Probing oxygen stability in NMC battery materials through spectroscopy, microscopy, modeling, and AI/ML

ORAL

Abstract

One of the significant mode of failure, but also an avenue for potential additional energy capacity, for lithium ion battery cathode materials is oxygen reactivity. Previously, we explored the use of computational and experimental x-ray absorption spectroscopy to determine the oxygen activity in lithium- iron [1] and iridium [2] oxide compounds. The issue is particularly important for the leading Ni-Mn-Co (NMC) cathode materials. In this talk, we will describe the use of density functional theory (DFT) together with microscopy and spectroscopy, and machine learning [3] and computer vision based microscopy tool Ingrained [4], to determine oxygen structure and stability in NMC materials and grain boundaries [5].

* We acknowledge the support from the BES SUFD Early Career award. This work is supported by the U.S. Department of Energy (DOE) Office of Science Scientific User Facilities project titled “Integrated Platform for Multimodal Data Capture, Exploration and Discovery Driven by AI Tools”. Work performed at the Center for Nanoscale Materials, a U.S. Department of Energy Office of Science User Facility, was supported by the U.S. DOE, Office of Basic Energy Sciences, under Contract No. DE-AC02-06CH11357. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. We gratefully acknowledge the computing resources provided on Bebop, a high-performance computing cluster operated by the Laboratory Computing Resource Center at Argonne National Laboratory.

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Publication: [1] L Li, E Lee, JW Freeland, TT Fister, MM Thackeray, MKY Chan, "Identifying the Chemical Origin of Oxygen Redox Activity in Li-Rich Anti-Fluorite Lithium Iron Oxide by Experimental and Theoretical X-ray Absorption Spectroscopy," The journal of physical chemistry letters 10, 806 (2019)
[2] L Li, et al, "Probing Electrochemically Induced Structural Evolution and Oxygen Redox Reactions in Layered Lithium Iridate," Chemistry of Materials 31, 4341 (2019).
[3] Y Chen, C Chen, I Hwang, MJ Davis, W Yang, C Sun, SP Ong, MKY Chan, "Robust Machine Learning Inference from X-ray Absorption Near Edge Spectra through Featurization," arXiv preprint arXiv:2310.07049 (2023).
[4] E Schwenker, VSC Kolluru, et al, "Ingrained: An Automated Framework for Fusing Atomic‐Scale Image Simulations into Experiments," Small 18, 2102960 (2022).
[5] X Liu, GL Xu, VSC Kolluru, et al, "Origin and regulation of oxygen redox instability in high-voltage battery cathodes," Nature Energy 7, 808 (2022).

Presenters

  • Maria K Chan

    Argonne National Laboratory

Authors

  • Yiming Chen

    Argonne National Laboratory

  • Haili Jia

    Argonne National Laboratory

  • Chaitanya Kolluru

    Argonne National Laboratory

  • Guiliang Xu

    Argonne National Laboratory

  • Chengjun Sun

    Argonne National Laboratory

  • Wanli Yang

    Lawrence Berkeley National Laboratory

  • Maria K Chan

    Argonne National Laboratory