Search Results for author: Adam J. Biacchi

Found 3 papers, 2 papers with code

The Joint Automated Repository for Various Integrated Simulations (JARVIS) for data-driven materials design

2 code implementations3 Jul 2020 Kamal Choudhary, Kevin F. Garrity, Andrew C. E. Reid, Brian DeCost, Adam J. Biacchi, Angela R. Hight Walker, Zachary Trautt, Jason Hattrick-Simpers, A. Gilad Kusne, Andrea Centrone, Albert Davydov, Jie Jiang, Ruth Pachter, Gowoon Cheon, Evan Reed, Ankit Agrawal, Xiaofeng Qian, Vinit Sharma, Houlong Zhuang, Sergei V. Kalinin, Bobby G. Sumpter, Ghanshyam Pilania, Pinar Acar, Subhasish Mandal, Kristjan Haule, David Vanderbilt, Karin Rabe, Francesca Tavazza

The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques.

Materials Science Computational Physics

High-throughput Density Functional Perturbation Theory and Machine Learning Predictions of Infrared, Piezoelectric and Dielectric Responses

no code implementations2 Oct 2019 Kamal Choudhary, Kevin F. Garrity, Vinit Sharma, Adam J. Biacchi, Angela R. Hight Walker, Francesca Tavazza

Many technological applications depend on the response of materials to electric fields, but available databases of such responses are limited.

Materials Science

Assessment of Vacancy Formation and Surface Energies of Materials using Classical Force-Fields

1 code implementation3 Apr 2018 Kamal Choudhary, Adam J. Biacchi, Supriyo Ghosh, Lucas Hale, Angela R. Hight Walker, Francesca Tavazza

Using some of the example cases, we show how our data can be used to directly compare different FFs for a material and to interpret experimental findings such as using Wulff construction for predicting equilibrium shape of nanoparticles.

Materials Science

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