304 citations · 398 across the 14 of their papers we have counts for
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cond-mat.mtrl-sci2023★ 3 cited
Oxygen Vacancy Formation Energy in Metal Oxides: High Throughput Computational Studies and Machine Learning Predictions
Bianca Baldassarri, Jiangang He, Abhijith Gopakumar +5
The oxygen vacancy formation energy () governs defect dynamics and is a useful metric to perform materials selection for a variety of applications. However, density functi…
cond-mat.mtrl-sci2023★ 2 cited
Complexity of Many-Body Interactions in Transition Metals via Machine-Learned Force Fields from the TM23 Data Set
Cameron J. Owen, Steven B. Torrisi, Yu Xie +6
This work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases of d-block elements. In exhaustive detail, we co…