Design of high bulk moduli high entropy alloys using machine learning

• Main Authors: Kandavalli, Manjunadh, Agarwal, Abhishek, Poonia, Ansh, Kishor, Modalavalasa, Ayyagari, Kameswari Prasada Rao
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2024
• Subjects: Engineering; Least absolute shrinkage and selection operator; Machine learning
• Online Access: https://hdl.handle.net/10356/173853
• Institution: Nanyang Technological University

In this work, the authors have demonstrated the use of machine learning (ML) models in the prediction of bulk modulus for High Entropy Alloys (HEA). For the first time, ML has been used for optimizing the composition of HEA to achieve enhanced bulk modulus values. A total of 12 ML algorithms were tr...