OP: High Order Perturbation of Surfaces Methods for Crossed Surface Plasmon Resonance Sensors: Simulation, Validation, and Design

<p>Surface Plasmon Resonance (SPR) sensors are a relatively new yet pervasive technology for measuring biological and chemical interactions. These devices respond to the change in the refractive index of a structure due to the occurrence of a biological or chemical reaction. Such a change modifies the behavior of surface waves at metal-dielectric interfaces within the structure, which are then measured to form the basis for thousands of highly sensitive and effective tests for not only chemical and biological species detection, but also medical diagnosis and environmental measuring. Indeed, a 2008 survey article (J. Homola, Surface plasmon resonance sensors for detection of chemical and biological species. Chemical Reviews, 108(2):462­493, 2008) lists SPR biosensors for Food Quality and Safety Analysis (62 listed), Medical Diagnostics (33 listed), and Environmental Monitoring (21 listed). In the decade since the appearance of this publication the list has grown substantially. This project shall advance the state of the art in the numerical simulation of these SPR sensors. The numerical simulation will be validated and verified through direct collaboration with experimentalists.</p>

<p>The algorithm of "High Order Perturbation of Surfaces" (HOPS) is optimal among the wide class of potential schemes for simulating solutions of the relevant model equations. Despite their advantageous properties for the problem at hand, the HOPS methods require further enhancements for their use by engineers. This research project aims to develop several improvements. First, the project will study extensions to the three dimensional, vectorial, multiply layered configurations of current interest. Second, the project will investigate the possibility of a joint expansion of the scattered fields in both boundary deformation and wavenumber. These latter developments will mandate new rigorous analysis (which this project will deliver) to determine their domain of applicability. Once these additions have been implemented and tested, these algorithms will be vaildated against the laboratory experimental results. After this, the project aims to create an optimization framework to design SPR sensors with enhanced sensing capabilities. This will involve the design of appropriate objective functions, followed by the efficient interfacing of the new forward solvers to state of the art minimization libraries.</p>