3 papers
cond-mat.mtrl-sci2024
Computational toolkit for predicting thickness of 2D materials using machine learning and autogenerated dataset by large language model
Chinedu Ekuma
The thickness of 2D materials not only plays a crucial role in determining the performance of nanoelectronic and optoelectronic devices but also introduces complexities in predicti…
cond-mat.mtrl-sci2024
Dynamic In-context Learning with Conversational Models for Data Extraction and Materials Property Prediction
Chinedu Ekuma
The advent of natural language processing and large language models (LLMs) has revolutionized the extraction of data from unstructured scholarly papers. However, ensuring data trus…
cond-mat.str-el2018
Two-particle excitations under coexisting electron interaction and disorder
C. E. Ekuma
We study the combined impact of random disorder and electron-electron, and electron-hole interactions on the absorption spectra of a three-dimensional Hubbard Hamiltonian. We deter…