Jiang, ZhisenLi, JizhouYang, YangMu, LinqinWei, ChenxiYu, XiqianPianetta, PieroZhao, KejieCloetens, PeterLin, FengLiu, Yijin2020-08-172020-08-172020http://hdl.handle.net/10919/99723The microstructure of a composite electrode determines how individual battery particles are charged and discharged in a lithium-ion battery. It is a frontier challenge to experimentally visualize and, subsequently, to understand the electrochemical consequences of battery particles’ evolving (de)attachment with the conductive matrix. Herein, we tackle this issue with a unique combination of multiscale experimental approaches, machine-learning-assisted statistical analysis, and experiment-informed mathematical modeling. Our results suggest that the degree of particle detachment is positively correlated with the charging rate and that smaller particles exhibit a higher degree of uncertainty in their detachment from the carbon/ binder matrix. We further explore the feasibility and limitation of utilizing the reconstructed electron density as a proxy for the state-of-charge. Our findings highlight the importance of precisely quantifying the evolving nature of the battery electrode’s microstructure with statistical confidence, which is a key to maximize the utility of active particles towards higher battery capacity.en-USCreative Commons Attribution 4.0 InternationalArticle - Refereedhttps://doi.org/10.1038/s41467-020-16233-511