Complexity to Clarity: Detecting, Identifying and Analysing Complex Materials Systems at the Molecular Level with Machine Learning

A thesis submitted in total fulfilment of the requirements of the degree of Doctor of Philosophy to the Centre for Materials and Surface Science, School of Computing, Engineering and Mathematical Sciences, La Trobe University, Victoria, Australia.

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Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.26181/29043281.v1
Primary Topic
Machine Learning in Materials Science
Type
article
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article

Complexity to Clarity: Detecting, Identifying and Analysing Complex Materials Systems at the Molecular Level with Machine Learning

Figshare
Machine Learning in Materials Science
article

Complexity to Clarity: Detecting, Identifying and Analysing Complex Materials Systems at the Molecular Level with Machine Learning

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Abstract

A thesis submitted in total fulfilment of the requirements of the degree of Doctor of Philosophy to the Centre for Materials and Surface Science, School of Computing, Engineering and Mathematical Sciences, La Trobe University, Victoria, Australia.

Figshare
La Trobe University (AU)
Openalex Percentile: Top 65%
Machine Learning in Materials Science
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Complexity to Clarity: Detecting, Identifying and Analysing Complex Materials Systems at the Molecular Level with Machine Learning · Figshare (2025) | TGRS Research Map | TGRS