Adsorption of Au Nanoparticles at Silica-

Water InterfaceMing

11/28/2011

Aggregation of particles on surfaces or molecules into self-assembled monolayers is an intrinsically non-Langmuirian process

Interaction between the aggregating moieties is a fundamental requirement.

Introduction

Random sequential adsorption (RSA) is a classical model of irreversible adsorption on substrates.

The adsorption of large particles such as colloids, protein, or latexes on substrates is often a highly irreversible process.

The objects are randomly and sequentially deposited onto a substrate. The adsorbed particles are permanently fixed at their spatial position.

The binding of the first layer to a surface by a Langmirian process at low surface coverage. Multilayer formation forms during the adsorption process.

Random sequential adsorption

E-CRDS is an ultrasensitive absorption spectroscopy used to observe the deposition of particles from gas or liquid phase onto surface.

The e-CRDS interrogation of the nanoparticles is sensitive to small extinction changes of the particle plasmon, which is related to the amount of adsorbed particles.

Evanescent wave cavity ring-down spectroscopy (e-CRDS)

Two high-reflectivity mirrors are placed opposite one another to form a linear optical cavity.

Laser radiation from continuous wave diode laser introduce into a mirror from the back of the mirror.

The radiation intensity in the cavity decays with a ring-down time, τ, was determined.

Any species that absorb radiation at the wavelength of the laser cause a decrease in the ring down time, τ, that is related directly to the absorbance of the species.

Au nanoparticle colloids of 15 ± 3 nm synthesized by citrate reduction

Au nanoparticle colloids of 45 ± 26 nm synthesized by sodium borohydride reduction

Au nanoparticles

Result and discussion

The real-time extinction during adsorption process for five dilutions

AFM images of the low surface coverage have been taken for known extinctions at both interrogation wavelengths

Low surface coverage layers (<5%) were deposited from the more dilute solution with only a few of the particles aggregated into pairs or structure on the surface.

Surface coverage

Surface concentrations and the surface coverage was determined from the AFM images

The concentrations of particles on the surface responsible for a known change in τ and hence extinction can be determined.

Extinction coefficient and get by the ratio of the extinction over the surface coverage.

The extinction coefficient is assumed to be constant with varied surface concentration

Extinction coefficient

The real-time extinction during adsorption process for five dilutions

Analysis of the monolayer-coverage extinction based on the extinction coefficients indicates that multilayers are being formed on silica surface

The maximum coverage for the citrate colloid corresponding to 2.9 layers.

The extinction for the low colloid concentration indicates that a complete monolayer has not been formed but this does not exclude the possibility of multilayered islands forming on the surface during the adsorption process.

Multilayers formed

Initial rate

Adsorption binding kinetics of the Au particles for sub-monolayer surface coverages should follow a simple differential rate law.

But the variation of initial slopes depends on colloid concentration, and it is not linear.

Two stoichiometric coefficients can be introduced to give a differential rate law of the form

Where ka is the association rate constant, [col] is the bulk concentration of the colloidal particles, θ is the surface coverage, and kd is the dissociation constant

t

For initial slope (θ ~ 0)

For citrate colloid: n1 = 2.07±0.13 at 635 nm and n1 = 3±1 at 830 nm

For borohydride colloid, a linear relationship with the colloid concentration indicating that a more conventional adsorption rate law is appropriate n1 = 1

Fitting results

The stoichiometric coefficient for the citrate-reduced gold nanoparticles indicates that the 15 nm nanoparticles aggregate better to one another on the surface even for low surface coverages.

The aggregation of 15 nm nanoparticle may due to its smaller size or citrate surface.

The low-colloid-concentration kinetic traces corresponding to 64 pM for the borohydride colloid and 1.2 nM for the citrate colloid have been fitted to the differential rate law with n1 and n2 set to 1.

These rate constants can be determined and binding constants (KD = kd/ka) are 0.74 ± 0.47 nM for the borohydride 45 nm particles and 2.75 ± 0.55 nM for the citrate 15 nm nanoparticles

Measurement of binding constant

These values of KD related to the Gibbs free energy of dissociation to give binding energies of 50 kJ mol-1 for the particles.

These is insufficient energy available thermally to dissociate the particles from the surface, and that once on the surface, the nanopartices do not move around or leave the surface rapidly and the binding event is irreversible.

Irreversibility of adsorption

The formation of aggregates on the surface is not restricted to packing in two dimensions and allow the aggregates to form multilayers

The binding constant for the nanoparticles on the surface suggests the particles do not move on the surface once attached

Extension kinetic model for Multilayer

Extension of kinetic model

Where θ1 is the coverage of the first layer next to the silica and θi is the coverage of the ith subsequent layer. The random deposition model allows aggregation and desorption from the silica surface using a standard langmuir non-interacting isotherm and a single adsorption rate and desorption rate for each of the subsequent gold layers.

The model reveals a sticking coefficient KM = 0.14 ± 0.03 nM for the silica-gold layer and 3.9 ± 0.8 nM for the gold-gold aggregation in three layers.

The layers fill up with a Poisson relation (Poisson distribution) between the relative coverages: θ1 = 0.894, θ2 = 0.858, θ3 = 0.824 with a surface roughness of 0.9.

The fitting is not unique with similar quality fits being found for three, four, and five layers on the surface but with the same distribution in the coverages.

Fit to the 100% colloid (6.2 nM)

The co-operative adsorption-aggregation process for the formation of the layer requires the structure of the charged interface to change as the layers develop.

The surface potential will change and similarly the profile of the electric field in the interface.

The rate constants for low surface coverage of layer 1 are four times larger than for the filling of layer 1 when the co-operative, random sequential model is used indicating “rate constant” variation during the aggregation.

Surface coverage effect

The colloidal solutions were diluted in citrate to 5%

After maximum extinction value achieved, the surface was washed in water, IPA, and HCl to remove the citrate ligand from particles. While no particles were removed

The adsorption of particles on washed surface was studied.

Adsorption after removal of ligand

The surface coverage is 1.2% for at the first adsorption stage.

A second adsorption phase is then possible with a similar adsorption profile reaching surface coverage of 3.0%. The number of small aggregates increases.

In third adsorption phase, there is a radically faster adsorption rate and significant cluster population on the surface as seen.

The adsorption of Au nanoparticles colloid on silica surface is highly irreversible process and the particles do not move on the surface once attached

Particle adsorption and aggregation kinetics suggest that particles show two effects associated with the packing: the size dependence and bilayer stabilization.

The citrate ligand on the surface of the particles may assist in the aggregation process of smaller particles, but larger 45 nm particles do not show aggregation.

Conclusions

Both 15 and 45 nm particles pack into multilayers although the aggregation appears to be size and ligand dependent.

The ligands around the particles control the nature of the charged interface and the surface energy of the particle and consequently influence the aggregation kinetics and surface structure.

Conclusions

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