Predictive model of PDP oxidation reaction with machine learning approach

A new machine learning based model, predicting reactive site of substrate using PDP catalyst, was under construction. My job was to generate computation data using DFT methods. One set of features the model would use was computational data generated by Gaussian. The new model took NPA charges, IR frequency, and calculated NMR data as input. Each descriptor also directly reflected the fundamental chemical property of the substrate. This new model could potentially empower the synthesis planning for pharmaceutical industry. The text would discuss the operation process, the use of each major descriptor, and the substrate set.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Chemistry

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2023

Author dc:creator

• Zhang, Minxing

Contributors dc:contributor

• White, Christina

• Organic Chemistry
• Computational Chemistry
• Machine Learning

Statement dc:rights

• Copyright 2023 Minxing Zhang

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/121958

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F121958