17 citations · 19 across the 5 of their papers we have counts for
5 papers
Target-Distribution-Guided Cross-Functional Fine-Tuning of Machine-Learning Interatomic Potentials
Yuki Nagai, Bo Thomsen, Motoyuki Shiga
Cross-functional fine-tuning of machine-learning interatomic potentials (MLIPs) is often treated as a relabeling problem, where configurations generated at one density-functional l…
Computation of the heat capacity of water from first principles
Motoyuki Shiga, Jan Elsner, Jörg Behler +1
Water is a unique solvent with many remarkable properties. An example is its exceptionally high heat capacity, which plays an important role in storing and transporting thermal ene…
Self-learning path integral hybrid Monte Carlo with mixed ab initio and machine learning potentials for modeling nuclear quantum effects in water
Bo Thomsen, Yuki Nagai, Keita Kobayashi +2
The introduction of machine learned potentials (MLPs) has greatly expanded the space available for studying Nuclear Quantum Effects computationally with ab initio path integral (PI…
Inelastic Neutron Scattering of Hydrogen in Palladium Studied by Semiclassical Dynamics
Motoyuki Shiga, Bo Thomsen, Hajime Kimizuka
Inelastic neutron scattering (INS) spectra of hydrogen in face-centered cubic palladium have been calculated considering nuclear quantum effects (NQE) at finite temperatures. The c…
Nuclear Quantum Effects on Autoionization of Water Isotopologues Studied by Ab Initio Path Integral Molecular Dynamics
Bo Thomsen, Motoyuki Shiga
In this study we investigate the nuclear quantum effects (NQEs) on the acidity constant (pKA) of liquid water isotopologues at the ambient condition by path integral molecular dyna…