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Related papers: Interatomic potentials from first-principles calcu…

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The superposition of atomic potentials (SAP) approach has recently been shown to be a simple and efficient way to initialize electronic structure calculations [S. Lehtola, J. Chem. Theory Comput. 15, 1593 (2019)]. Here, we study the…

Computational Physics · Physics 2020-04-13 Susi Lehtola , Lucas Visscher , Eberhard Engel

In the last few years, much efforts have gone into developing universal machine-learning potentials able to describe interactions for a wide range of structures and phases. Yet, as attention turns to more complex materials including alloys,…

Materials Science · Physics 2023-06-23 Eugène Sanscartier , Félix Saint-Denis , Karl-Étienne Bolduc , Normand Mousseau

We present an investigation into data selection methods for the efficient sampling of configuration space as applied to the development of inter-atomic potentials for scale bridging in molecular dynamics (MD) simulations. This investigation…

Computational Physics · Physics 2021-08-04 Jan Finkbeiner , Samuel Tovey , Christian Holm

We introduce a new class of machine learning interatomic potentials - fast General Two- and Three-body Potential (GTTP), which is as fast as conventional empirical potentials and require computational time that remains constant with…

Computational Physics · Physics 2023-01-03 Sergey Pozdnyakov , Artem R. Oganov , Efim Mazhnik , Arslan Mazitov , Ivan Kruglov

This work demonstrates that fine-tuning transforms foundational machine-learned interatomic potentials (MLIPs) to achieve consistent, near-ab initio accuracy across diverse architectures. Benchmarking five leading MLIP frameworks (MACE,…

Chemical Physics · Physics 2025-11-10 Jonas Hänseroth , Aaron Flötotto , Muhammad Nawaz Qaisrani , Christian Dreßler

Gaussian Process Regression-based Gaussian Approximation Potential has been used to develop machine-learned interatomic potentials having density-functional accuracy for free sodium clusters. The training data was generated from a large…

Atomic and Molecular Clusters · Physics 2023-09-19 Balasaheb J. Nagare , Sajeev Chacko , Dilip. G. Kanhere

Machine learning (ML) approaches enable large-scale atomistic simulations with near-quantum-mechanical accuracy. With the growing availability of these methods there arises a need for careful validation, particularly for physically agnostic…

Chemical Physics · Physics 2023-06-06 Joe D. Morrow , John L. A. Gardner , Volker L. Deringer

Accurate structural relaxation is critical for advanced materials design. Traditional approaches built on physics-derived first-principles calculations are computationally expensive, motivating the creation of machine-learning interatomic…

New interatomic potentials describing defects, plasticity and high temperature phase transitions for Ti are presented. Fitting the martensitic hcp-bcc phase transformation temperature requires an efficient and accurate method to determine…

Materials Science · Physics 2016-12-12 M. I. Mendelev , T. L. Underwood , G. J. Ackland

Long-range forces up to next-to-leading order are computed in the framework of the Einstein-Maxwell-dilaton system by means of a semiclassical approach to gravity. As has been recently shown, this approach is effective if one of the masses…

General Relativity and Quantum Cosmology · Physics 2012-03-30 Nahomi Kan , Kiyoshi Shiraishi

Recent advances regarding the interplay between ab initio calculations and metrology are reviewed, with particular emphasis on gas-based techniques used for temperature and pressure measurements. Since roughly 2010, several thermophysical…

This paper addresses the problem of consistent energy-based coupling of atomistic and continuum models of materials, limited to zero-temperature statics of simple crystals. It has been widely recognized that the most practical coupled…

Numerical Analysis · Mathematics 2011-08-09 Alexander V. Shapeev

Machine-learned interatomic potentials are revolutionising atomistic materials simulations by providing accurate and scalable predictions within the scope covered by the training data. However, generation of an accurate and robust training…

Materials Science · Physics 2025-07-30 Mariia Radova , Wojciech G. Stark , Connor S. Allen , Reinhard J. Maurer , Albert P. Bartók

Machine-learned interatomic potentials hold the promise to enable the modeling of highly concentrated liquids over meaningful timescales, far from reach for current ab initio electronic structure methods. Here we evaluate the performances…

Chemical Physics · Physics 2026-03-24 Luca Brugnoli , Mathieu Salanne , A. Marco Saitta , Alessandra Serva , Arthur France-Lanord

Reactive force fields for molecular dynamics have enabled a wide range of studies in numerous material classes. These force fields are computationally inexpensive as compared to electronic structure calculations and allow for simulations of…

Materials Science · Physics 2023-04-26 Brenden W. Hamilton , Pilsun Yoo , Michael N. Sakano , Md Mahbubul Islam , Alejandro Strachan

We present a new optimization-based method for atomistic-to-continuum (AtC) coupling. The main idea is to cast the coupling of the atomistic and continuum models as a constrained optimization problem with virtual Dirichlet controls on the…

Numerical Analysis · Mathematics 2013-04-19 Derek Olson , Pavel Bochev , Mitchell Luskin , Alexander V. Shapeev

Atomistic simulations provide insights into structure-property relations on an atomic size and length scale, that are complementary to the macroscopic observables that can be obtained from experiments. Quantitative predictions, however, are…

Materials Science · Physics 2021-04-14 Nataliya Lopanitsyna , Chiheb Ben Mahmoud , Michele Ceriotti

We have developed a multi-objective optimization (MOO) procedure to construct modified-embedded-atom-method (MEAM) potentials with minimal manual fitting. This procedure has been applied successfully to develop a new MEAM potential for…

In this study, an efficient first-principles approach for calculating the thermodynamic properties of mixed metal oxides at high temperatures is demonstrated. More precisely, this procedure combines density functional theory and harmonic…

Materials Science · Physics 2023-05-12 Joakim Brorsson , Ivana Staničić , Jonatan Gastaldi , Tobias Mattison , Anders Hellman

The coefficients of interatomic potential of simple form Exp-6 for neon are obtained. Repulsive part is calculated ab-initio in the Hartree-Fock approximation using the basis of atomic orbitals orthogonalized exactly on different lattice…

Chemical Physics · Physics 2007-05-23 Yu. V. Eremeichenkova , L. S. Metlov , A. F. Morozov
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