Author

T. Bernhard

2 papers indexed here

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Open access Aug 2026

Machine learning force field molecular dynamics simulation of SEI formation on lithium metal

Lithium metal batteries represent a cornerstone technology for next-generation energy storage systems owing to their exceptional energy density. However, the extreme reactivity of lithium metal drives continuous parasitic reactions with electrolytes, causing interfacial instability and dendritic growth that severely...

Norio Takenaka, Taiga Iwata, T. Bernhard et al. · npj Computational Materials · 2 citations

Preprint Sep 2026

SALTED: a symmetry-adapted machine-learning program for predicting electron-densities in molecules and materials

SALTED provides an open-source Python package for machine learning the quantum-mechanical electron density, $n(\mathbf{r})$, in molecular and condensed-phase systems based on input atomic coordinates and species. The program adopts a linear atom-centered decomposition of the electron density, which makes it highly tran...

Zekun Lou, Alan M. Lewis, T. Bernhard et al. · 0 citations