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Machine-learned interatomic potentials (MLIPs) show promise in accurately describing the physical properties of materials, but there is a need for a higher throughput method of validation. Here, we demonstrate using that MLIPs and molecular…

Materials Science · Physics 2023-03-07 Dennis S. Kim , Michael Xu , James M. LeBeau

Acid-base reactions are ubiquitous in nature. Understanding their mechanisms is crucial in many fields, from biochemistry to industrial catalysis. Unfortunately, experiments only give limited information without much insight into the…

Chemical Physics · Physics 2022-06-08 Emanuele Grifoni , GiovanniMaria Piccini , Michele Parrinello

We develop an efficient parallel multiscale method that bridges the atomistic and mesoscale regimes, from nanometer to micron and beyond, via concurrent coupling of atomistic simulation and mesoscopic dynamics. In particular, we combine an…

Computational Physics · Physics 2020-12-23 Yuying Wang , Zhen Li , Junbo Xu , Chao Yang , George Em Karniadakis

To support efforts on cooling and trapping of alkaline-earth atoms and designs of atomic clocks, we performed ab initio relativistic many-body calculations of electric-dipole transition amplitudes between low-lying states of Mg, Ca, and Sr.…

Atomic Physics · Physics 2009-11-07 S. G. Porsev , M. G. Kozlov , Yu. G. Rakhlina , A. Derevianko

Dynamics of flexible molecules are often determined by an interplay between local chemical bond fluctuations and conformational changes driven by long-range electrostatics and van der Waals interactions. This interplay between interactions…

Chemical Physics · Physics 2021-03-05 Valentin Vassilev-Galindo , Gregory Fonseca , Igor Poltavsky , Alexandre Tkatchenko

The study of cells' dynamical properties is essential to a better understanding of several physiological processes. These properties are directly associated with cells' mechanical parameters experimentally achieved through physical stress.…

Soft Condensed Matter · Physics 2022-01-26 G. Ourique , E. F. Teixeira , L. G. Brunnet

Materials composed of elements from the third and fifth columns of the periodic table display a very rich behavior, with the phase diagram usually containing a metallic liquid phase and a polar semiconducting solid. As a consequence, it is…

Materials Science · Physics 2022-01-13 Giulio imbalzano , Michele Ceriotti

The solid acids CsH$_2$PO$_4$ and Cs$_7$(H$_4$PO$_4$)(H$_2$PO$_4$)$_8$ pose significant challenges for the simulation of proton transport phenomena. In this work, we use the recently developed machine-learned force field (MLFF) MACE to…

Parametrizing energy functions for ionic systems can be challenging. Here, the total energy function for an eutectic system consisting of water, SCN$^-$, K$^+$ and acetamide is improved vis-a-vis experimentally measured properties. Given…

Chemical Physics · Physics 2024-10-25 Kai Töpfer , Eric Boittier , Michael Devereux , Andrea Pasti , Peter Hamm , Markus Meuwly

A tutorial introduction to the technique of Molecular Dynamics (MD) is given, and some characteristic examples of applications are described. The purpose and scope of these simulations and the relation to other simulation methods is…

Disordered Systems and Neural Networks · Physics 2009-11-10 Kurt Binder , Jurgen Horbach , Walter Kob , Wolfgang Paul , Fathollah Varnik

Hydrogen atom transfer (HAT) reactions are essential in many biological processes, such as radical migration in damaged proteins, but their mechanistic pathways remain incompletely understood. Simulating HAT is challenging due to the need…

Machine Learning · Computer Science 2025-11-25 Marlen Neubert , Patrick Reiser , Frauke Gräter , Pascal Friederich

A model of the three-dimensional rotating compressible Euler equations on the cubed sphere is presented. The model uses a mixed mimetic spectral element discretization which allows for the exact exchanges of kinetic, internal and potential…

Numerical Analysis · Mathematics 2020-12-01 D. Lee , A. Palha

Multi-component metal nanoparticles (NPs) are of paramount importance in the chemical industry, as most processes therein employ heterogeneous catalysts. While these multi-component systems have been shown to result in higher product…

The applicability of the three steps systematic parametrization procedure (3SSPP) to develop a force field for primary amines was evaluated in the present work. Previous simulations of primary amines show that current force fields (FF) can…

Soft Condensed Matter · Physics 2023-05-26 H. Espinosa-Jiménez , A. B. Salazar-Arriaga , H. Dominguez

The mechanisms of physical and chemical interactions of low temperature plasmas with surfaces can be fruitfully explored using molecular dynamics (MD) simulations. MD simulations follow the detailed motion of sets of interacting atoms…

Computational Physics · Physics 2015-05-13 David B. Graves , Pascal Brault

A combination of first principle molecular dynamics (MD) simulations with a rate equation model (MD-RE approach) is presented to study the trapping and the scattering of rare gas atoms from metal surfaces. The temporal evolution of the atom…

Statistical Mechanics · Physics 2018-09-10 A Filinov , M Bonitz , D Loffhagen

We propose a new model suitable for a nonequilibrium molecular dynamics (MD) simulation of electrical conductors. The model consists of classical electrons and atoms. The atoms compose a lattice vibration system. The electrons are scattered…

Statistical Mechanics · Physics 2015-05-30 Fan Lee , Tatsuro Yuge , Akira Shimizu

Multi-particle collision dynamics (MPCD) is a mesoscopic simulation method to simulate fluid particle-like flows. MPCD has been widely used to simulate various problems in condensed matter. In this study, hydrostatic behavior of gas in the…

Computational Physics · Physics 2015-09-28 Asis Pattisahusiwa , Acep Purqon , Sparisoma Virid

Though offering unprecedented pathways to molecular dynamics (MD) simulations of technologically-relevant materials and conditions, machine-learning interatomic potentials (MLIPs) are typically trained for ``simple'' materials and…

Materials Science · Physics 2025-07-09 Nikola Koutná , Shuyao Lin , Lars Hultman , Davide G. Sangiovanni , Paul H. Mayrhofer

We compare the predicted phase behaviour of lead (Pb) using three different interatomic potential models, including an embedded atom method (EAM), a modified embedded atom method (MEAM), and a neural network-based machine-learned model in…