15 citations · 30 across the 12 of their papers we have counts for
3 papers · 1 filter
Extracting Atomic Environments for Machine Learning Interatomic Potentials
Jared C. Stimac, Fei Zhou, Kyle Bushick +4
In order to appropriately capture large-scale material features and emergent phenomena via atomistic simulations, such as Molecular Dynamics (MD), the system scale can range up to…
Inverse design of bespoke interatomic potentials via active learning by information-matching
Yonatan Kurniawan, Logan D. Williams, Amit Samanta +6
Interatomic potentials (IPs) enable large-scale atomistic simulations beyond the reach of first-principles methods, but their predictive reliability depends critically on the selec…
Shake-up and shake-off spectra in the electron capture decay of atomic Be
Mauro Guerra, Inwook Kim, Stephan Friedrich +33
The most stringent laboratory-based experimental limits on the existence of sub-MeV sterile neutrinos are currently set by decay spectroscopy of radioactive Be embedded into su…