron microscopy [17] (SEM/TEM), scanning probe
microscopy (SPM) [18,19], ultraviolet visible light
(UV–vis) light absorbance spectroscopy [11,13,
17,20], and reflectometry [21]. Of these only UV–
vis is capable of quick surface characterization
and is limited to transparent substrates only.
While SEM, TEM and SPM are capable of characterizing nanoparticle coatings on non-transparent
substrates, these techniques are cumbersome,
time-consuming and often expensive to use. Therefore, development of characterization techniques
capable of quick and reliable investigation of
nanoparticle-coated non-transparent, solid sub-
strates is needed. Recently, spectroscopic ellipsometry (SE) was applied to characterize assemblies of
nanoparticles deposited on monolayer [16,19,22,
23] and grafted polymer surfaces [14] bound to
solid, non-transparent substrates. Although the
actual ellipsometric measurements are simple and
fast,1 the quantitative characterization of nanoparticle coatings using SE is not trivial. Because of the
inverse-space nature of ellipsometry, [1,24,25], i.e.,
its inability to provide information about particle
number density (= number of particles per unit
surface area) directly from the measurements,
one needs to carry out optical modeling in order
to fit the experimental data to a multi-layer structure incorporating nanoparticles. This optical
modeling involves calculating the dielectric constant of the layer containing nanoparticles,
typically using various effective medium approximations, such as those by Bruggeman or Maxwell–Garnett [26]. While one can qualitatively
reproduce the experimental data using these models, quantitative comparison with experiments is
still rather poor [13,19]. Kooij et al. had to resort
to a complex model derived from the thin island
film theory [27,28] to improve the quantitative
comparison of nanoparticle surface coverage predicted by ellipsometry with actual coverage determined by atomic force microscopy (AFM) [19].
Even with the use of the complex model, Kooij
et al. obtained excellent agreement between the
predicted and actual surface coverage only above
20%; below this value, their ellipsometric prediction overestimated number of particles on the
surface. In their recent publication, Kooij and
co-workers improved the range of their prediction
by taking into account particle image dipoles and
lateral interaction upto quadrupole order [16].
While the approach used by Kooij and coworkers
is comprehensive and facilitates accurate estima1
Ellipsometry measures the change in polarization state of
light reflected from the surface of a sample in terms of W and D,
which are related to the ratio of Fresnel reflection coefficients,
Rp and Rs for p- and s-polarized light, respectively, according to
the expression q = tan (W)exp (iD) = Rp/Rs. Because of the
inverse nature of this problem, the W and D values cannot be
directly converted into the index of refraction versus sample
depth profile. Rather, a model-based iterative procedure is used
to fit the experimentally measured W and D values.
R.R. Bhat, J. Genzer / Surface Science 596 (2005) 187–196
189
tion of surface coverage, their ellipsometric model
is fairly complex, thus precluding quick estimation
of the surface coverage.
In this report, we demonstrate that by correlating ellipsometric measurements with those using
other surface sensitive techniques, such as nearedge X-ray absorption fine structure (NEXAFS)
spectroscopy, UV–vis and AFM, one can derive
simple relationships between the actual number
density of particles on the surface and that predicted from raw ellipsometric measurements. We
illustrate our point by considering two case studies
involving adsorption of gold nanoparticles on:
(1) amino-terminated organosilane self-assembled
monolayer (SAM) and (2) surface-grafted polyacrylamide film. Since ellipsometry measurements
depend on the nature of the interfaces present in
the sample, we obtain two distinct sets of ellipsometry spectra for these two different scenarios. By
subjecting the ellipsometry results to similar data
treatments, we establish correlations between raw
ellipsometric measurements and the number density of nanoparticles on the SAM as well as polymer surfaces. This approach will thus allow for
quick estimation of nanoparticle density on a
given surface without performing complex optical
modeling.
droxyl groups, which are required for coupling
organosilane molecules. In order to generate substrates with different coverage of nanoparticles,
we created a number density gradient of particles
following our earlier work [18]. For this, first a
gradient in concentration of 3-aminopropyltriethoxysilane (APTES) was prepared by vapor
diffusion method [18,30]. The substrate was subsequently immersed in an aqueous gold nanoparticle
solution for 24 h, following which the substrate
was washed thoroughly with DI water and dried
with nitrogen. The number density of adsorbed
gold nanoparticles was determined from tapping
mode AFM (Nanoscope III, Digital Instruments)
scans at various positions along the substrate.
