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Author

Arghya Bhowmik

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Open access Sep 2026

Domain-specific dataset enable accurate MLIPs for disordered halide-based solid electrolytes

Efficient exploration of chemical space with machine-learning interatomic potentials (MLIPs) requires a comprehensive, application-focused training database. Solid-state electrolytes for Li-ion batteries have attracted growing attention owing to their ability to improve safety and energy density. Among these, halide-ba...

Chiku Parida, Arghya Bhowmik, Juan Maria Garcia Lastra · 0 citations
Jul 2026

(Invited) Autonomous, Data-Driven Acceleration of Energy Storage Technology, from Electrons to Devices

Electrochemical energy conversion and storage sit at a decisive inflection point: urgency of breakthrough is high, yet the science remains dominated by multiscale physics, interfacial complexity, sparse high-fidelity data, and long validation cycles for safety and lifetime. I have a pragmatic thesis: AI does not “repla...

Arghya Bhowmik · 0 citations

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