Bridging AI- and experimental-led materials discovery with better database architecture
Materials databases lie at the heart of future data-driven discovery in energy-related fields, say researchers from Tohoku University. In an article published in the journal Precision Chemistry, they have examined how different types of databases, both computational and experimental, work together t...
Image: Phys.org
Materials databases lie at the heart of future data-driven discovery in energy-related fields, say researchers from Tohoku University. In an article published in the journal Precision Chemistry, they have examined how different types of databases, both computational and experimental, work together to support modern artificial intelligence (AI) tools used in materials science.
Originally published at Phys.org
