Matscholar: The search engine for materials science researchers
06-14, 10:10–10:30 (Europe/Berlin), Frannz Salon

Matscholar ( is a scientific knowledge search engine for materials science researchers. We have indexed information about materials, their properties, and the applications they are used in for millions of materials by text mining the abstracts of more than 5 million materials science research papers. Using a combination of traditional and AI-based search technologies, our system extracts the key pieces of information and makes it possible for researchers to do queries that were previously impossible. Matscholar, which utilizes and our our own bespoke language models, greatly accelerates the speed at which energy and climate tech researchers can make breakthroughs and can even help them discover insights about materials and their properties that have gone unnoticed.

The Search track is presented by OpenSource Connections

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John Dagdelen is a PhD student in the department of materials science and engineering at UC Berkeley. His research focuses at the intersection of artificial intelligence, high performance computing, and materials discovery and design.