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Yu, Xiqian (ORCID:000000018513518X)

Publications and source records attributed to Yu, Xiqian (ORCID:000000018513518X).

Depth-dependent valence stratification driven by oxygen redox in lithium-rich layered oxide

Abstract Lithium-rich nickel-manganese-cobalt (LirNMC) layered material is a promising cathode for lithium-ion batteries thanks to its large energy density enabled by coexisting cation and anion redox activities. It however suffers from a voltage decay upon cycling, urging for an in-depth understanding of the particle-level structure and chemical complexity. In this work, we investigate the Li 1.2 Ni 0.13 Mn 0.54 Co 0.13 O 2 particles morphologically, compositionally, and chemically in three-dimensions. While the composition is generally uniform throughout the particle, the charging induces a strong depth dependency in transition metal valence. Such a valence stratification phenomenon is attributed to the nature of oxygen redox which is very likely mostly associated with Mn. The depth-dependent chemistry could be modulated by the particles’ core-multi-shell morphology, suggesting a structural-chemical interplay. These findings highlight the possibility of introducing a chemical gradient to address the oxygen-loss-induced voltage fade in LirNMC layered materials.

25 ENERGY STORAGE↗

Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes

The 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.

25 ENERGY STORAGE↗