collaborators

12 papers

physics.chem-ph2026

How reproducible are first-principles simulations of liquid water?

Niamh ONeill, Benjamin X. Shi, William J. Baldwin +5

Liquid water is fundamentally important, and its accurate computer simulation has been the driving force for myriad methodological developments. Ab initio molecular dynamics with f…

physics.chem-ph2026

Assessing the impact of nodal surface optimization in fixed-node diffusion Monte Carlo on non-covalent interactions

Kousuke Nakano, Benjamin X. Shi, Dario Alfè +1

Diffusion quantum Monte Carlo (DMC) and coupled cluster theory [CCSD(T)] are widely-employed benchmark methods for noncovalent interactions (NCIs). However, recent studies have rep…

cond-mat.mtrl-sci2026

Practical and accurate density functionals for transition-metal heterogeneous catalysis

Benjamin X. Shi, Timothy C. Berkelbach

Density functional theory (DFT) underpins modern atomistic simulations of transition-metal surfaces. It can predict key properties linked to catalytic performance, such as adsorpti…

physics.chem-ph2026

From Accurate Quantum Chemistry to Converged Thermodynamics for Ion Pairing in Solution

Niamh O'Neill, Benjamin X. Shi, William C. Witt +6

Quantitative prediction of thermodynamic properties in solution is essential for translating atomistic simulations into reliable chemical insight. As an exemplar system, the behavi…

cond-mat.mtrl-sci2026

Efficient first-principles modeling of complex molecular crystals at sub-chemical accuracy

Benjamin X. Shi, Kristina M. Herman, Flaviano Della Pia +5

Molecules can form myriad crystalline polymorphs, each with distinct properties affecting their performance across diverse applications, from pharmaceuticals to functional material…

physics.chem-ph2026

MACE-POLAR-1: A Polarisable Electrostatic Foundation Model for Molecular Chemistry

Ilyes Batatia, William J. Baldwin, Domantas Kuryla +10

Accurate modelling of electrostatic interactions and charge transfer is fundamental to computational chemistry, yet most machine learning interatomic potentials (MLIPs) rely on loc…