[HTML][HTML] Universal machine learning framework for defect predictions in zinc blende semiconductors
A Mannodi-Kanakkithodi, X Xiang, L Jacoby, R Biegaj… - Patterns, 2022 - cell.com
We develop a framework powered by machine learning (ML) and high-throughput density
functional theory (DFT) computations for the prediction and screening of functional impurities …
functional theory (DFT) computations for the prediction and screening of functional impurities …
Defect Modeling and Device Optimization in Chalcogenide Photovoltaics from First Principles to AI-assisted Design
X Xiang - 2024 - search.proquest.com
This dissertation presents a comprehensive framework for defect modeling and device
optimization in chalcogenide photovoltaics, focusing on Cu (In, Ga) Se 2 (CIGS) and …
optimization in chalcogenide photovoltaics, focusing on Cu (In, Ga) Se 2 (CIGS) and …
Simulación y diseño de celdas solares basadas en semiconductores InxGa1-xN y Si
CE Pachón Pacheco - repositorio.unal.edu.co
En el presente trabajo se realiza un estudio computacional de celdas solares, utilizando
uniones In x Ga 1-x N-In x Ga 1-x N, heterouniones In x Ga 1-x N-Si y celdas tándem de dos …
uniones In x Ga 1-x N-In x Ga 1-x N, heterouniones In x Ga 1-x N-Si y celdas tándem de dos …