Bringing Big Data to Clean Energy Materials Discovery

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The Berlinguette research program focuses on developing advanced materials for clean energy production and storage. Google research is seeking to revolutionize materials science by using machine learning techniques to help researchers solve major research questions in new ways inaccessible to humans alone. A limitation to both these research programs is the lack of a capability to rapidly generate detailed characterization data for wide ranges of novel materials.This collaborative research program seeks to develop a microfabricated platform technology for performing simultaneous high-throughput materials fabrication, characterization and screening. The resulting microfabricated devices will use a multiplexed architecture to address large numbers of thin film samples with in situ electrochemical, electrical and thermal measurements. Microscopic and spectroscopic characterization tools will also be employed. These tools will provide both practical and fundamental insights into the characteristics of the studied materials.The Berlinguette research group is a pioneer in photochemical film growth methods that result in highly active electrocatalytic films. For this reason thin film samples will be grown photochemically as well as by electrosynthesis and through vapor deposition techniques. Dispensing film growth precursors and electrolytes via a microarray printer will allow a high throughput of systematically varied compositions of both films and electrolytes to be investigated. In collaboration with Google Inc, we will develop and deploy state-of-the-art big data analysis methodologies to make optimal use of the high volume of data this platform will produce. These technologies will enable the Berlinguette group to elucidate fundamental composition- and structure-property relationships and thus identify commercially viable clean energy materials at an unrivalled pace.