|About this Abstract
||2022 TMS Annual Meeting & Exhibition
||Advances in Multi-Principal Elements Alloys X
||Computational Study of Thermodynamic and Thermoelectric Properties of Al-Co-Cr-Fe-Ni and Al-Cu-Fe-Mn-Ni High-Entropy Alloys
||Md Abdullah Al Hasan, Seungha Shin, Xuesong Fan, Peter K Liaw, Dustin Allen Gilbert
|On-Site Speaker (Planned)
High-entropy alloys (HEAs) have been of great interest as novel types of alloys because of their unique microstructures and adjustable properties. However, their large configurational space has imposed challenges on the prediction of properties and material design. Computational approaches enable us to effectively study various properties of HEAs, addressing atomic details under systematically controlled conditions. In this presentation, we will introduce our recent computational studies on thermodynamic and thermoelectric properties of Al-Co-Cr-Fe-Ni and Al-Cu-Fe-Mn-Ni HEAs. We investigated these properties of HEAs with varied compositions and short-range orders, using first-principles calculations, molecular dynamics, and semi-classical Boltzmann transport theory. In addition, to effectively analyze a large size of data, we used modern data analytics, including correlation analysis and machine learning. Through this research, we have identified the effects of Al contents and short-range order on thermoelectric performance and thermodynamic properties in AlxCoCrFeNi and studied the thermodynamic properties of various structures of AlCuFeMnNi.
||High-Entropy Alloys, Computational Materials Science & Engineering, Machine Learning