摘要
Recent developments in data mining-aided materials discovery and optimization are reviewed in this paper,and an introduction to the materials data mining(MDM)process is provided using case studies.Both qualitative and quantitative methods in machine learning can be adopted in the MDM process to accomplish different tasks in materials discovery,design,and optimization.State-of-the-art techniques in data mining-aided materials discovery and optimization are demonstrated by reviewing the controllable synthesis of dendritic Co_(3)O_(4) superstructures,materials design of layered double hydroxide,battery materials discovery,and thermoelectric materials design.The results of the case studies indicate that MDM is a powerful approach for use in materials discovery and innovation,and will play an important role in the development of the Materials Genome Initiative and Materials Informatics.
基金
Financial supports to this work from National Key Research and Development Program of China(No.2016YFB0700504,2017YFB0701600)
Science and Technology Commission of Shanghai Municipality of China(No.15DZ2260300 and No.16DZ2260600)are gratefully acknowledged.
