Laboratory

data.matr.io

D3Batt: Battery Cycling

Data-driven prediction
House
Closed-loop optimization
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Battery Materials

Aqueous electrolytes
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Simulation

Network of synthesizable materials
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CAMD and OQMD
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XANES for random forest models
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Electrocatalysis

OER catalysis (ACE-I)
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About

The data.matr.io materials research platform is designed to accelerate materials research so that a sustainable energy infrastructure may be realized in the twenty-first century. Here, we highlight our internal and external projects which use the data.matr.io platform to assist researchers in designing batteries for electric vehicles, optimize fuel cell catalysts, and discover never-before synthesized crystal structures. In addition, we demonstrate collaborative efforts between the matr.io development team and external research partners, including network analysis for synthesizeability, text mining for material prediction, automated property derivation, and multi-element corrosion analysis.