2 citations · 4 across the 3 of their papers we have counts for
Showing physics.comp-phShow all
2 papers · 1 filter
physics.comp-ph2025
Long-range electrostatics for machine learning interatomic potentials is easier than we thought
Dongjin Kim, Bingqing Cheng
The lack of long-range electrostatics is a key limitation of modern machine learning interatomic potentials (MLIPs), hindering reliable applications to interfaces, charge-transfer…
physics.comp-ph2024★ 2 cited
Learning charges and long-range interactions from energies and forces
Dongjin Kim, Daniel S. King, Peichen Zhong +1
Accurate modeling of long-range forces is critical in atomistic simulations, as they play a central role in determining the properties of materials and chemical systems. However, s…