Machine learning-guided synthesis of advanced inorganic materials

• Main Authors: Tang, Bijun, Lu, Yuhao, Zhou, Jiadong, Chouhan, Tushar, Wang, Han, Golani, Prafful, Xu, Manzhang, Xu, Quan, Guan, Cuntai, Liu, Zheng
• Other Authors: School of Materials Science and Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Engineering::Materials; Machine Learning (ML); Progressive Adaptive Model (PAM)
• Online Access: https://hdl.handle.net/10356/146742
• Institution: Nanyang Technological University

Synthesis of materials with minimum number of trials is of paramount importance towards the acceleration of advanced materials development. The enormous complexity involved in existing multi-variable synthesis methods leads to high uncertainty, numerous trials and exorbitant cost. Recently, machine...