The particle densities were determined from the
AFM micrographs (1 lm · 1 lm) by manual
counting. To determine the concentration profile
of APTES organosilane along the substrate, we
used near-edge X-ray absorption fine structure
(NEXAFS) spectroscopy [31], which was carried
out on the NIST/Dow materials characterization
end-station U7A at the National Synchrotron
Light Source at Brookhaven National Laboratory
(NSLS BNL) [32]. Details about the NEXAFS
measurement on the particle/SAM gradient system
can be found in Ref. [18].
2. Experimental
2.2. Preparation and characterization of
nanoparticle gradient on polymer films
2.1. Preparation and characterization of
nanoparticle gradient on monolayer films
All chemicals were purchased from Aldrich and
used as received. Deionized (DI) water (resistivity > 16 MX cm) was produced using the Millipore
water purification system. Silicon substrates with a
2 nm thick layer of native SiOx were purchased
from Silicon Valley Microelectronics. Aqueous
solution of gold nanoparticles was prepared by citrate reduction of HAuCl4 following the method of
Frens [29]. The resulting particles have a diameter
of 16.9 ± 1.8 nm, as established by TEM [18].
The silicon wafer was cut into rectangular pieces
(4.5 cm · 1.2 cm) that were exposed to ultraviolet/ozone (UVO) treatment for 30 min in order
to generate a large number of surface-bound hy-
In order to form end-grafted polymers on flat
silica-covered substrates, we used atom transfer
radical polymerization (ATRP) on account of its
ability to form polymers with a relatively low polydispersity index [33]. Because of the ability of amino-containing groups to bind to citrate-capped
gold nanoparticles [14,34,35], we grew an -NH2
containing polymer viz. polyacrylamide (PAAm).
To achieve this, we first formed a SAM of
organosilane-based polymerization initiator, (11(2-Bromo-2-methyl)propionyloxy)undecyltrichlorosilane (BMPUS), on a silica-covered silicon
substrate [14]. Polymerization of acrylamide
(AAm) was carried out using methanol/water
ATRP [36] at room temperature by immersing
the substrate vertically into a custom-designed
chamber that was charged with 10.0 g of AAm,
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30.0 g of methanol, 7.5 g of deionized water, 7.26 g
of bipyridine, 0.78 g of CuCl, and 0.0033 g of
CuCl2 and purged with nitrogen. The particle density on the substrate was adjusted by varying the
molecular weight (MW) of grafted PAAm, to
which the particles attach. Polymer assemblies
comprising gradually varying MW of PAAm on
the substrate were generated utilizing polymerization solution ‘‘draining’’ method [13] during the
‘‘grafting from’’ polymerization of AAm. The
dry thickness of grafted PAAm along the substrate
was measured by SE. PAAm MW gradient was
kept immersed in colloidal gold solution overnight
to achieve complete immobilization of particles on
the PAAm film. After drying the substrate, particle
number density along the substrate was measured
via AFM. Concurrently, a series of SE profiles was
collected at different positions along the PAAm
brush/particle specimen. UV–vis absorbance spectra were also collected from gold nanoparticle
coating deposited on a similar PAAm gradient film
grown from a glass slide.
3. Results and discussion
Nanocomposite coatings comprising different
particle surface coverages were created by utilizing
two different kinds of adhesive layers: (1) selfassembled monolayer and (2) surface-grafted polymer gradients. The objective behind using two
types of organic substrates was to test the ability
of ellipsometry to characterize and predict number
density of nanoparticles adsorbed on different
types of surfaces. In order to generate substrates
decorated with gradually varying particle coverages, we use the gradient approach, which facilitates systematic mapping of the entire range of
system parameters affecting a given phenomenon
[14,18,37]. In the case of the SAM density gradient,
varying concentration of underlying organosilane
species in a gradient fashion leads to nanoparticle
assemblies with continuously varying surface coverage (cf. cartoon in Fig. 1). The main advantage
of using a gradient specimen instead of several individual substrates is that one can minimize experimental errors associated with producing many
individual samples and ascribe an observed phe-
nomenon to the parameters being varied [38,39].
