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Electrical and Computer Engineering

South Dakota State University

Electronic Theses and Dissertations

Theses/Dissertations

2024

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Full-Text Articles in Engineering

Structural Construction And Surface Modification Of Copper Current Collectors For Lithium Metal Batteries, Yaohua Liang Jan 2024

Structural Construction And Surface Modification Of Copper Current Collectors For Lithium Metal Batteries, Yaohua Liang

Electronic Theses and Dissertations

Graphene, a prevalent anode material in commercial lithium-ion batteries, has reached its theoretical capacity limit. The imperative is to develop high-capacity anode materials to meet the growing demand for energy density. Lithium metal, renowned for its exceptionally high theoretical specific capacity density (3680 mAh g-1) and low reduction potential (-3.04 V, relative to the standard hydrogen electrode), is commonly dubbed the "Holy Grail" for negative electrode materials in high-energy-density batteries. However, practical advancements in lithium metal anodes face obstacles like low Coulombic efficiency, limited cycle life, and heightened reactivity to the electrolyte and internal short circuits resulting from lithium dendrite …


Optimizing Large Language Models And Multimodal Approaches For Biomedical Publication And Satellite Imagery, Youngsun Jang Jan 2024

Optimizing Large Language Models And Multimodal Approaches For Biomedical Publication And Satellite Imagery, Youngsun Jang

Electronic Theses and Dissertations

This dissertation comprises two main sections: the first focuses on natural language processing (NLP) for extracting key information from scientific literature using large language models (LLMs), and the second addresses remote sensing for detecting natural disasters, such as floods, from satellite imagery using a multimodal approach. The first section investigates methods to enhance Transformer-based models in classifying and extracting information from biomedical scientific publications. Key contributions include the development of a custom dataset for classification and Question and Answering (Q&A) tasks, fine-tuning Transformer models like the Bidirectional Encoder Representations from Transformers (BERT) and addressing multi-span answer issues with the TAg-based …