Studying surface degradation of charged Ni-based Li-ion battery cathodes using machine-learning interatomic potentials

Abstract

Nickel-rich cathode materials are industry-leading high-performance materials for Li-ion batteries as they offer high capacity and energy density [1,2]. However, they are known to suffer from structural instability especially at high state of charge [3]. Structural transformations from a layered structure to spinel-/ and or rocksalt-like phases have been observed experimentally in post-mortem studies [4,5]. This process is accompanied by the loss of lattice oxygen [3,5,6]. While overwhelming experimental evidence is available regarding the process, exact atomistic pathways of these transformations are still under debate. While first-principle simulations can help to understand this degradation process on the atomic scale, they are limited by the computational cost of sampling rare reactive events at the appropriate level of theory. To bridge this gap, machine-learning interatomic potentials (MLIP) have become of tremendous interest in materials science [7,8]. In this contribution, we have studied surface degradation pathways of charged NiO2 surfaces using CHGNet as a charge-informed MLIP. We investigated various crystal facets of NiO2 by combining a finetuned MLIP and density-functional-theory (DFT) at the meta-generalized gradient approximation (metaGGA) level. We discuss surface energetics for different terminations and show novel surface degradation pathways obtained by MLIP molecular dynamics. The sampled structures are subsequently verified in terms of energetics using high accuracy DFT. We further discuss oxygen vacancy formation on these new surfaces and how oxygen vacancy defects can trigger follow-up Ni migration as an initial step towards thermodynamically stable end products. Our work showcases how DFT calculations can be efficiently extended with machine learning to study surface degradation in battery materials. Our study reveals novel surface degradation pathways in Nickelbased cathode materials as a first step towards a better understanding of the complex cathode material degradation process.

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