STEWART ET AL.VOL. 6
’ NO. 5
April 13, 2012
C2012 American Chemical Society
Controlling Assembly of Mixed Thiol
Monolayers on Silver Nanoparticles to
Tune Their Surface Properties
Alan Stewart, Shuai Zheng, Maighre ´ad R. McCourt, and Steven E. J. Bell*
School of Chemistry & Chemical Engineering, Queen's University Belfast, Belfast BT9 5AG, U.K.
ing particles with required properties are to
change the size, shape, or composition of
the bulk particles and/or to modify the sur-
face. In many cases both the structure and
example to create particles with appropri-
ate optical properties that can also interact
been enormous effort and success in the
developmentof methods for preparation of
particles of controlled sizes and shapes,
including prisms,5,6rods,7cubes,8and nano-
stars,9,10as well as bumpy gold nano-
particles,11hollow gold nanoparticles,12
and nanoshells,13less research has been
carried out on methods for controlling na-
nanoparticles, by far the most popular
method is to use self-assembled mono-
layers (SAMs) of ω-substituted thiols that
spontaneously bond to the surface via
strong covalent metal?thiol bonds.2This
approach is a simple extension of methods
bulk metal substrates, e.g., electrodes and
Modification of nanoparticles with single
thiols allows gross control of the surface
ofthe modifier, but the possibilities for finer
tunability, e.g., by using alkanethiols with
different chain lengths,15are limited. How-
ever, it should be possible to use mixed
monolayers of two or more thiols to create
nanoparticles with properties intermediate
between those obtained with the pure
of both on the surface. The advantage of
this method is that it potentially allows con-
tinuous tuning of the surface properties be-
tween very different extremes. Indeed, meth-
ods for preparing mixed thiol monolayers on
etal nanoparticles are ubiquitous
two main approaches to design-
bulk metal surfaces are well established, and
as contact angles, between extreme values
simply by altering the relative proportions of
hydrophilic and hydrophobic thiols on the
surface.16However, the most widely used
methods for modifying bulk metals, which
are based on sequential immersion in solu-
tions of different thiols (which may also
include addition and removal of chemical
*Address correspondence to
Received for review July 25, 2011
and accepted April 13, 2012.
Modifying the surfaces of metal nanoparticles with self-assembled monolayers of functiona-
lized thiols provides a simple and direct method to alter their surface properties. Mixed self-
assembled monolayers can extend this approach since, in principle, the surfaces can be tuned
by altering the proportion of each modifier that is adsorbed. However, this works best if the
composition and microstructure of the monolayers can be controlled. Here, we have modified
preprepared silver colloids with binary mixtures of thiols at varying concentrations and
modifier ratios. Surface-enhanced Raman spectroscopy was then used to determine the effect
of altering these parameters on the composition of the resulting mixed monolayers. The data
the feedstock when the total amount of modifier was sufficient for approximately one
monolayer coverage. At higher modifier concentrations the thermodynamically favored
modifier dominated, but working at near monolayer concentrations allowed the surface
composition to be controlled by changing the ratios of modifiers. Finally, a positively charged
porphyrin probe molecule was used to investigate the microstructure of the mixed
monolayers, i.e., homogeneous versus domains. In this case the modifier domains were
found to be <2 nm.
KEYWORDS: nanoparticles.surface modification.mixed monolayers.SERS.
