Applying machine learning to balance performance and stability of high energy density materials

• Main Authors: Huang, Xiaona, Li, Chongyang, Tan, Kaiyuan, Wen, Yushi, Guo, Feng, Li, Ming, Huang, Yongli, Sun, Chang Q., Gozin, Michael, Zhang, Lei
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Electrical and electronic engineering; Computational Materials Science; Energy Materials
• Online Access: https://hdl.handle.net/10356/160677
• Institution: Nanyang Technological University

The long-standing performance-stability contradiction issue of high energy density materials (HEDMs) is of extremely complex and multi-parameter nature. Herein, machine learning was employed to handle 28 feature descriptors and 5 properties of detonation and stability of 153 HEDMs, wherein all 21,64...