activity
20222026
most citedAccurate and efficient machine learning interatomic potentials for finite temperature modeling of molecular crystals

11 citations · 20 across the 10 of their papers we have counts for

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Showing cond-mat.mtrl-sciShow all

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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…

cond-mat.mtrl-sci20261 cited

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…

cond-mat.mtrl-sci2024

Nuclear quantum effects induce superionic proton transport in nanoconfined water

Pavan Ravindra, Xavier R. Advincula, Benjamin X. Shi +3

Recent work has suggested that nanoconfined water may exhibit superionic proton transport at lower temperatures and pressures than bulk water. Using first-principles-level simulati…

cond-mat.mtrl-sci20221 cited

Accurate and efficient structure factors in ultrasoft pseudopotential and projector augmented wave DFT

Benjamin X. Shi, Rebecca J. Nicholls, Jonathan R. Yates

Structure factors obtained from diffraction experiments are one of the most important quantities for characterizing the electronic and structural properties of materials. Methods f…

cond-mat.mtrl-sci2022

General embedded cluster protocol for accurate modeling of oxygen vacancies in metal-oxides

Benjamin Xu Shi, Venkat Kapil, Andrea Zen +3

The O vacancy (Ov) formation energy, , is an important property of a metal-oxide, governing its performance in applications such as fuel cells or heterogeneous catal…