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Machine Learning Techniques for Photocatalysis and Materials Discovery

thesis
posted on 2024-02-28, 10:10 authored by VINKY CHOW
Material science and engineering research has long utilized the trial-and-error experimentation. However, the approach is costly and time-consuming. This thesis intends to introduce machine learning as an efficient tool in alleviating the burden associated with the conventional approaches in material science research. We first discuss how discriminative models can be incorporated to facilitate the photocatalysis process and reduce the experimental burden. We then present a generative model framework for inorganic material discovery with desired properties. Finally, we extend and enhance the generative model with improved loss function to enable more effective material generation.

History

Campus location

Malaysia

Principal supervisor

Raphael Phan

Additional supervisor 1

Dr Ganesh Krishnasamy

Additional supervisor 2

Prof Chai Siang Piao

Year of Award

2024

Department, School or Centre

School of Information Technology (Monash University Malaysia)

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Information Technology

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