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High-entropy alloys have attracted attention for their exceptional mechanical properties and thermal stability. However, the combinatorial explosion in the number of possible elemental compositions renders traditional trial-and-error…

Materials Science · Physics 2025-04-30 Ryo Murakami , Seiji Miura , Akihiro Endo , Satoshi Minamoto

Predicting the melting temperature (Tm) of multi-component and high-entropy alloys (HEAs) is critical for high-temperature applications but computationally expensive using traditional CALPHAD or DFT methods. In this work, we develop a…

Materials Science · Physics 2026-01-08 Mohd Hasnain

This study introduces a language transformer-based machine learning model to predict key mechanical properties of high-entropy alloys (HEAs), addressing the challenges due to their complex, multi-principal element compositions and limited…

Computational Engineering, Finance, and Science · Computer Science 2024-11-08 Spyros Kamnis , Konstantinos Delibasis

Active learning (AL) is a powerful sequential optimization approach that has shown great promise in the discovery of new materials. However, a major challenge remains the acquisition of the initial data and the development of workflows to…

Materials Science · Physics 2024-11-22 Mohnish Harwani , Juan C. Verduzco , Brian H. Lee , Alejandro Strachan

High entropy alloys (HEA) represent a class of materials with promising properties, such as high strength and ductility, radiation damage tolerance, etc. At the same time, a combinatorially large variety of compositions and a complex…

Materials Science · Physics 2025-10-03 Franco Moitzi , Lorenz Romaner , Andrei V. Ruban , Oleg E. Peil

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

The traditional design and development of metallic alloys has taken a hill-climbing approach to date, with incremental advances. Throughout the last century, aluminium (Al) alloy design has been essentially empirical and iterative, based on…

Materials Science · Physics 2021-06-02 J. Mangos , N. Birbilis

Addressing the uncertainty and variability in the quality of 3D printed metals can further the wide spread use of this technology. Process mapping for new alloys is crucial for determining optimal process parameters that consistently…

Materials Science · Physics 2024-01-02 David Guirguis , Conrad Tucker , Jack Beuth

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

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 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

Machine learning (ML) is shown to predict new alloys and their performances in a high dimensional, multiple-target-property design space that considers chemistry, multi-step processing routes, and characterization methodology variations. A…

Materials Science · Physics 2020-10-12 Sen Liu , Branden B. Kappes , Behnam Amin-ahmadi , Othmane Benafan , Xiaoli Zhang , Aaron P. Stebner

Thermodynamics is fundamental for understanding and synthesizing multi-component materials, while efficient and accurate prediction of it still remain urgent and challenging. As a demonstration of the "Divide and conquer" strategy…

Materials Science · Physics 2020-10-28 Pin-Wen Guan , Venkatasubramanian Viswanathan

High entropy alloys (HEAs) have been increasingly attractive as promising next-generation materials due to their various excellent properties. It's necessary to essentially characterize the degree of chemical ordering and identify…

Materials Science · Physics 2019-08-13 Jiaxin Zhang , Xianglin Liu , Sirui Bi , Junqi Yin , Guannan Zhang , Markus Eisenbach

High-entropy alloys are characterized by high configurational entropy. Since the discovery of high-entropy alloys (HEA) in 2004, entropy engineering has provided a promising direction for exploiting composition, lattice disorder, band…

Materials Science · Physics 2019-11-12 S. Joseph Poon , Jian He

Accelerating the design of materials with targeted properties is one of the key materials informatics tasks. The most common approach takes a data-driven motivation, where the underlying knowledge is incorporated in the form of…

Materials Science · Physics 2022-09-28 Shunshun Liu , Kyungtae Lee , Prasanna V. Balachandran

Traditional automated crash analysis systems heavily rely on static statistical models and historical data, requiring significant manual interpretation and lacking real-time predictive capabilities. This research presents an innovative…

Machine Learning · Computer Science 2025-02-11 Karthik Sivakoti

High-entropy alloys (HEAs) are metallic materials with solid solutions stabilized by high mixing entropy. Some exhibit excellent strength, often accompanied by additional properties such as magnetic, invar, corrosion, or cryogenic response.…

Materials Science · Physics 2024-09-26 Anurag Bajpai , Ziyuan Rao , Abhinav Dixit , Krishanu Biswas , Dierk Raabe

The development of oxidation-resistant high-entropy alloy (HEA) bond coats is restricted by the limited understanding of how multi-principal element interactions govern scale formation across temperatures. This study uncovers new oxidation…

Materials Science · Physics 2025-12-18 Dennis Boakye , Chuang Deng

A novel phenomenological framework for an efficient estimation of the thermo-electric properties at room temperature and elevated temperatures of body-centered cubic (BCC) transition metal concentrated alloys is proposed in this work. The…