STEWART ET AL.VOL. 6
’ NO. 5
templating agents)17or immersion in a single solution
of a mixture of thiols,18,19do not transfer readily to
direct modification of colloids, which cannot be im-
mersed and then removed at will. An alternative
approach, in which the particles are synthesized in
the presenceofcapping agents,has becomepopular.20
Originally, only single capping agents were used, but
the use of mixtures is becoming more common. For
capped with thiols such as octanethiol and mercapto-
propionic acid via a one-step route21and shown that
they form ribbon-like domains on the surface due to
the surface curvature,21?23which disappear when sur-
face curvature is reduced.24Alternatively, a place ex-
change reaction may be used to partly replace the
capping agent with a different compound.25,26
nanoparticles produced using capping agents,27most
previous studies have focused on small gold spherical
nanoparticles or rhomboid nanoclusters.28,29The ma-
jor problem of the capping agent approach for func-
tionalizing nanoparticles is that it removes the
simplicity and flexibility of being able to prepare
particles with the desired size and shape before select-
ing their surface properties through chemical modifi-
cation. We prefer the more flexible approach of first
synthesizing the nanoparticles and then functionaliz-
ing them with mixtures of thiols, since this should
allow us, for example, to make nanoprisms, rods, or
but then to use a standard method to functionalize
their surfaces. There have been some reports of the
approach being followed for spherical Au nano-
the composition of the feedstock is not necessarily
reflected in the resulting SAM.30,32While it is possible
to use trial and error to find appropriate reaction
conditions, these are not expected to be generally
transferable between different particles and modifier
mixtures. Here our objective is to develop an under-
standing that will allow the process to be controlled
and surfaces to be generated in a predictable way. The
model systems investigated were hydroxylamine-
reduced silver colloid (HRSC),33citrate-reduced silver
colloid (CRSC),34or Ag nanoprisms,35which were syn-
thesized by literature methods, then modified using
mixed thiol feedstocks of various concentrations. All
of the particles used in this study provide strong
enhancement of the surface species' Raman signals,
which allows the SAM composition to be monitored
in situ using surface-enhanced Raman spectroscopy
(SERS), since each compound gives its own character-
istic Raman spectrum.4,36
An additional important aspect of mixed SAMs on
nanoparticles is that cooperative effects from both
modifiers may provide properties that cannot be in-
troduced using single modifiers.37For example, we
have recently developed a SERS sensor that used a
mixed monolayer composed of mercaptopropanesulfo-
nate (MPS) and benzyl mercaptan (BZM) and promoted
sorption, while those modified with only MPS or BZM
showed no MDMA binding.36The microstructure of the
mixed monolayer is crucial in determining whether such
the surface, the only part of the surface where both
of nucleation for some place exchange reactions).38
Alternatively, if there is intimate mixing of the modi-
fiers, then the entire surface will have properties that
are different from either of the two modifiers. In this
work we have developed a method that allows nano-
particles modified with mixed SAMs to be prepared
with a desired composition and have then used a
charged SERS-active porphyrin molecule to probe
the microstructure of the surfaces of these modified
Figure 1. (A) Modification of a preprepared silver nanopar-
ticle with a mixed thiol feedstock. (B) SERS spectra of (i) PT
and (ii) MPS adsorbed on HRSC. (C) SERS spectra of 1:1
mixtures of MPS and PT added to HRSC at total modifier
intensities of MPS and PT bands. (Inset) Semilog plot of the
ratios of the heights of PT (896 cm?1) and MPS (802 cm?1)
bands against total modifier concentration.
STEWART ET AL. VOL. 6
’ NO. 5
RESULTS AND DISCUSSION
Figure 1 illustrates the general approach we have
followed, which is to add dilute mixtures of thiol
modifiers to SERS-active Ag colloids that had been
prepared using standard literature methods33?35and
to monitor the surface composition of the resulting
modified nanoparticles using SERS. Mercaptopropane-
sulfonate (MPS) and 1-pentanethiol (PT) modifiers
were used in this test system, since their SERS spectra
were quite distinct and simple comparison of the
strong bands at 802 (MPS) and 896 cm?1(PT) allows
the relative proportions of each to be estimated
directly. Figure 1C shows the SERS spectra of a series
of colloids prepared with simple 1:1 MPS:PT modifying
feedstocks that had different total modifier concentra-
tions (between 10?3and 10?5M, corresponding to
approximately 0.1?10 monolayers). Surprisingly, the
relative intensities of the marker bands changed dra-
matically over the series. At high total modifier con-
centrations, only PT bands could be observed in the
spectra, and MPS bands only appeared as the total
concentration of modifiers was reduced. A plot of the
ratio of the heights of marker bands at 896 cm?1(PT)
and 802 cm?1(MPS) against the total concentration
of modifiers in the feedstock (Figure 1C, Inset) shows
that above 1 ? 10?4M (corresponding to monolayer
coverage) PT preferentially adsorbs, but below mono-
layer coverage the ratios of peak heights are similar.
