Improving the Detection Accuracy of an Ag/Au Bimetallic Surface Plasmon Resonance Biosensor Based on Graphene

A theoretical study was conducted with the aim of improving the detection accuracy of graphene-based surface plasmon resonance (SPR) biosensors. We studied the effect of applying a bias voltage to the sensor surface on its detection accuracy. The optimum thicknesses of silver and gold layers in the biosensor of 47 nm and 3 nm, respectively, were determined. Graphene layers deposited on these thin silver and gold films formed a sensor surface system, on which the surface plasmons were excited. The real and imaginary parts of the refractive index of graphene were controlled by the bias voltage. When the chemical potential was increased from 36 meV to 8 eV, the detection accuracy of the sensor was correspondingly increased by 213%.

Structure of PtRu/Ru(0001) and AgPd/Pd(111) surface alloys: A kinetic Monte Carlo study

Bimetallic surfaces allow tailoring their catalytic activity by modifying their composition and/or structure. However, under operating conditions, catalytically active bimetallic structures are often not stable and change their morphology which might reduce their functionality. Still, catalytically active structures do not necessarily need to be thermodynamically stable and might also be kinetically stabilized. Here we report kinetic Monte Carlo simulations based on density functional theory calculation to address the meta-stability of surface alloy systems. As structural changes can typically only occur via vacancy diffusion in the surface, we first determine the vacancy diffusion barrier as a function of their bimetallic environment. By determining the temporal evolution of the bimetallic surface alloys as a function of temperature, we analyze the factors underlying the stability and structure of the bimetallic surface alloys.

Sensitivity Analysis of Single- and Bimetallic Surface Plasmon Resonance Biosensors

Comparative analysis of the sensitivity of two surface plasmon resonance (SPR) biosensors was conducted on a single-metallic Au sensor and bimetallic Ag–Au sensor, using a cathepsin S sensor as an example. Numerically modeled resonance curves of Au and Ag–Au layers, with parameters verified by the results of experimental reflectance measurement of real-life systems, were used for the analysis of these sensors. Mutual relationships were determined between ∂Y/∂n components of sensitivity of the Y signal in the SPR measurement to change the refractive index n of the near-surface sensing layer and ∂n/∂c sensitivity of refractive index n to change the analyte’s concentration, c, for both types of sensors. Obtained results were related to experimentally determined calibration curves of both sensors. A characteristic feature arising from the comparison of calibration curves is the similar level of Au and Ag–Au biosensors’ sensitivity in the linear range, where the signal of the AgAu sensor is at a level several times greater. It was shown that the influence of sensing surface morphology on the ∂n/∂c sensitivity component had to be incorporated to explain the features of calibration curves of sensors. The shape of the sensory surface relief was proposed to increase the sensor sensitivity at low analyte concentrations.