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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

We investigate the mass fractions and in-medium properties of heavy nuclei in stellar matter at characteristic densities and temperatures for supernova (SN) explosions. The individual nuclei are described within the compressible liquid-drop…

Nuclear Theory · Physics 2017-03-21 Shun Furusawa , Igor Mishustin

In materials science, point defects play a crucial role in materials properties. This is particularly well known for the wide band gap insulators where the defect formation/compensation determines the equilibrium Fermi level and generally…

Materials Science · Physics 2023-11-29 Harshan Reddy Gopidi , Lovelesh Vashist , Oleksandr I. Malyi

Finding Minimum Energy Configurations (MECs) is essential in fields such as physics, chemistry, and materials science, as they represent the most stable states of the systems. In particular, identifying such MECs in multi-component alloys…

Materials Science · Physics 2025-01-27 Md Rajib Khan Musa , Yichen Qian , Jie Peng , David Cereceda

Impurity diffusion coefficients are entirely obtained from a low cost classical molecular statics technique (CMST). In particular, we show how the CMST is appropriate in order to describe the impurity diffusion behavior mediated by a…

Materials Science · Physics 2013-11-06 Viviana P. Ramunni

We present a novel deep learning (DL) approach to produce highly accurate predictions of macroscopic physical properties of solid solution binary alloys and magnetic systems. The major idea is to make use of the correlations between…

Computational Physics · Physics 2021-01-29 Massimiliano Lupo Pasini , Ying Wai Li , Junqi Yin , Jiaxin Zhang , Kipton Barros , Markus Eisenbach

We introduce an interpretable deep learning framework that predicts the cohesive energy of transition-metal alloys (TMAs) by embedding cohesion theory within graph neural networks (GNNs). Beyond accurate prediction of cohesive energy, a key…

Materials Science · Physics 2025-09-11 Yang Huang , Shih-Han Wang , Shuyi Cao , Luke E. K. Achenie , Hongliang Xin

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

Vacancy mechanism plays a dominant role in the atomic migration when a close-packed disordered alloy undergoes ordering transition. However, the calculation of thermal vacancy formation energies (VFEs) of random solid solutions is usually…

Materials Science · Physics 2017-02-13 H. B. Luo , Q. M. Hu , J. Du , A. R. Yan , J. P. Liu

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 geometry of thermodynamic state space is studied for asymptotically anti-de Sitter black holes in D-dimensional space times. Convexity of thermodynamic potentials and the analytic structure of the response functions is analysed. The…

General Relativity and Quantum Cosmology · Physics 2015-08-19 Brian P. Dolan

The vastness of the space of possible multicomponent metal alloys is hoped to provide improved structural materials but also challenges traditional, low-throughput materials design efforts. Computational screening could narrow this search…

The generalized stacking fault energy is a key ingredient to mesoscale models of dislocations. Here we develop an approach to quantify the dependence of generalized stacking fault energies on the degree of chemical disorder in…

Materials Science · Physics 2020-01-22 Anirudh Raju Natarajan , Anton Van der Ven

Materials design has traditionally evolved through trial-error approaches, mainly due to the non-local relationship between microstructures and properties such as strength and toughness. We propose 'alloy informatics' as a machine learning…

Materials Science · Physics 2025-04-08 Dario Massa , Efthimios Kaxiras , Stefanos Papanikolaou

A combination of classical density-functional theory and thermodynamic perturbation theory is applied to a survey of finite-temperature trends in the relative stabilities of one-component crystals and quasicrystals interacting via effective…

Materials Science · Physics 2009-10-30 A. R. Denton , J. Hafner

I review recent results from numerical simulations on the structure and dynamics of the ISM, and attempt to put together a coherent dynamical scenario. In particular, I discuss results on 1) the spatial distribution of the gas components,…

Astrophysics · Physics 2007-05-23 Enrique Vazquez-Semadeni

Seismogenic plate boundaries are presumed to behave in a similar manner to a densely packed granular medium, where fault and blocks systems rapidly rearrange the distribution of forces within themselves, as particles do in slowly sheared…

We calculate properties like equilibrium lattice parameter, bulk modulus and monovacancy formation energy for nickel (Ni), iron (Fe) and chromium (Cr) using Kohn-Sham density functional theory (DFT). We compare relative performance of local…

Materials Science · Physics 2011-09-15 Prithwish Kumar Nandi , M. C. Valsakumar , Sharat Chandra , H. K. Sahu , C. S. Sundar

We present a systematic methodology for the accurate calculation of defect structures in supercells which we illustrate with a study of the neutral vacancy in silicon. This is a prototypical defect which has been studied extensively using…

Materials Science · Physics 2009-11-10 M. I. J. Probert , M. C. Payne

There has been considerable interest in chalcogenide alloys with high concentrations of native vacancies that lead to properties desirable for thermoelectric and phase-change materials. Recently, vacancy ordering has been identified as the…

Materials Science · Physics 2015-06-18 Najeb Abdul-Jabbar , Peter Ercius , Ronald Gronsky , Edith Bourret-Courchesne , Brian Wirth
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