"Automated Materials Spectroscopy and Topology Optimizations Using Gene" by Miu Lun Lau

Publication Date

12-2023

Date of Final Oral Examination (Defense)

September 2023

Type of Culminating Activity

Dissertation

Degree Title

Doctor of Philosophy in Computing

Department Filter

Computer Science

Department

Computer Science

Supervisory Committee Chair

Min Long, Ph.D.

Supervisory Committee Member

Michal Kopera, Ph.D.

Supervisory Committee Member

Edoardo Serra, Ph.D.

Abstract

This dissertation will focus on the implementation and development of genetic algorithm software for increasing the productivity and analysis rate for spectrum analysis, topology optimization, and others. The software artifacts generated have resulted in a basic software framework called Neo. The framework has been further developed into different software for specific spectra methods such as EXAFS, Astrophysics, Nano-Indentation, and many more.

For GA implementation that relates to EXAFS, we have demonstrated the usage of GA to correctly identify chemical species presented, for Copper metal species, Technetium compounds, and in-situ of SnS2 batteries. The software artifact was able to generate accurate and physically reasonable EXAFS fittings that rapidly accelerate the analysis process.

For the Nano-indentation, our software also demonstrates better fits for graphite-related material compared to conventional LSF fits. Additionally, our software has the ability to rapidly analyze a large amount of indentation mapping, as shown in High Entropy Alloy (HEA) results.

For the heat exchanger optimization, we demonstrate the ability to optimize the shape of the heat exchanger based on the design parameter and the underlying physics-informed model. The model is supplemented by adsorption parameters calculated in molecular dynamics.

DOI

https://doi.org/10.18122/td.2177.boisestate

Share

COinS