From Virtual High-Throughput Screening and Machine Learning to the Discovery and Rational Design of Polymers for Optical Applications

This dissertation is concerned with the application of materials discovery framework developed in our group to discover high-refractive-index polymers. Development and application of the framework includes four key parts. In the first part, we present a method to accurately predict the refractive index (RI) of polymers using a combination of first-principles and data modeling. We validated the model with experimental RI values of polymers (Chapter 2). We further benchmark our results using different model chemistries to optimize the tradeoff between the accuracy and computation time (Chapter 3). The second part covers the development of a molecular library generator (ChemLG) and a virtual high-throughput screening (ChemHTPS) infrastructure. We demonstrate the applicability of these software suites by providing examples (Chapter 4). In the third part, we apply ChemLG and ChemHTPS to generate a library of polyimides and compute their RI values, respectively. Using the data generated in this work, we identify structure-property relationships via hypergeometric distribution analysis (Chapter 5). Finally, we present the application of machine learning to accelerate the process of property prediction. We construct efficient machine learning models to accurately predict the packing density, polarizability, and RI values of organic molecules and characterize them on a massive scale (Chapter 6).

Grantor dc:publisher

State University of New York at Buffalo

Year dc:date.issued

2018

Author dc:creator

• Afzal, Mohammad Atif; 0000-0001-8261-2024

Contributors dc:contributor

• Hachmann, Johannes
• Chemical and Biological Engineering

• computational chemistry
• molecular chemistry
• materials science

Statement dc:rights

• Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.
• Copyright retained by author.

Language dc:language

eng

Handle dc:identifier

http://hdl.handle.net/10477/77967

OAI record oai:identifier

https://ubir.buffalo.edu/oai/request?verb=GetRecord&metadataPrefix=qdc&identifier=oai%3Aubir.buffalo.edu%3A10477%2F77967