AI Fast Track to Battery Fast Charge
Source abstract
Abstract
In the February 20th issue of Nature, William Chueh and colleagues present a closed-loop optimization strategy for the fast charging of battery cells using early cycle life predictions obtained from machine learning models and Bayesian optimization. 1 The developed strategy uses limited testing to obtain substantial improvements in the cycle life of commercial battery cells and aptly demonstrates how machine learning and AI can fast track the performance optimization of battery materials and cells.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Battery Technologies Research · Advancements in Battery Materials · Advanced Battery Materials and Technologies
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References (10)
Show source-provided references
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