We have previously established that electrostatic
attraction between negatively charged gold particles and positively ionized APTES surface
(-NH3+) in slightly acidic gold sol results in binding
of particles to those parts of the surface which are
covered by APTES, resulting in a gradient in number density of particles [18]. Number density of
nanoparticles at various positions on the substrate
was determined from AFM scans. In order to correlate the number density of particles and concentration of APTES molecules on the substrate, we
monitored APTES concentration as a function of
the substrate position using NEXAFS spectroscopy. NEXAFS involves the resonant soft X-ray
excitation of a K- or L-shell electron to an unoccupied low-lying antibonding molecular orbital of r
symmetry, r*, or p symmetry, p* [31]. The initial-state K-shell excitation gives NEXAFS its element specificity, while the final-state unoccupied
molecular orbitals provide NEXAFS with its
bonding or chemical selectivity. A measurement
of the intensity of NEXAFS spectral features thus
allows for the identification of chemical bonds and
determination of their relative population density
within the sample. In a typical NEXAFS experiment, one measures the intensity of the Auger electrons that are emitted from the sample in the form
of the partial electron yield (PEY) signal. Positiondependent APTES concentration on the specimen
was determined by performing PEY NEXAFS line
scans at a fixed photon excitation energy corresponding to the N–H bond (400.0 eV) along the
gradient (cf. Fig. 1(a)). As can be seen from profiles
in Fig. 1(a), the intensity of peak at 400 eV decreases as one moves away from the front end of
the gradient (i.e., in the direction of decreasing
APTES concentration on the substrate). A linear
relationship between the particle number density
on the surface and PEY NEXAFS intensity of
the peak corresponding to N–H bond, shown in
Fig. 2, confirms that the nanoparticle gradient is indeed formed because of the underlying -NH2 organosilane gradient.
Fig. 1(b) presents three representative ellipsometry spectra taken at different positions along the
nanoparticle gradient. Specifically, we plot cos (D)
profiles as a function of the wavelength of ellipti-
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191
Fig. 1. (Top panel) Cartoon depicting gold nanoparticles adsorbed on an APTES organosilane concentration gradient. (Bottom panel)
(a) Partial electron yield NEXAFS intensity and (b) cosine of the ellipsometric angle D, cos (D), measured at three positions along the
specimen comprising gold nanoparticles adsorbed on APTES self-assembled monolayers with gradually varying density on a flat
substrate. The data illustrate that the increase in ATEPS density ( ! ), monitored by the increase in the N–H signal at 400 eV in the
NEXAFS spectra, is accompanied by a corresponding increase in cos (D) and a spectral blue shift in the peak between 500 and 600 nm.
cally polarized light (k), as cos (D) exhibits the
most pronounced changes. This higher sensitivity
of cos (D) compared to tan (W) is in accordance
with the equation, q = tan (W)exp (iD) = Rp/Rs,
which states that amplitude of q = jRp/Rsj is given
by tan(W) and difference of the phase between pand s-polarized components is related to cos (D).
