Accelerating Chemical Understanding
One of the difficulties in chemistry research comes from bridging the gap between the data collected by experimental chemists and the computational data analysis done by theoretical chemists. There can be a significant disparity of knowledge between the two branches of chemistry, which can hinder the progress of research and education on both sides. Furthermore, understanding the results of the chemical data can be a daunting task for newcomers to chemistry research. My intention is to bridge this gap by developing a computational framework that gives easily understandable statements on the fundamentals of materials and molecules and their corresponding X-ray spectral fingerprints. These statements will be based on the output of electronic structure and spectral calculations from Density Functional Theory (DFT) from data calculated in the Prendergast Group. The framework can then be generalized to many areas of chemistry research, particularly topics that are energy-relevant, such as catalysis, electrochemistry (e.g., batteries), and various examples of chemical conversion. In building a program designed to take inputs from computed chemical data and give outputs as a set of readable scientific statements (such as the properties of a molecule), I will be able to translate the computational results into scientific language and promote an increase in scientific communication within the field of chemistry and for those newly interested in learning about the results.
Message to Sponsor
- Major: Chemistry
- Sponsor: Rose Hills Foundation
- Mentor: David Prendergas, Ana Sanz Matias