Artificial Intelligence for Materials Science

Dr. Yuan Cheng. Before join in Monash Suzhou Research Institute, Dr Yuan Cheng is a Senior Scientist and Group Manager at the Institute of High Performance Computing (IHPC) in Singapore. She graduated from Fudan University, China with a Bachelor degree and got her Ph. D degree from National University of Singapore. Upon completion of her Ph.D. degree, she joined the Institute of High Performance Computing (IHPC) in Singapore. During Feb. till Jun. 2009 she visited Brown University, USA as a visiting scholar. Dr Cheng’s expertise involves investigation of the mechanical properties of biomaterials, the mechanical properties of nanomaterials and the interface between nanomaterials and water & biomaterials, exploring their applications in biomedical engineering. She has published more than 70 journal papers in the leading journals including Prog. Polym. Sci., Physics Reports, Adv. Mater., Adv. Funct. Mater., Nature Comm., etc., with an H-index of 25.Dr. Tian Wang. Dr. Wangreceived the M.S. and Ph.D. degrees from Xi'an Jiaotong University, China, and the University of Technology of Troyes, France, in 2010 and 2014, respectively. He is currently an Associate Professor with the School of Automation of Science and Electrical Engineering, Beihang University. His research interests include artificial intelligence and machine learning.Dr. Gang Zhang. Dr. Zhang received B. Sci and PhD in physics from Tsinghua University in 1998 and 2002, respectively. Prior to his joining Institute of High Performance Computing (IHPC), he was a professor at Department of Electronics, Peking University. His research focuses on electronic, thermal, and optical properties of novel materials and structures in important engineering problems, aims to develop a fundamental understanding of the processes underlying new technologies and to establish simulations tools for material and device design.

• Chapter 1. Brief Introduction of the Machine Learning Method.- Chapter 2. Machine learning for high-entropy alloys.- Chapter 3. Two-way TrumpetNets and TubeNets for Identification of Material Parameters.- Chapter 4. Machine learning interatomic force fields for carbon allotropic materials.- Chapter 5. Genetic Algorithms.- Chapter 6. Accelerated Discovery of Thermoelectric Materials using Machine Learning.- Chapter 7. Thermal nanostructure design based on materials informatics. - Chapter 8. Machine Learning Accelerated Insights of Perovskite Materials.