In very thin films, such as the ones used in our
study, contribution to q due to the phase change
(i.e., cos (D)) dominates relative to the intensity
change (i.e., tan (W)) [25]. Upon adsorption of particles, an upward shift in cos (D) occurs over the
entire wavelength range, and a characteristic peak
develops around k 520 nm. The position of the
peak near 520 nm corresponds to the surface plasmon resonance of the gold colloids [7]. There are
two aspects worth noticing about this peak: its
magnitude and position. Magnitude of the peak,
cos (D)max, decreases as one moves away from the
front end of the gradient (i.e., as particle number
density decreases). Concurrently, the peak exhibits
a systematic spectral blue shift with increasing particle loading. In Fig. 3, we plot PEY NEXAFS
intensity collected at various positions along the
gradient against corresponding cos (D)max. Also
added in the plot are data points gathered from
various gradient samples prepared by depositing
gold particles at different pH values. All these
points fall on a master curve, which can be
approximated by a linear relation between PEY
NEXAFS intensity and cos (D)max. By cross-correlating the linear relations established between: (1)
nanoparticle number density and PEY NEXAFS
intensity (cf. Fig. 2) and (2) PEY NEXAFS intensity and cos (D)max (cf. Fig. 3), we establish a linear
relationship between particle number density and
cos (D)max. The result of such a cross-correlation
is shown by the line plotted in Fig. 4. The particle number density predicted by the line shows
excellent agreement with actual number density
determined from AFM scans. This agreement indicates that one can use spectroscopic ellipsometry
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Fig. 2. Correlation between the gold particle density determined from atomic force microscopy scans and the intensity of
the partial electron yield (PEY) NEXAFS N–H signal at
400 eV, measured on substrates comprising gold particles
adsorbed onto substrates having a concentration gradient of
APTES molecules.
Fig. 3. Correlation between the intensity of the partial electron
yield (PEY) NEXAFS N–H signal (at 400 eV) and the
maximum of cosine of the ellipsometric angle D, cos (D),
measured on substrates comprising gold particles adsorbing
onto substrates decorated with concentration gradient of
APTES molecules. In addition to varying the density of the
APTES molecules in the SAM, the particle density on the
gradient was further tailored by adjusting the pH of the gold
sol.
as a predictive tool to determine number density of
particles adsorbed on SAM surfaces.
Fig. 4. Comparison between the actual nanoparticle number
density in the particle/SAM system (solid data points) and that
predicted using SE (line), both plotted as a function of
cos (D)max. Actual number density is determined from AFM
scans of the surface. The predicted linear relationship between
particle density and cos (D)max was obtained by combining the
correlations between: (1) Au particle density and PEY
NEXAFS data (cf. Fig. 2) and (2) PEY NEXAFS data and
cos (D)max (cf. Fig. 3).
In order to test the predictive capability of
ellipsometry in determining nanoparticle density
on coatings comprising thicker organic layers,
we repeated a similar cross-correlation approach
for systems comprising gold nanoparticles attached to PAAm grafted surfaces. In our previous work, we have demonstrated that we can
enhance particle loading on the PAAm surface
by progressively increasing the length of PAAm
chain grown along the substrate (i.e., by creating
a gradient in MW of anchored PAAm) [13] (cf.
cartoon in Fig. 5). One advantage of using polymer coatings is that greater particle loading is
achieved, relative to that on SAM surfaces. This
increased surface coverage by nanoparticles allows one to employ UV–vis spectroscopy for
facile characterization of particle loading. In
Fig. 5(a) we plot UV–vis spectra taken at three
different spots along the nanoparticle gradient
formed on top of grafted PAAm surface. As particle concentration increases along the gradient,
the intensity of plasmon absorption peak around
520 nm (Amax) associated with gold nanoparticles
[7,11,12] also increases, accompanied by a spec-
R.R. Bhat, J. Genzer / Surface Science 596 (2005) 187–196
193
Fig. 5. (Top panel) Cartoon depicting gold nanoparticles adsorbed on substrate comprising surface-anchored polyacrylamide
molecular weight gradient. (Bottom panel) (a) UV–vis absorbance intensity and (b) cosine of the ellipsometric angle D, cos (D),
measured at three positions along the specimen comprising gold nanoparticles adsorbed on PAAm MW gradient. The data illustrates
that the increase in particle density ( ! ), monitored by the increase in the absorbance in the gold plasmon region, is accompanied
by a corresponding increase in cos (D) and a spectral blue shift in the peak between 500 and 600 nm.
tral red shift in the peak position. Such a behavior has previously been associated with increase
in gold particle concentration and consequent
clustering [12,17,40], thus justifying our claim
that we form particle density gradient by using
polymer brush MW gradient. Fig. 6 illustrates
quantitatively that particle number density on
the surface is linearly related to the absorbance
maximum, Amax.
