Theiss Research

Recent advances and applications of deep learning methods in materials science

Kamal Choudhary, Brian DeCost, Chi Chen et al. · npj Computational Materials · 2022 · 961 citations · Full text

Atomistic Line Graph Neural Network for improved materials property predictions

Kamal Choudhary, Brian DeCost · npj Computational Materials · 2021 · 614 citations · Full text

Electric-field induced structural transition in vertical MoTe2- and Mo1–xWxTe2-based resistive memories

Feng Zhang, H. R. Zhang, Sergiy Krylyuk et al. · Nature Materials · 2018 · 445 citations

Materials Science, Engineering, Emerging Memory Technology +7

The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design

npj Computational Materials · 2020 · 436 citations · Full text

Integrated Infrastructure, Engineering, Machine Learning +31

Application of finite element, phase-field, and CALPHAD-based methods to additive manufacturing of Ni-based superalloys

Trevor Keller, Greta Lindwall, Supriyo Ghosh et al. · Acta Materialia · 2017 · 418 citations · Full text

Materials Science, Materials Engineering, Metal Processing +10