4 citations · 8 across the 4 of their papers we have counts for
4 papers
Discovering Novel Halide Perovskite Alloys using Multi-Fidelity Machine Learning and Genetic Algorithm
Jiaqi Yang, Panayotis Manganaris, Arun Mannodi-Kanakkithodi
Expanding the pool of stable halide perovskites with attractive optoelectronic properties is crucial to addressing current limitations in their performance as photovoltaic (PV) abs…
First Principles Investigation of Polymorphism in Halide Perovskites
Jiaqi Yang, Arun Mannodi-Kanakkithodi
Halide perovskites have been extensively studied as materials of interest for optoelectronic applications. There is a major emphasis on ways to tailor the stability, defect behavio…
Accelerating Defect Predictions in Semiconductors Using Graph Neural Networks
Md Habibur Rahman, Prince Gollapalli, Panayotis Manganaris +5
Here, we develop a framework for the prediction and screening of native defects and functional impurities in a chemical space of Group IV, III-V, and II-VI zinc blende (ZB) semicon…
A High-Throughput Computational Dataset of Halide Perovskite Alloys
Jiaqi Yang, Panayotis Manganaris, Arun Mannodi-Kanakkithodi
Novel halide perovskites with improved stability and optoelectronic properties can be designed via composition engineering at cation and/or anion sites. Data-driven methods, especi…