| About this Abstract |
| Meeting |
MS&T24: Materials Science & Technology
|
| Symposium
|
Understanding High Entropy Materials via Data Science and Computational Approaches
|
| Presentation Title |
Predictive Screening of Phase Stability in High-Entropy Borides |
| Author(s) |
Muhammad Waqas Qureshi, Shuguang Wei, Jun Young Kim, Dane Morgan, Izabela Szlufarska |
| On-Site Speaker (Planned) |
Muhammad Waqas Qureshi |
| Abstract Scope |
High-entropy materials offer unprecedented opportunities for tailoring mechanical, chemical, and thermal properties for enhanced performance across a multitude of energy storage, catalysis, nuclear and high-temperature applications. However, the major challenge in advancing their discovery lies in accurately predicting their single-phase stability and formation ability. In this study, we predicted stability of several new single-phase high-entropy borides (HEBs) by using a combination of CALPHAD and screening of descriptors through first-principal calculations. All the compositions undergo screening using available descriptors including entropy forming ability and lattice distortion and empirical descriptors. All existing descriptors have a misclassification regime, which limits their accuracy for predicting HEBs. Here, we propose a new cost-effective descriptor, called structure penalty, which predicts the stability of HEBs consistently with all the currently available experimental data and calculated phase diagrams. Our combinational approach holds the promise of expediting the design of HEBs by effectively integrating theoretical predictions with experimental investigations. |