59 citations · 119 across the 11 of their papers we have counts for
12 papers
Bridging the Synthesizability Gap in Perovskites by Combining Computations, Literature Data, and PU Learning
Rushik Desai, Junyeong Ahn, Alejandro Strachan +1
Among emerging energy materials, halide and chalcogenide perovskites have garnered significant attention over the last decade owing to the abundance of their constituent species, l…
Exploring the defect landscape and dopability of chalcogenide perovskite BaZrS3
Rushik Desai, Shubhanshu Agarwal, Kiruba Catherine Vincent +3
BaZrS3 is a chalcogenide perovskite that has shown promise as a photovoltaic absorber, but its performance is limited because of defects and impurities that have a direct influence…
Square Moiré Superlattices in Twisted Two-Dimensional Halide Perovskites
Shuchen Zhang, Linrui Jin, Yuan Lu +21
Moiré superlattices have emerged as a new platform for studying strongly correlated quantum phenomena, but these systems have been largely limited to van der Waals layer two-dimens…
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…
JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design Methods
Kamal Choudhary, Daniel Wines, Kangming Li +35
Lack of rigorous reproducibility and validation are major hurdles for scientific development across many fields. Materials science in particular encompasses a variety of experiment…
Machine learning for impurity charge-state transition levels in semiconductors from elemental properties using multi-fidelity datasets
Maciej P. Polak, Ryan Jacobs, Arun Mannodi-Kanakkithodi +2
Quantifying charge-state transition energy levels of impurities in semiconductors is critical to understanding and engineering their optoelectronic properties for applications rang…
Data-Driven Design of Novel Halide Perovskite Alloys
Arun Mannodi-Kanakkithodi, Maria K. Y. Chan
The great tunability of the properties of halide perovskites presents new opportunities for optoelectronic applications as well as significant challenges associated with exploring…
Defect Physics of Pseudo-cubic Mixed Halide Lead Perovskites from First Principles
Arun Mannodi-Kanakkithodi, Ji-Sang Park, Alex B. F. Martinson +1
Owing to the increasing popularity of lead-based hybrid perovskites for photovoltaic (PV) applications, it is crucial to understand their defect physics and its influence on their…
Machine-learned impurity level prediction for semiconductors: the example of Cd-based chalcogenides
Arun Mannodi-Kanakkithodi, Michael Y. Toriyama, Fatih G. Sen +3
The ability to predict the likelihood of impurity incorporation and their electronic energy levels in semiconductors is crucial for controlling its conductivity, and thus the semic…
Phonon-pump electronic-probe study of methylammonium lead iodide reveals electronically decoupled organic and inorganic sublattices
Peijun Guo, Arun Mannodi-Kanakkithodi, Jue Gong +10
Organic-inorganic hybrid perovskites such as methylammonium lead iodide (CH3NH3PbI3) are game-changing semiconductors for solar cells and light-emitting devices owing to their exce…