We believe that this effect is a result of competition
between MPS and PT for surface sites. At high con-
centrations the relative proportion of each modifier on
the surface is determined by their relative binding affi-
nities. However, at total modifier concentrations that are
closer to those required for monolayer coverage, the
equilibrium position resulting from the competitive ad-
modifier with the highest affinity will deplete its concen-
tration in the bulk phase, reducing its ability to compete
for the remaining sites. This can be modeled using an
are equal at equilibrium:
k1A[A](1 ?θA? θB) ¼ k2AθA
where k1Aand k2Aare the rate constants for adsorption
and desorption of A and θAand θBare the fractions of
the surface covered by modifiers A and B. However, in
onto the surface:
k1A([A] ?[A]ads)(1 ? θA?θB) ¼ k2AθA
By expressing the concentration in monolayer units
(i.e., relative to the number of molecules required to
so that N is the number of potential monolayers in the
modifying solution, xAis the proportion of A in the
modifying feedstock, andby combining rate constants
it can be shown that
1 ? θA
K0(xAN ? θA)
where K0is a composite quantity determined by the
adsorption and desorption rate constants for A and B
(k1Ak2B/k2Ak1B). Figure 2 shows plots of θAagainst N for
various values of K0obtained by solving eq 3 numeri-
cally. At high concentrations, eq 3 reduces to the
standard Langmuir model, because the term correct-
ing for the adsorbed modifier becomes negligible, i.e.,
(xAN ? θA) = xAN. Since (1 ? xA)N . 1 . θAat high N,
and at 1:1 feedstock the relative surface coverage is
directly proportional to the relative sizes of the equi-
At intermediate concentrations the proportions are
less heavily weighted in favor of the modifier with the
highest binding constant until at N = 1 the above
model breaks down, since it assumes that θAþ θB= 1,
and this cannot be true for N < 1. At values of N < 1,
there are not enough molecules in solution to form a
complete monolayer, and the fraction of the surface
covered in A, θA, will be limited by the amount of A
present in the feedstock, i.e., xAN, (assuming k1Ais large).
Since there will still be free sites even if all of A has
adsorbed to the surface, B is also free to adsorb without
competition. Therefore, the ratio of A to B on the surface
will be equal to their ratio in the modifying feedstock.
Figure 3 compares experimental data for 1:1 feed-
stocks of three different thiol mixtures over large con-
centration ranges. These mixtures were chosen because
Figure 2. Predicted fractional surface coverage, θA, given
by a 1:1 A:B feedstock with changing total modifier con-
centration. Simulations at different values of K0, the ratio of
binding constants between the modifiers A and B, are
shown. Above monolayer concentrations, the fractional
coverage of A increases according to the value of K0; below
monolayer concentrations, the fractional coverage of A will
be 0.5 regardless of the value of K0.
STEWART ET AL.VOL. 6
’ NO. 5
their relative K0values were also expected to span a
large range. Similarly, in order to demonstrate the
generality of this approach, the measurements were
spherical, diameter ca. 62 nm), CRSC (mixed morphol-
ogy spheres, rods, truncated prisms, etc.) and silver
nanoprisms (edge length ca. 20?30 nm). Data from
ing the reproducibility of the measurements are given in
the Supporting Information.
The data for PT:MPS mixtures on HRSC show the
trend that the model predicts, with approximately
equal proportions of each modifier at submonolayer
coverage and a dramatic rise in the proportion of the
70, reflecting the much more favorable binding of PT
compared to MPS. In contrast, in the PT:BZM system
the binding constants are much more similar to each
other so that neither modifier dominates, even at higher
valueof1.8, which reflectsthefactthatthefraction of PT
on the surface does rise slightly above 0.5 at higher
concentrations. The difference between 3A and 3C is
supplementary Figure S3 shows that PT:BZM on HRSC
behaves similarly to the same mixture on CRSC. The
methoxybenzenethiol (MOBT):thiophenol (TP) system,
shown on silver nanoprisms in Figure 3B, lies between
these two extremes of K0. Although PT:BZM comes
close, none of the systems we have studied have a K0
surface monolayer composition match that of the
feedstock at all values of total concentration.
