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Understanding the physical origin of deformation mechanisms in random alloys requires an understanding of their average behavior and, equally important, the role of local fluctuations around the average. Material properties of random alloys…

Computational Physics · Physics 2024-11-08 Max Hodapp

Active learning (AL) can drastically accelerate materials discovery; its power has been shown in various classes of materials and target properties. Prior efforts have used machine learning models for the optimal selection of physical…

Materials Science · Physics 2021-10-18 David E. Farache , Juan C. Verduzco , Zachary D. McClure , Saaketh Desai , Alejandro Strachan

Resolving the atomic-scale structure of defective high-entropy alloys (HEAs) containing interstitial species remains a major computational challenge due to the vast configurational space and the limitations of existing methods. Here we…

Materials Science · Physics 2026-03-11 Siya Zhu , Raymundo Arroyave

Electronic materials exhibiting phase transitions between metastable states (e.g., metal-insulator transition materials with abrupt electrical resistivity transformations) are challenging to decode. For these materials, conventional machine…

Materials Science · Physics 2020-11-09 Yiqun Wang , Akshay Iyer , Wei Chen , James M. Rondinelli

We devise a nonlocal correlation energy functional that describes the entire range of dispersion interactions in a seamless fashion using only the electron density as input. The new functional is considerably simpler than its predecessors…

Chemical Physics · Physics 2010-12-27 Oleg A. Vydrov , Troy Van Voorhis

Predicting relaxed atomic structures of chemically complex materials remains a major computational challenge, particularly for high-entropy systems where traditional first-principles methods become prohibitively expensive. We introduce the…

Disordered Systems and Neural Networks · Physics 2025-12-09 Neethu Mohan Mangalassery , Abhishek Kumar Singh

Recently, high entropy alloys (HEAs) have emerged as a new platform for discovering superconducting materials and offer avenues to explore exotic superconductivity. The highly disordered nature of HEA suggests regular phonon required for…

Superconductivity · Physics 2021-09-29 Kapil Motla , Arushi , P. K. Meena , D. Singh , P. K. Biswas , A. D. Hillier , R. P. Singh

Melting properties are critical for designing novel materials, especially for discovering high-performance, high-melting refractory materials. Experimental measurements of these properties are extremely challenging due to their high melting…

Materials Science · Physics 2024-08-19 Li-Fang Zhu , Fritz Koermann , Qing Chen , Malin Selleby , Joerg Neugebauer , and Blazej Grabowski

Superconducting high-entropy alloys (HEAs) are a newly burgeoning field of unconventional superconductors and raise intriguing questions about the presence of superconductivity in highly disordered systems, which lack regular phonon modes.…

Superconductivity · Physics 2023-05-16 K. Motla , Arushi , S. Jangid , P. Meena , R. K. Kushwaha , R. P. Singh

Superconducting high entropy alloy (HEA) are emerging as a new class of superconducting materials. It provides a unique opportunity to understand the complex interplay of disorder and superconductivity. We report the synthesis and detail…

Superconductivity · Physics 2022-04-13 Kapil Motla , Pavan Meena , Arushi , D. Singh , P. K. Biswas , A. D. Hillier , R. P. Singh

Hydrogen diffusion in metals and alloys plays an important role in the discovery of new materials for fuel cell and energy storage technology. While analytic models use hand-selected features that have clear physical ties to hydrogen…

Materials Science · Physics 2023-10-30 Grace M. Lu , Matthew Witman , Sapan Agarwal , Vitalie Stavila , Dallas R. Trinkle

We study layered systems and heterostructures of s-wave superconductors by means of a suitable generalization of Dynamical Mean-Field Theory. In order to reduce the computational effort, we consider an embedding scheme in which a relatively…

Strongly Correlated Electrons · Physics 2016-06-22 Francesco Petocchi , Massimo Capone

Refractory Complex Concentrated Alloys (RCCAs) can exhibit exceptional high-temperature strength, making such alloys promising candidates for high-temperature structural applications. However, current RCCAs do not possess the…

Materials Science · Physics 2025-11-04 Akhil Bejjipurapu , Alejandro Strachan , Kenneth H. Sandhage , Michael S. Titus

The reason behind the remarkable properties of High-Entropy Alloys (HEAs) is rooted in the diverse phases and the crystal structures they contain. In the realm of material informatics, employing machine learning (ML) techniques to classify…

Machine Learning · Computer Science 2024-01-02 Debsundar Dey , Suchandan Das , Anik Pal , Santanu Dey , Chandan Kumar Raul , Arghya Chatterjee

The design of corrosion-resistant high entropy alloys (CR-HEAs) is challenging due to the alloys' virtually astrological composition space. To facilitate this, efficient and reliable high-throughput exploratory approaches are needed. Toward…

Materials Science · Physics 2021-04-22 Thien Duong , Yafei Wang , Xiaoli Yan , Adrien Couet , Santanu Chaudhuri

Refractory high-entropy alloys are under consideration for applications where materials are subjected to high temperatures and levels of radiation, such as in the fusion power sector. However, at present, their scope is limited because they…

Materials Science · Physics 2024-04-09 Christopher D. Woodgate , Julie B. Staunton

Scanning transmission electron microscopy (STEM) is now the primary tool for exploring functional materials on the atomic level. Often, features of interest are highly localized in specific regions in the material, such as ferroelectric…

Materials Science · Physics 2021-08-11 Nicole Creange , Ondrej Dyck , Rama K. Vasudevan , Maxim Ziatdinov , Sergei V. Kalinin

In-situ Electron Energy Loss Spectroscopy (EELS) is an instrumental technique that has traditionally been used to understand how the choice of materials processing has the ability to change local structure and composition. However, more…

Accurate and efficient calculations of absorption spectra of molecules and materials are essential for the understanding and rational design of broad classes of systems. Solving the Bethe-Salpeter equation (BSE) for electron-hole pairs…

Materials Science · Physics 2021-02-18 Sijia S. Dong , Marco Govoni , Giulia Galli

A general method is presented for modeling high entropy alloys as ensembles of randomly sampled, ordered configurations on a given lattice. Statistical mechanics is applied post hoc to derive the ensemble properties as a function of…

Materials Science · Physics 2022-11-24 Andrew Novick , Quan Nguyen , Roman Garnett , Eric Toberer , Vladan Stevanović