Abstract
A heterogeneous phase/structure distribution in the bulk of spinel lithium nickel manganese oxides (LNMOs) is the key to maximizing the performance and stability of the cathode materials of lithium-ion batteries. Herein, we report the use of two-dimensional ptychographic X-ray absorption fine structure (XAFS) to visualize the density and valence maps of manganese and nickel in as-prepared LNMO particles and unsupervised learning to classify the three-phase group in terms of different elemental compositions and chemical states. The described approach may increase the supply of information for nanoscale characterization and promote the design of suitable structural domains to maximize the performance and stability of batteries.
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