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Two new refractory amorphous high-entropy alloys (RAHEAs) within the W--Ta--Cr--V and W--Ta--Cr--V--Hf systems were herein synthesized using magnetron-sputtering and tested under high-temperature annealing and displacing irradiation using…

Materials Science · Physics 2023-03-27 Matheus A. Tunes , Hi T. Vo , Jon K. S. Baldwin , Tarik A. Saleh , Saryu J. Fensin , Osman El-Atwani

Compositionally complex alloys hold the promise of simultaneously attaining superior combinations of properties, such as corrosion resistance, light-weighting, and strength. Achieving this goal is a challenge due in part to a large number…

A hallmark of human intelligence is the ability to construct self-contained chunks of knowledge and reuse them in novel combinations for solving different problems. Learning such compositional structures has been a challenge for artificial…

Machine Learning · Computer Science 2022-07-26 Jorge A. Mendez

Predictive materials synthesis is the primary bottleneck in realizing new functional and quantum materials. Strategies for synthesis of promising materials are currently identified by time-consuming trial and error approaches and there are…

High entropy alloys (HEAs) are a series of novel materials that demonstrate many exceptional mechanical properties. To understand the origin of these attractive properties, it is important to investigate the thermodynamics and elucidate the…

Materials Science · Physics 2020-11-03 Xianglin Liu , Jiaxin Zhang , Junqi Yin , Sirui Bi , Markus Eisenbach , Yang Wang

High entropy alloys (HEA) show promise as a new type of high-performance structural material. Their vast degrees of freedom provide for extensive opportunities to design alloys with tailored properties. However, the compositional…

Disordered Systems and Neural Networks · Physics 2019-04-19 Qi Jie , Andrew Cheung , S. Joseph Poon

Superconductors have been among the most fascinating substances, as the fundamental concept of superconductivity as well as the correlation of critical temperature and superconductive materials have been the focus of extensive investigation…

Developing ductile refractory BCC alloys has remained a challenge. The intrinsic ductility (D) of an alloy is the ratio of surface energy ($\gamma_s$) and unstable stacking fault energy ($\gamma_{usfe}$). Lowering the valence electron…

Materials Science · Physics 2023-01-03 Sufyan M. Shaikh , B. S. Murty , Satyesh K. Yadav

A supervised machine learning (ML) based computational methodology for the design of particulate multifunctional composite materials with desired thermal conductivity (TC) is presented. The design variables are physical descriptors of the…

Computational Physics · Physics 2025-07-25 Mohammad Saber Hashemi , Masoud Safdari , Azadeh Sheidaei

In this study Mo-Nb-Ta-W refractory high-entropy alloys (R-HEAs) have been studied for their phase stability for a wide temperature range (100 K to 2000 K). The equilibrium thermodynamic phases are determined by the changes in enthalpy and…

Materials Science · Physics 2021-03-16 Varnita Bajpai , Soumyadipta Maiti , Shashank Mishra , Beena Rai

Recently, high-entropy alloys (HEAs) have attracted wide attention due to their extraordinary materials properties. A main challenge in identifying new HEAs is the lack of efficient approaches for exploring their huge compositional space.…

Materials Science · Physics 2019-05-07 Tatiana Kostiuchenko , Fritz Körmann , Jörg Neugebauer , Alexander Shapeev

Refractory high entropy alloys (RHEA) have been proven to have excellent mechanical properties with a potential use as protective thin films. However, the combination of high hardness with low friction and wear is a major challenge in the…

Materials Science · Physics 2021-12-03 Dawei Luo , Qing Zhou , Wenting Ye , Yue Ren , Christian Greiner , Yixuan He , Haifeng Wang

Machine Learning (ML) has offered innovative perspectives for accelerating the discovery of new functional materials, leveraging the increasing availability of material databases. Despite the promising advances, data-driven methods face…

Leveraging strong optoelectronic responses to external stimuli, such as temperature and electric fields, is central to the development of advanced photonic technologies, including adaptive photodetectors and reconfigurable photovoltaic…

Materials Science · Physics 2026-02-25 Pol Benítez , Cibrán López , Edgardo Saucedo , Claudio Cazorla

Tungsten exhibits exceptional temperature and radiation resistance, making it well-suited for applications in extreme environments such as nuclear fusion reactors. Additive manufacturing offers geometrical design freedom and rapid…

High entropy alloys (HEAs) are multicomponent compounds whose high configurational entropy allows them to solidify into a single phase, with a simple crystal lattice structure. Some HEA's exhibit desirable properties, such as high specific…

Materials Science · Physics 2017-06-29 Rui Feng , Peter K. Liaw , Michael C. Gao , Michael Widom

High-throughput methods enable accelerated discovery of novel materials in complex systems such as high-entropy alloys, which exhibit intricate phase stability across vast compositional spaces. Computational approaches, including Density…

Compositional verification algorithms are well-studied in the context of model checking. Properly selecting components for verification is important for efficiency, yet has received comparatively less attention. In this paper, we address…

Formal Languages and Automata Theory · Computer Science 2024-08-19 Ian Dardik , April Porter , Eunsuk Kang

The growing need for structural materials with strength, mechanical stability, and durability in extreme environments is driving the development of high entropy alloys. These are materials with near equiatomic mixing of five or more…

Materials Science · Physics 2025-09-18 Rahul Bouri , Manikantan R. Nair , Tribeni Roy

During powder production, the pre-alloyed powder composition often deviates from the target composition leading to undesirable properties of additive manufacturing (AM) components. Therefore, we developed a method to perform high-throughput…

Materials Science · Physics 2020-12-23 Xin Wang , Wei Xiong
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