Affiliations: State Grid Smart Grid Research Institute Co. Ltd., Beijing, China
Correspondence:
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Corresponding authors: Shengyi Li and Bo Wang, State Grid Smart Grid Research Institute Co.Ltd., Beijing, China. E-mails: lishengyi@ geiri.sgcc.com.cn; wangbopku@qq.com.
Abstract: With the proposal and development of the Material Genome Engineering program, artificial intelligence has played a significant role in accelerating the research and development of new materials. In the field of electrical engineering materials, high-throughput experimental and computational methods provide a huge amount of data. It also poses new challenges to how to manage material data scientifically and efficiently. Database technology has become a hot topic for material scientists and engineers. This paper makes a comprehensive overview of the development, demand analysis and application of database technology in the electrical engineering materials, and discusses the existing problems and the future development trend of the database. Compared with many materials, such as energy materials, catalytic materials, biomedical materials, etc., the electrical material database still has a long way to go in the process of database platform construction, management and operation, and practical application. However, driven by governmental support and market demand, the construction of electrical material database will gradually improve and play an important role in the data-driven new materials researches.
Keywords: Material genome engineering, electrical engineering materials, database, big data technology, machine learning