The main implication for these results is that the
composition of mixed monolayers is not simply con-
trolled by the molar ratio of the modifiers in the feed-
stock and the relative binding constants; the overall
concentration is also critical. The larger the difference
in binding constants, the larger the effect that the
concentration will have. This means that, in principle,
the surface could be tuned by altering the total con-
centration at afixedfeedstock composition ratio, since
at higher concentrations the more strongly binding
modifier will occupy more surface than the weakly
bound one, even if the ratio in the feedstock is 1:1.
However, this approach will result in samples where
the nanoparticles sit within solutions containing large
amounts of unbound thiol modifiers. It is preferable to
work at modifier concentrations near monolayer cov-
erage, since this will minimize the amount of residual
unbound modifier. In addition, working at this con-
centration should also minimize preferential binding
effects and thus allow mixed monolayers composed of
thiols with very different binding constants to be pre-
pared by altering the relative concentrations in the
Here wehaveillustrated thiseffectusingthe PT:MPS
system, which has very different binding constants
(K0= 70), and have carried out experiments where the
total modifier concentration was fixed at 1 ? 10?4M
(equivalent to ca. 1.25 monolayers with the volume of
HRSC used). This ensured full monolayer coverage but
still allowed the surface compositions to be varied by
the experimental conditions, rather than be domi-
nated the relative binding constants of the modifiers.
For example, as shown in Figure 4, when the composi-
tion of the PT:MPS feedstock was varied in 10% incre-
ments from 0 to 100% (with a fixed total modifier
the spectrum of PT to that of MPS was observed.
The heights of the MPS and PT peaks at 802 and
896 cm?1, respectively, could be used to track the
surface composition of the monolayers. In principle,
this should be simply a matter of calculating the
mole fraction on the surface by determining the
height ofeachpeakas afractionofits heightwhenthe
colloid was completely covered in that component
(Figure 4B). However, it was found that this gave
across the series, while the total should be 1.00 at all
Figure 3. Plots showing how the surface mole fractions of
various modifiers adsorbed from 1:1 binary modifier mix-
tures change with total amount of modifier. Solid lines are
the fits to the competitive binding model discussed in the
text. Plots show the fractions of (A) PT adsorbed from a PT:
MPS feedstock on HRSC, (B) MOBT from a MOBT:TP feed-
stock on Ag nanoprisms, (C) PT from a PT:BZM feedstockon
CRSC. 200 μL of silver colloid was used in each case.
STEWART ET AL.VOL. 6
’ NO. 5
feedstock compositions. The most likely explanation
for this change was that the extent of aggregation
varied across the composition range. Nevertheless,
irrespective of its origin, the variation could be cor-
rected by finding the factor needed to give each
sample a total mole fraction of 1 and then multiplying
each height in that sample by this correction factor, as
shown in Figure 4C.
It is striking that although the curves in Figure 4C
cross at 50% MPS in feedstock, they do not directly
follow the composition of the feedstock, which would
give straight line plots. In fact the model does not
predict straight line behavior for N > 1, since if N > 1,
competition for surface sites moves the crossover in
favor of the more strongly binding modifier. Of course,
if the conditions are close to N = 1 or if both modifiers
are similarly binding (i.e., K0= 1), then there will be no
competition and straight line behavior will be ob-
served. For example, the plot for the PT:BZM system
at close to monolayer concentration shown in Figure 5
is near linear. However, the main point is that this ap-
in a rational way by altering the feedstock composition,
even if they have very different binding constants.
The reason for preparing mixed monolayers is to
modulate the properties of the nanoparticles. In many
cases this requires the surface to have a local composi-
tion that is mixed on an appropriate length scale, i.e.,
for any domains present to be smaller than the foot-
print of the probe technique. For example, in our work
molecule targets onto nanoparticles for SERS sensors,
the binding requires the adsorbed molecules to inter-
act simultaneously with different modifiers36and par-
ticles covered with just one of the modifiers do not
bind the targets. This means it is essential to under-
stand not only the relative amounts of the modifier
present on the surface but also how they are arranged
than the critical length scale. This general problem has
previously been addressed using ESR,40fluorescence,41
mass spectrometry,42and chemical cross-linking ap-
proaches.43Evidence for domain formation has been
obtained, but it is not clear how system- dependent
these effects are. Here we have used the simple PT
and MPS thiol modifiers and a well-known cationic
porphyrin complex test compound (zinc 5,10,15,
showing the fractional height of MPS (802 cm?1, ?) and PT (896 cm?1, Δ) along with the sum of these. (C) Plot of the mole
3 replicate experiments.
