Experimental evidence of record-breaking solid electrolyte discovered by machine learning
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ACS Publications
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Using next-generation compute to design next-generation materials.
We use artificial intelligence and physics-based simulation to design new, customized electrolytes for high performance electrochemical systems: electric vehicle and aerospace batteries, long-duration energy storage systems, decarbonized manufacturing, and more.
Experimental evidence of record-breaking solid electrolyte discovered by machine learning
Published on
ACS Publications
Review of machine learning-based modeling for battery material design
Published on
Wiley Online Library
Two new low electrochemical expansion cathode materials identified from 38,000+ candidates
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Springer Link
Perspective on battery-powered urban aircraft
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Nature
Technoeconomic analysis of iron-air batteries
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ECSarXiv Preprints
Facile screening of billions of candidate materials with ML models
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AIP Publishing
Featured in the December-January edition of Automotive World’s Electric Mobility Magazine, Aionics CEO and co-founder Austin Sendek discussed how nearly all EV battery electrolytes today rely on combinations of the same 11 molecules—a tiny fraction of the 50 billion possibilities available. However, AI could be the key to unlocking this vast untapped pool, a breakthroughContinue reading "Aionics Featured in Automotive World"
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Dr. Venkat Viswanathan wins the 2024 Energy Lectureship Award for Energy Storage by ACS Energy Letters
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