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physics.chem-ph2026
Solvating machine-learning interatomic potentials for solution-phase chemistry
Anton Z. Ni, Joonho Lee
Most machine-learning interatomic potentials (MLIPs) are trained on gas-phase data, which limits their use for chemistry in solution. Here, we introduce AnySolv, a transferable imp…
physics.chem-ph2025
Efficient All-Electron Periodic Fourier-Transformed Coulomb Method
Hieu Q. Dinh, Adam Rettig, Xintian Feng +1
We present an efficient algorithm for the all-electron periodic Coulomb matrix based on the Ewald summation combined with the Fourier-transformed Coulomb method. The short-range co…
physics.chem-ph2025★ 7 cited
Gaussian-Based Periodic Grand Canonical Density Functional Theory with Implicit Solvation for Computational Electrochemistry
Anton Z. Ni, Adam Rettig, Joonho Lee
We present a numerical method for grand canonical density functional theory (DFT) tailored to solid-state systems, employing Gaussian-type orbitals as the primary basis. Our approa…