538 citations · 1.2k across the 13 of their papers we have counts for
9 papers · 1 filter
Best of Both Worlds: Enforcing Detailed Balance in Machine Learning Models of Transition Rates
Anjana Anu Talapatra, Anup Pandey, Matthew S. Wilson +4
The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation…
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…
Machine learning in nuclear materials research
Dane Morgan, Ghanshyam Pilania, Adrien Couet +3
Nuclear materials are often demanded to function for extended time in extreme environments, including high radiation fluxes and transmutation, high temperature and temperature grad…
Bioplastic Design using Multitask Deep Neural Networks
Christopher Kuenneth, Jessica Lalonde, Babetta L. Marrone +3
Non-degradable plastic waste stays for decades on land and in water, jeopardizing our environment; yet our modern lifestyle and current technologies are impossible to sustain witho…
Tuning magnetic and optical properties through strain in epitaxial LaCrO3 thin films
Yogesh Sharma, Binod Paudel, Jegon Lee +7
We report on the effect of epitaxial strain on magnetic and optical properties of perovskite LaCrO3 (LCO) single crystal thin films. Epitaxial LCO thin films are grown by pulsed la…
The Joint Automated Repository for Various Integrated Simulations (JARVIS) for data-driven materials design
Kamal Choudhary, Kevin F. Garrity, Andrew C. E. Reid +25
The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional the…
Efficient Computational Design of 2D van der Waals Heterostructures: Band-Alignment, Lattice-Mismatch, Web-app Generation and Machine-learning
Kamal Choudhary, Kevin F Garrity, Steven T. Hartman +2
We develop a computational database, web-apps, and machine-learning (ML) models to accelerate the design and discovery of two-dimensional (2D)-heterostructures. Using density funct…
Machine Learning and Materials Informatics: Recent Applications and Prospects
Rampi Ramprasad, Rohit Batra, Ghanshyam Pilania +2
Propelled partly by the Materials Genome Initiative, and partly by the algorithmic developments and the resounding successes of data-driven efforts in other domains, informatics st…
Using machine learning to identify factors that govern amorphization of irradiated pyrochlores
Ghanshyam Pilania, Karl R. Whittle, Chao Jiang +4
Structure-property relationships is a key materials science concept that enables the design of new materials. In the case of materials for application in radiation environments, co…