5 papers
Molecular augmented dynamics: Generating experimentally consistent atomistic structures by design
Tigany Zarrouk, Miguel A. Caro
A fundamental objective of materials modeling is identifying atomic structures that align with experimental observables. Conventional approaches for disordered materials involve sa…
Linear-scaling calculation of experimental observables for molecular augmented dynamics simulations
Tigany Zarrouk, Miguel A. Caro
Aligning theoretical atomistic structural models of materials with available experimental data presents a significant challenge for disordered systems. The configurational space to…
Unifying the description of hydrocarbons and hydrogenated carbon materials with a chemically reactive machine learning interatomic potential
Rina Ibragimova, Mikhail S. Kuklin, Tigany Zarrouk +1
We present a general-purpose machine learning (ML) interatomic potential for carbon and hydrogen which is capable of simulating various materials and molecules composed of these el…
Accelerated First-Principles Exploration of Structure and Reactivity in Graphene Oxide
Zakariya El-Machachi, Damyan Frantzov, A. Nijamudheen +3
Graphene oxide (GO) materials are widely studied, and yet their atomic-scale structures remain to be fully understood. Here we show that the chemical and configurational space of G…
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…