(130c) Understanding the Onset of Surface Degradation in Layered Li-Battery Cathodes | AIChE

(130c) Understanding the Onset of Surface Degradation in Layered Li-Battery Cathodes

Authors 

Li, X. - Presenter, Columbia Universtiy
Lam, W. C. A., Columbia University
Yeu, I. W., Columbia University
Mishra, A., University of Illinois Urbana-Champaign
Rodríguez-López, J., University of Illinois at Urbana-Champaign
Urban, A., Columbia University
Cobalt, a scarce transition metal, is a constituent of the cathode materials of most-energy dense commercial lithium-ion batteries (LIBs), such as LiCoO2 (LCO), LiNixMn1-x/2Co1-x/2O2 with x < 1 (NMC), and LixCoyAlzO2 with x > y >> z (NCA). Although LiNiO2 (LNO) is chemically very similar to LCO, LNO and related Co-free Ni-rich cathodes suffer from surface degradation via oxygen gas release during electrochemical cycling, which leads to safety concerns and prevents commercial adoption. While the surface degradation of LiNiO2 and related cathode compositions have been characterized experimentally on a phenomenological level, an understanding of the surface reconstructions that form on the atomic scale and the intrinsic surface instability of LNO compared with LCO is still lacking.

Here, we apply first-principles atomistic modeling to shed light on surface reactivity using a thermodynamic methodology for the prediction of voltage and temperature-dependent surface electrode reconstructions that we recently developed [1]. We implemented this approach in a computational framework, automating the time-consuming enumeration of surface reconstructions, the construction of symmetric slab models, and the analysis of surface phase diagrams. We determined the self-reduction mechanism of LNOand compared the stable surface reconstructions with those of LCO. The results provide insight into the initial stages of surface degradation in Ni-rich cathodes and lies the foundation for the computational design of cathode materials that are stable against oxygen release.

[1] X. Li, Q. Wang, H. Guo, N. Artrith, and A. Urban, in revision (2022); preprint: https://doi.org/10.48550/arXiv.2112.04697