电池的“预言家”——AI 如何在电池出厂时就预测它一辈子的寿命轨迹| Battery Brew 8

本期主题：电池的“预言家”——AI 如何在电池出厂时就预测它一辈子的寿命轨迹节目概述本期节目深入探讨一项超级硬核却又实用爆棚的电池研究：清华大学深圳国际研究生院周光敏、张选、李阳教授团队在《Energy & Environmental Science》上发表的最新成果。他们开发了一种基于“物理信息学习”的非破坏性退化模式解耦技术，只需电池前50次循环（仅占总寿命4%）的多步充电数据，就能精准预测电池整个生命周期的退化轨迹，甚至跨温度预测准确率高达95.1%。这不仅能大幅缩短电池研发周期，还能为报废原型开启“精准直接回收”模式，潜在市场规模到2060年可达197亿美元。参考文献 & 延伸阅读原文论文：Zhou et al., "Non-destructive degradation pattern decoupling in lithium-ion batteries via physics-informed learning", Energy & Environmental Science, 2025.感谢收听！继续充电，也继续酿造好生活！#EKLBatteryBrew更多电池前沿论文&解读，探索X账号：@[EKL_Batteries](x.com)前往小宇宙评论区与主播互动

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电池的“预言家”——AI 如何在电池出厂时就预测它一辈子的寿命轨迹| Battery Brew 8

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