On the Role of Long-Range Electrostatics in Machine-Learned Interatomic Potentials for Complex Battery Materials
Staacke, Carsten G, Heenen, Hendrik H, Scheurer, Christoph, Csányi, Gábor, Reuter, Karsten, Margraf, Johannes T
Published in ACS applied energy materials (22.11.2021)
Published in ACS applied energy materials (22.11.2021)
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Journal Article
Kernel charge equilibration: efficient and accurate prediction of molecular dipole moments with a machine-learning enhanced electron density model
Staacke, Carsten G, Wengert, Simon, Kunkel, Christian, Csányi, Gábor, Reuter, Karsten, Margraf, Johannes T
Published in Machine learning: science and technology (01.03.2022)
Published in Machine learning: science and technology (01.03.2022)
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Journal Article
Tackling Structural Complexity in Li[sub.2]S-P[sub.2]S[sub.5] Solid-State Electrolytes Using Machine Learning Potentials
Staacke, Carsten G, Huss, Tabea, Margraf, Johannes T, Reuter, Karsten, Scheurer, Christoph
Published in Nanomaterials (Basel, Switzerland) (01.08.2022)
Published in Nanomaterials (Basel, Switzerland) (01.08.2022)
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Journal Article
Data-efficient iterative training of Gaussian approximation potentials: Application to surface structure determination of rutile IrO 2 and RuO 2
Timmermann, Jakob, Lee, Yonghyuk, Staacke, Carsten G, Margraf, Johannes T, Scheurer, Christoph, Reuter, Karsten
Published in The Journal of chemical physics (28.12.2021)
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Published in The Journal of chemical physics (28.12.2021)
Journal Article