Figure 5. Corrected fractional coverages of modifiers in
mixed monolayers of (a) BZM (O) and PT (Δ) on HRSC at
total concentration 10?4M, i.e., close to monolayer. Error
bars are (1 s calculated from 3 replicate experiments.
STEWART ET AL.VOL. 6
’ NO. 5
p-tosylate salt (ZnTMPyP)). This probe is expected
to be attracted to the anionic MPS but not the
Figure 6A shows selected spectra of 1.5 ? 10?6M
ZnTMPyP on nanoparticles functionalized with SAMs
of MPS, PT, and mixtures of the two components. The
absence of binding to the pure PT surface shows that
electrostatic attraction to the modifier is required to
promote adsorption, which will limit the positively
charged porphyrin to adsorbing only to sections of
the surface where it overlays at least one of the
negatively charged MPS modifiers. This means that if
the domains on the mixed surface were much larger
than the probe molecule (similar to a Janus particle),44
then the fraction of the surface capable of attracting
ZnTMPyP would be the fraction covered by MPS. In
that case the ZnTMPyP SERS signal from a mixed
monolayer would increase linearly with the fractional
coverage of MPS. Thus, as shown in Figure 6C(i), at
only approximately 50% of the surface (and give half
the maximum possible signal) since the PT-covered
half will not allow ZnTMPyP binding. However, it is
clear from the spectral data in Figure 6A that even a
small amount of MPS on the nanoparticle surface
promotes a disproportionate amount of binding of
ZnTMPyP and that an MPS fractional coverage of
20?25% (uncorrected for total signal height) gives a
50:50 coverage is already at the maximum value,
implying full surface coverage by the porphyrin probe.
potential binding sites meeting the criterion for probe
adsorption increases as the domain size decreases, as
shown in Figure 6C(iii). In this case it is clear that the
surface will find at least one negatively charged modi-
fier and adsorb; that is, the domains are <2 nm. This is
similar to the morphology of SAMs on Au(111) sub-
strates recently reported by Bukowska,19Au nanopar-
ticles reported by Stellacci, where one modifier forms
microdomains in a “percolated matrix” of the other,21
and Au nanoparticles modified with thiols carrying
cationic head groups.41
concentration was kept constant at 1 ? 10?4M): (i) blank spectra obtained from the modified colloids only; (ii) the same
colloids after addition of 1.5 ? 10?6M ZnTMPyP. (B) Variation in the intensity of the strong ZnTMPyP marker band at
simple 1:1 relationship has been included for emphasis. (C) Cartoon representation showing how different modifier domain
domains are much larger than the probe molecule, while in (ii) the domains are an intermediate size, and in (iii) the domains
not allow probe adsorption if the microstructure is type (i), while type (iii) has underlying MPS at all potential binding sites.
STEWART ET AL.VOL. 6
’ NO. 5
It has been shown that silver nanoparticles of various
byaddingthe correctconcentration of modifiersdirectly
composition of the surfaces can be modeled using a
competitive adsorption approach that explicitly includes
the effect of depletion of the bulk modifier at low feed-
in the feedstock while maintaining the overall modifier
concentration at an appropriate level. The surfaces can
also be probed by adding model analytes, yielding more
information on their composition and behavior.
It is believed that the processes developed for
studying mixed SAMs of PT and MPS can be applied
to many other binary mixtures of thiols, which is a
necessary step in the development of metal nanopar-
ticles for increasingly complex purposes.
Silver nitrate (99.9999%), hydroxylamine hydrochloride, so-
dium chloride, sodium mercaptopropanesulfonate, 1-penta-
nethiol, benzyl mercaptan, methoxybenzenethiol, thiophenol,
tetra-p-tosylate were purchased from Sigma-Aldrich. Sodium hy-
droxide was purchased from Riedel-de Haën, and all chemicals
were used as received without further purification. All solutions
were prepared from distilled, deionized (DDI) water (resistivity =
18.2 MΩ), obtained from a Branstead Nanopure system, or from
absolute ethanol obtained from T. E. Laboratories Ltd.
