Experimental evidence of record-breaking solid electrolyte discovered by machine learning
Published on
ACS Publications
Using next-generation compute to design next-generation materials.
Aionics combines high-performance computing with machine learning to build better batteries for the electrification-of-everything revolution
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
Published on
Springer Link
Perspective on battery-powered urban aircraft
Published on
Nature
Technoeconomic analysis of iron-air batteries
Published on
ECSarXiv Preprints
Facile screening of billions of candidate materials with ML models
Published on
AIP Publishing
CB Insights today named Aionics to its eighth-annual AI 100, showcasing the 100 most promising private AI companies of 2024. “AI is taking off at lightning speed, and it’s not just big tech companies at the forefront of it,” said Deepashri Varadharajan, director of AI research at CB Insights. “Our AI 100 winners – many of themContinue reading "Aionics Named to CB Insights’ AI 100 2024"
Aionics partners with Cellforce, featured in TechCrunch and MIT Technology Review
Solomon Oyakhire joins Aionics as Scholar-in-Residence
Aionics, Inc. and Carnegie Mellon University Announce Licensing Agreement for Breakthrough Battery Electrolyte Design Software
LK-99: What can machine learning tell us about the candidate superconductor?
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