English
Related papers

Related papers: Machine-Learning-Based Intelligent Framework for D…

200 papers

Refractory high-entropy alloys (RHEAs) are compositionally complex materials which have been demonstrated to have the potential for exceptional strength at high operating temperatures. However, their composition space is vast, and other…

Materials Science · Physics 2025-11-21 Stephen A. Giles , Hugh Shortt , Peter K. Liaw , Debasis Sengupta

Development of process-structure-property relationships in materials science is an important and challenging frontier which promises improved materials and reduced time and cost in production. Refractory high entropy alloys (RHEAs) are a…

Materials Science · Physics 2023-04-28 Stephen A. Giles , Hugh Shortt , Peter K. Liaw , Debasis Sengupta

Refractory high-entropy alloys can function at temperatures exceeding those of nickel-based superalloys. Aluminum, as an alloying element, contributes multiple advantageous characteristics to various high-temperature alloys. The Aluminum…

Materials Science · Physics 2025-03-28 M. Sreenidhi Iyengar , M. K Anirudh , P. H. Anantha Desik , M. P. Phaniraj

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

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

Machine learning is becoming a powerful tool to predict temperature-dependent yield strengths (YS) of structural materials, particularly for multi-principal-element systems. However, successful machine-learning predictions depend on the use…

Materials Science · Physics 2022-07-13 Baldur Steingrimsson , Xuesong Fan , Rui Feng , Peter K. Liaw

Refractory high-entropy alloys, RHEAs, are promising high-temperature structural materials. Their large compositional space poses great design challenges for phase control and high strength-ductility synergy. The present research pioneers…

Materials Science · Physics 2023-12-11 Jie Qi , Xuesong Fan , Diego Ibarra Hoyos , Michael Widom , Peter K. Liaw , Joseph Poon

High-entropy alloys (HEAs) have attracted extensive interest due to their exceptional mechanical properties and the vast compositional space for new HEAs. However, understanding their novel physical mechanisms and then using these…

Materials Science · Physics 2022-09-08 Xianglin Liu , Jiaxin Zhang , Zongrui Pei

Refractory compositionally complex alloys (RCCAs) are considered the next generation high-temperature materials. However, their high-dimensional composition spaces are too large to explore by traditional density functional theory or…

Safe and high-density storage of hydrogen, for a clean-fuel economy, can be realized by hydride-forming materials, but these materials should be able to store hydrogen at room temperature. Some high-entropy alloys (HEAs) have recently been…

Materials Science · Physics 2024-05-31 Shivam Dangwal , Yuji Ikeda , Blazej Grabowski , Kaveh Edalati

In the quest of new materials that can withstand severe irradiation and mechanical extremes for advanced applications (e.g. fission reactors, fusion devices, space applications, etc), design, prediction and control of advanced materials…

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

Multi-principal-element metallic alloys have created a growing interest that is unprecedented in metallurgical history, in exploring the property limits of metals and the governing physical mechanisms. Refractory high-entropy alloys (RHEAs)…

The design of high-entropy alloys (HEA) with desired properties is challenging due to their large compositional space. While various machine learning (ML) models can predict specific HEA solid-solution phases (SS), predicting high-entropy…

Materials Science · Physics 2023-06-27 Jie Qi , Diego Ibarra Hoyos , S. Joseph Poon

This chapter presents an innovative framework for the application of machine learning and data analytics for the identification of alloys or composites exhibiting certain desired properties of interest. The main focus is on alloys and…

Materials Science · Physics 2020-12-15 Baldur Steingrimsson , Xuesong Fan , Anand Kulkarni , Michael C. Gao , Peter K. Liaw

Refractory multi-principal element alloys (RMPEAs) represent a novel class of alloys characterized by an extensive compositional design space and the potential for exceptional mechanical performance under extreme conditions. While accurate…

Materials Science · Physics 2026-04-21 A. K. Shargh , C. D. Stiles , J. A. El-Awady

High-entropy alloys are solid solutions of multiple principal elements, capable of reaching composition and feature regimes inaccessible for dilute materials. Discovering those with valuable properties, however, relies on serendipity, as…

High-entropy alloys (HEAs) with multiple constituent elements have been extensively studied in the past 20 years due to their promising engineering application. Previous experimental and computational studies of HEAs focused mainly on…

Materials Science · Physics 2020-04-10 Liang Zhang , Kun Qian , Björn W. Schuller , Cheng Lu , Yasushi Shibuta , Xiaoxu Huang

The tunability of the mechanical properties of refractory multi-principal-element alloys (RMPEAs) make them attractive for numerous high-temperature applications. It is well-established that the phase stability of RMPEAs control their…

Materials Science · Physics 2024-08-13 A. K. Shargh , C. D. Stiles , J. A. El-Awady

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
‹ Prev 1 2 3 10 Next ›