Hydroxylamine-reduced silver colloid was synthesized fol-
lowing the method published by Leopold and Lendl.33A 5 mL
amount of NaOH (0.1 M) was added to 5 mL of aqueous
hydroxylamine hydrochloride (6 mM); then the whole mixture
was added to 90 mL of aqueous AgNO3(0.1 mM) with stirring.
before use. The Cl?stabilizing ions were characterized by the
Ag?Cl stretch at 240 cm?1in the SERS spectrum. These mostly
spherical nanoparticles were analyzed by the dynamic light
scattering technique using a Malvern Zetasizer Nano ZS and
found to have an average diameter of 62 nm. The total surface
area of the colloid in a given volume was calculated by assum-
ing that all the silver salt was converted to colloidal silver and
that all nanoparticles were spherical with a diameter of 62 nm.
This allowed the amount of modifier required for monolayer
coverage to be approximated by dividing the total surface area
by the area taken up by one molecule, which was calculated as
20.2 Å2by Giz et al.45The values obtained were found to agree
well with isotherm experiments.
Citrate-reduced silver colloid was synthesized according to
Lee and Meisel's method.34AgNO3(45 mg) was dissolved in
250 mL and heated under reflux until boiling. When the boiling
temperature was reached, 5 mL of 1% sodium citrate solution
was added dropwise with stirring. The mixture was allowed to
reflux for 90 min and was allowed to cool to room temperature.
These nanoparticles are well-known to have a mixture of sizes
area of these was determined by direct measurement of the
Silver nanoprisms were synthesized using a modified version
of the method published by Aherne et al.35Seeds were pro-
duced by combining aqueous sodium citrate (5 mL; 2.5 mM),
polysodium styrenesulfonate (0.25 mL; 500 mg L?1), and so-
dium borohydride (0.3 mL, 10 mM), then adding silver nitrate
(0.5 mM) at a rate of 0.57 mL per minute. A 90 μL portion of this
seed solution was dispersed in 5 mL of DDIH2O and mixed with
was added at a rate of 0.57 mL per minute. Sodium citrate
solution (0.5 mL; 25 mM) was added to stabilize the particles,
which were then cleaned by centrifuging at 3500 rpm for 1 h,
removing the supernatant, and resuspending in the same
volume of DDI H2O. The purple solution of nanoprisms was
characterized by UV?vis spectroscopy using an Agilent 8453
spectrometer and were found to have a λmaxof 553 nm, which
was expected to correspond to an edge length of approxi-
mately 20?30 nm.35
Stock solutions of each modifier were prepared by dissolving
MPS in distilled, deionized water and dissolving PT and BZM in
absolute ethanol. Mixed feedstocks were made by combining the
to silver colloid and stirring vigorously for approximately 5 s.
Samples for SERS analysis were prepared by adding 20 μL of
modifying feedstock to 200 μL of colloid and aggregating with
20 μL of 1 M NaCl (for HRSC and CRSC) or 20 μL of 0.1 M MgSO4
was added before the aggregation stage. Raman spectra were
acquired using an Avalon R2 Ramanstation, equipped with a
785 nm diode laser delivering 100 mW at the sample. Back-
scattering at 180? was collected using an Echelle spectrograph
and Avalon electrically cooled CCD. Integration times were 3 ?
10 s for all spectra.
In some experiments (shown in Figures 4 and 5), it was
necessary to correct the raw data to allow for system-wide
changes in intensity. The raw data were treated by normalizing
its height when the colloid was completely covered in that
components on thesurface would be thethiol modifiers, so the
sum of the fractional heights should equal 1. However, the sum
of the heights varied between ∼0.5 and 1.1, so it became
necessary to apply a correction factor to the data, which was
of the modifiers. The fractional heights were multiplied by the
on the surface, which are plotted in Figures 4C and 5.
Conflict of Interest: The authors declare no competing
Acknowledgment. The authors thank the Engineering and
Physical Sciences Research Council for partially funding this
Supporting Information Available: MixedisothermsofPT:BZM
on HRSC, UV?vis spectra of MPS:PT-modified HRSC, SERS spectra
of modifiers. This information is available free of charge via the
Internet at http://pubs.acs.org.
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