Designing viable molecular candidates is pivotal to devising low-cost and sustainable storage systems. A reinforcement learning framework has been developed that can identify stable candidates for redox flow batteries in the large search space of organic radicals.
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The authors declare no competing interests.
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Cao, Y., Ser, C.T., Skreta, M. et al. Reinforcement learning supercharges redox flow batteries. Nat Mach Intell 4, 667–668 (2022). https://doi.org/10.1038/s42256-022-00523-2