Subcategory: Materials Science
Room: Exhibit Hall
Jack Liu - Carnegie Mellon University
Co-Author(s): David Heson, Mississippi State University, Mississippi State, MSWilliam Robertson, Middle Tennessee State University, Murfreesboro, TN
The goal of our project is to build a computational platform to model and optimize the performance of Bloch surface wave sensors for biological and chemical applications.IntroductionBloch surface waves (BSWs) occur in an optical multilayer when resonance is achieved between an incident electromagnetic wave and a surface guided wave in the defect layer. BSWs are non-radiative and are only generated in a prism coupling arrangement at incident angles beyond the critical angle for total internal reflection. BSW generation is manifested as a dip from total reflection to near-zero reflection at certain resonant angles.The resonant angles are highly sensitive to the conditions at the surface. Placing material on the surface significantly alters the resonant angle, allowing for measurements of nanoscale biochemical processes such as antigen-antibody reactions. The overall goal of the project is to design multilayers that exhibit optimal BSW properties for biosensing applications.MethodsAll code was written in Python. The matrix method outlined in Ohta and Ishida was implemented to compute the coefficients of reflection and transmission as well as the electric field profile of arbitrary multilayers. Algorithms were created to explore various combinations of refractive indexes and layer widths. The code was executed on personal laptops and the Middle Tennessee State University Computer Science JupyterHub clusters.ResultsOptimization algorithms found multilayers exhibiting BSWs with sensitivities of 3.4 degrees per Refractive Index Unit (RIU), which is a slight improvement over older designs. A design with a sensitivity of 18.3 degrees per RIU was found, but its electric field profile was not indicative of a BSW, suggesting that the observed reflectivity dip is due to interference and not resonant coupling. The sensitivity per unit change in layer thickness was also measured, and the results were similar to the measures per RIU.ConclusionThe created algorithms are successful and efficient at identifying optimal multilayer designs for BSW sensing. Although the code was designed to explore BSW phenomena, it is more broadly applicable since it can calculate the reflection and transmission of any arbitrary multilayer, even those containing metals.The codebases were uploaded to Github, along with a user interface to utilize the tools. Future plans include packaging the code and uploading it to the Python Package Index, allowing other researchers to import the functionality into their own code. Multilayers with defect layers in different positions and different materials will be explored to determine if even more optimal designs are possible.
Funder Acknowledgement(s): This research was funded by the NSF REU Award #1757493.
Faculty Advisor: William Robertson, William.Robertson@mtsu.edu
Role: I created a Python implementation of the transfer matrix calculation described in the Ohta and Ishida paper. Using my implementation, I predicted the reflective properties of various optical multilayers, calculated their electric field profiles, and generated plots (2D and 3D) of calculated values. I created algorithms to identify the location of surface modes from reflectivity calculations and to optimize the design of multilayers for sensitivity and surface mode depth.