In Fig. 5(b), we plot the characteristic profiles
of cos (D) measured at three different distances
from the sample edge, corresponding to the same
positions, at which the UV–vis data were taken.
The cos (D) spectra after attaching the gold particles to the PAAm brush are very different from
those acquired from PAAm brush alone. Similar
to the case of gold particles attached to APTES
SAM surfaces, a pronounced peak around
k 520 nm is detected, which reveals the presence
of gold nanoparticles on the substrates. The value
of cos (D)max is found to increase with increasing
particle concentration and there is a concomitant
spectral blue shift in the position of the peak. In
Fig. 7, we plot Amax versus cos (D)max—the two
parameters that arise predominantly due to the
presence of particles—collected at various points
on the gradient. A linear relation between the
two is detected. Once again, by cross-correlating
the linear relations between: (1) nanoparticle number density and Amax (cf. Fig. 6) and (2) Amax
and cos (D)max (cf. Fig. 7), we obtain a linear relationship between particle number density and
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Fig. 6. Correlation between the gold particle density determined from atomic force microscopy scans and maximum
intensity of the gold plasmon peak in the UV–vis spectra (Amax)
in the particle/PAAm system.
Fig. 7. Correlation between the maximum intensity of the gold
plasmon peak in the UV–vis spectra (Amax) and the maximum
of cosine of the ellipsometric angle D, (cos (D)max) in the
particle/PAAm system.
cos (D)max. The particle number density predicted
by such a linear relation agrees very well with actual number density ascertained by using AFM
scans (cf. Fig. 8). Thus, one can estimate nanoparticle number density on polymer-coated surfaces
by performing quick ellipsometry measurements.
In our approach, we conclude a linear relationship
between particle number density and cos (D)
Fig. 8. Comparison between the actual nanoparticle number
density in the particle/PAAm system (data points) and that
predicted using SE (line), both plotted as a function of
cos (D)max. Actual number density is determined from the
AFM scans of the surface. The predicted linear relationship
between Au particle density and cos (D)max was derived by
combining the correlations between: (1)Au particle density and
the maximum of UV–vis absorbance (cf. Fig. 6) and (2) the
maximum of UV–vis absorbance and cos (D)max (cf. Fig. 7).
parameter measured in SE via other independent
surface characterization techniques. This approach
then qualifies SE to be used routinely after an initial calibration. Figs. 4 and 8 reveal that for the
range of particle densities considered (upto 22%
surface coverage), there is a linear relationship between the number of particles on the surface and
cos (D)max value measured by ellipsometry, irrespective of the nature of the underlying layer.
However, due to the different physical characteristics of the two underlying layers, the slopes of the
two lines are different. Therefore, spectroscopic
ellipsometry measurements can be used to quantitatively compare samples containing nanoparticles, as long as all the samples have similar
physical nature.
4. Conclusions
The chief aim of this paper was to demonstrate
the predictive power of spectroscopic ellipsometry
(SE) in determining number density of nanoparticles bound to surfaces decorated with either organ-
R.R. Bhat, J. Genzer / Surface Science 596 (2005) 187–196
ic monolayers or surface-grafted polymers. By
utilizing a battery of experimental tools, involving
atomic force microscopy (AFM), near-edge X-ray
absorption fine structure (NEXAFS) spectroscopy, ultraviolet–visible (UV–vis) spectroscopy,
and SE we derived an empirical linear relationship
that correlates the number density of nanoparticles
on surfaces and cos (D) parameter measured in SE.
Excellent agreement among data collected by
various experimental probes suggested that SE
can be utilized as a convenient predictive tool facilitating the determination of the number density
of nanoparticle bound to solid non-transparent
substrates.
Acknowledgements
This work was supported by the National Science Foundation. The authors would like to thank
Dr. Kirill Efimenko (NCSU) and Dr. Daniel A.
Fischer (NIST/BNL) for their assistance during
the course of NEXAFS measurements. NEXAFS
experiments were carried out at the National Synchrotron Light Source, Brookhaven National Laboratory, which is supported by the US Department
of Energy, Division of Materials Sciences and
Division of Chemical Sciences.
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