Prospects for the database development in electrical engineering materials.

The article focuses on the development, challenges, and future prospects of database technology in the field of electrical engineering materials within the framework of Material Genome Engineering (MGE). It highlights the critical role of databases in managing the vast data generated by high-throughput experiments and computational methods, such as density functional theory (DFT), to accelerate material discovery and innovation. While specialized electrical engineering material databases are still underdeveloped compared to other material fields, existing platforms like the Materials Project, AFLOWLIB, and the Open Quantum Materials Database (OQMD) provide extensive computational data relevant to electrical materials. The article emphasizes the need for unified standards, secure data sharing mechanisms, integration with machine learning and artificial intelligence, and enhanced cooperation among computational, experimental, and database platforms to realize a data-driven model for electrical material research and development.