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Benchmarking short-range machine learning potentials for atomistic simulations of metal/electrolyte interfaces2026 arXiv (Cornell University) preprint Materials Science Machine Learning in Materials Science Open access
Lucas B. T. de Kam, Jiaxin Zhu, Ankit Mathanker, Katharina Doblhoff-Dier, Nitish Govindarajan
4citations -
Accurate prediction of structural and mechanical properties on amorphous materials enabled through machine-learning potentials: a case study of silicon nitride2024 arXiv (Cornell University) preprint Materials Science Machine Learning in Materials Science Open access
Ganesh Kumar Nayak, Prashanth Srinivasan, Juraj Todt, Rostislav Daniel, Paolo Nicolini, David Holec
1citations -
SALTED: a symmetry-adapted machine-learning program for predicting electron-densities in molecules and materials2026 arXiv (Cornell University) preprint Materials Science Machine Learning in Materials Science Open access
Zekun Lou, Alan M. Lewis, T. Bernhard, Lukas Seifert, Agustín Salcedo, Florian Kleemiss, +2 more
0citations -
Stability of Binary Precipitates in Cu-Ni-Si-Cr Alloys Investigated Through Active Learning2023 SSRN Electronic Journal preprint Materials Science Machine Learning in Materials Science Open access
Ángel Díaz Carral, Xiang Xu, Simon Gravelle, Azade YazdanYar, Siegfried Schmauder, Maria Fyta
0citations -
Stability of Binary Precipitates in Cu-Ni-Si-Cr Alloys Investigated Through Active Learning2023 SSRN Electronic Journal preprint Materials Science Machine Learning in Materials Science Open access
Ángel Díaz Carral, Xiang Qun Xu, Simon Gravelle, Azade YazdanYar, Siegfried Schmauder, Maria Fyta
0citations -
Discovering electron transfer driven changes in chemical bonding in lead chalcogenides (PbX, where X = Te, Se, S, O)2020 arXiv (Cornell University) preprint Materials Science Crystal Structures and Properties Open access
Stefan Maier, Simon Steinberg, Yudong Cheng, Carl‐Friedrich Schön, Mathias Schumacher, Riccardo Mazzarello, +4 more
2citations
14 results