3.2k citations · 6k across the 17 of their papers we have counts for
21 papers
MuDirac 1.3.0: A Sustainable Software Tool for Calculating Ground State Nuclear Properties Using Muonic X-Ray Measurements
Leandro Liborio, Milan Kumar, Subindev Devadasan +4
The nuclear charge radius is one of the most fundamental quantities of the atomic nucleus. It can be deduced from a combination of experimental measurements of muonicX-raytransitio…
Autonomous thermodynamically informed database generation for machine-learned interatomic potentials and application to magnesium
Vincent G. Fletcher, Albert P. Bartók, Livia B. Pártay
We propose a novel approach for constructing training databases for Machine-Learned Interatomic Potential (MLIP) models, specifically designed to capture phase properties across a…
Experiment-driven atomistic materials modeling: A case study combining X-ray photoelectron spectroscopy and machine learning potentials to infer the structure of oxygen-rich amorphous carbon
Tigany Zarrouk, Rina Ibragimova, Albert P. Bartók +1
An important yet challenging aspect of atomistic materials modeling is reconciling experimental and computational results. Conventional approaches involve generating numerous confi…
Completeness of Atomic Structure Representations
Jigyasa Nigam, Sergey N. Pozdnyakov, Kevin K. Huguenin-Dumittan +1
In this paper, we address the challenge of obtaining a comprehensive and symmetric representation of point particle groups, such as atoms in a molecule, which is crucial in physics…
Insight into liquid polymorphism from the complex phase behaviour of a simple model
Albert P. Bartók, György Hantal, Livia B. Pártay
We systematically explored the phase behavior of the hard-core two-scale ramp model suggested by Jagla[E. A. Jagla, Phys. Rev. E 63, 061501 (2001)] using a combination of the neste…
Combining phonon accuracy with high transferability in Gaussian approximation potential models
Janine George, Geoffroy Hautier, Albert P. Bartók +2
Machine learning driven interatomic potentials, including Gaussian approximation potential (GAP) models, are emerging tools for atomistic simulations. Here, we address the methodol…