Structure-Property Relationships in Organic Field-Effect Transistors
The next installment of FLAMEL's Chalk and Talk series will feature Christopher Shartrand, a first-year FLAMEL trainee with a lecture entitled, "Structure-Property Relationships in Organic Field-Effect Transistors."
The talk will be held in Room 102, Pettit/MiRC.
Organic Field-Effect Transistors are a common device used in modern day development of organic electronics. Until recently, most research regarding OFETs has been focused on developing novel process techniques while improvement in the desired property mobility has remained stagnant. The problem now is to develop a statistical methodology that focuses on this fact.
This talk will detail the initial steps in the development of the methodology. It will contain an in-depth discussion on physically justified features for data reduction, an outline of the difficulties of regression modeling in a small response environment, and the possible ways that relevant research outside of our process design can be used to deal with these issues.
Chris is a first year PhD student in the School of Industrial and Systems Engineering. He received a B.S. degree in Applied Mathematics from the State University of New York at Fredonia. Before Georgia Tech he had the opportunity to participate in two unique internships and a REU over a diversified field of disciplines. He has worked as a Demographic Data Analyst for Pitney Bowes Corporation and as an Radiological Emergency Planner for the New York State Office of Emergency Management. Additionally during his REU, he conducted research involving CD4+ T-cells at the Virginia Bioinformatics Institute at Virginia Tech.
Chris is currently involved in research under the advisement of Drs. J-C Lu, Martha Grover, and Elsa Reichmanis. He is attempting to aid in the development of a scientific data-synthesis engine for unifying available big-data embedded in theoretical models, model simulations and past experiments. The process will aid toward designing new experiments that shore up potential knowledge gaps. From there the goal is to create a learning process that can investigate areas that have larger trust uncertainty.