(740h) Harnessing Virtual High-Throughput Screening and Machine Learning for the Discovery of Novel High Refractive Index Polymers
AIChE Annual Meeting
2017
2017 Annual Meeting
Materials Engineering and Sciences Division
Atomistic and Molecular Modeling and Simulation of Polymers
Thursday, November 2, 2017 - 5:15pm to 5:30pm
We present a computational study of novel high-RI polymer candidates proposed according to the guidelines discussed above. Various paths to introducing highly polarizable elements into carbon-based frameworks are being explored. We compute static polarizabilities at the density functional theory (DFT) level and benchmark the predictive performance of different model chemistries and computational protocols. We obtain RI values based on the Lorentz-Lorenz equation.
To accelerate the discovery process of next-generation high-RI materials, we employ a high-throughput screening, materials informatics, and data-driven rational design approach that we have been developing in the group. It is a powerful tool and has shown to be highly promising for rapidly identifying polymer candidates with exceptional RI values.