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We propose an approach to materials prediction that uses a machine-learning interatomic potential to approximate quantum-mechanical energies and an active learning algorithm for the automatic selection of an optimal training dataset. Our…

Materials Science · Physics 2018-06-28 Konstantin Gubaev , Evgeny V. Podryabinkin , Gus L. W. Hart , Alexander V. Shapeev

Machine-learning interatomic potentials are widely used as computationally efficient surrogates for density functional theory in atomistic simulations, enabling large-scale, long-time modeling of materials systems. We investigate how…

Materials Science · Physics 2026-04-13 Jonas Grandel , Philipp Benner , Janine George

Titanium and its alloys are technologically important materials that display a rich phase behaviour. In order to enable large-scale, realistic modelling of Ti and its alloys on the atomistic scale, Machine Learning Interatomic Potentials…

Materials Science · Physics 2025-01-13 Connor S. Allen , Albert P. Bartók

Multi-principal element alloys open large composition spaces for alloy development. The large compositional space necessitates rapid synthesis and characterization to identify promising materials, as well as predictive strategies for alloy…

The extension of the first-principles generalized pseudopotential theory (GPT) to transition-metal (TM) aluminides produces pair and many-body interactions that allow efficient calculations of total energies. In aluminum-rich systems…

Compositionally complex alloys or concentrated solid solutions are the latest frontier in catalyst design, but mixing different elements in one catalyst may result in surface segregation. Atomistic simulations can predict segregation…

Materials Science · Physics 2022-12-12 Alberto Ferrari , Vadim Sotskov , Alexander V. Shapeev , Fritz Körmann

Elastic description of planar quasicrystals can be formulated as an interplay between two Goldstone fields corresponding to phonon and phason degrees of freedom. We reformulate this description as a gauge theory with one gauge field that is…

Strongly Correlated Electrons · Physics 2021-08-12 Piotr Surówka

We present a comprehensive and user-friendly framework built upon the pyiron integrated development environment (IDE), enabling researchers to perform the entire Machine Learning Potential (MLP) development cycle consisting of (i) creating…

Machine learning interatomic potentials (MLIPs) offer an efficient and accurate framework for large-scale molecular dynamics (MD) simulations, effectively bridging the gap between classical force fields and \textit{ab initio} methods. In…

The optical properties of defects in solids produce rich physics, from gemstone coloration to single-photon emission for quantum networks. Essential to describing optical transitions is electron-phonon coupling, which can be predicted from…

Materials Science · Physics 2026-04-21 Mark E. Turiansky , John L. Lyons , Noam Bernstein

We present a systematic benchmark of MACE potentials for iron-nickel alloys, focusing on structural, elastic, magnetic, and finite-temperature properties relevant to phase stability. The reference dataset comprises spin-polarized PBE…

Materials Science · Physics 2026-05-28 Kushal Ramakrishna , Mani Lokamani , Attila Cangi

Ab initio linear-response calculations are reported of the phonon spectra and the electron-phonon interaction for several transition metal carbides and nitrides in a NaCl-type structure. For NbC, the kinetic, optical, and superconducting…

Superconductivity · Physics 2009-11-11 E. G. Maksimov , S. V. Ebert , M. V. Magnitskaya , A. E. Karakozov , S. Yu. Savrasov

The first-principles full-potential linearized augmented plane-wave method based on density functional theory is used to investigate electronic structure and magnetic properties of hypothetical binary compounds of I$^{A}$ subgroup elements…

Materials Science · Physics 2008-09-14 Krzysztof Zberecki , Leszek Adamowicz , Michał Wierzbicki

A multitude of observed boron-based materials have outstanding superconducting, mechanical, and refractory properties. Yet, the structure, the composition, and the very existence of some reported metal boride (M-B) compounds have been a…

Materials Science · Physics 2014-10-03 A. G. Van Der Geest , A. N. Kolmogorov

Following a resurgence of interest in dilute superconductivity in polar semiconductors, we perform a variational calculation to probe the existence of Fr{\"o}hlich bipolarons in these materials. Our solution is capable of interpolating…

Strongly Correlated Electrons · Physics 2021-11-25 L. Lin , P. B. Littlewood , A. Edelman

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

We provide a methodology for generating interatomic potentials for use in classical molecular dynamics simulations of atomistic phenomena occurring at energy scales ranging from lattice vibrations to crystal defects to high energy…

Materials Science · Physics 2009-12-03 Pratyush Tiwary , Axel van de Walle , Niels Grønbech-Jensen

We show that quantum correlations induced by electron-electron interactions in the presence of random impurity scattering can play an important role in the thermal stabilization of amorphous Hume-Rothery systems: When there is strong…

Materials Science · Physics 2009-10-31 Johann Kroha

Interatomic potentials approximate the potential energy of atoms as a function of their coordinates. Their main application is the effective simulation of many-atom systems. Here, we review empirical interatomic potentials designed to…

Materials Science · Physics 2022-11-11 Martin H. Muser , Sergey V. Sukhomlinov , Lars Pastewka

A novel embedded atom method (EAM) potential for the Xi-phases of Al-Pd-Mn has been determined with the force-matching method. Different combinations of analytic functions were tested for the pair and transfer part. The best results are…

Materials Science · Physics 2012-02-09 Daniel Schopf , Peter Brommer , Benjamin Frigan , Hans-Rainer Trebin
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