Many-Body Benchmark of Electronic Charge and Spin Densities for Li 1– x NiO 2

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Authors: Abdul Ghaffar, Shenli Zhang, Liwen F. Wan, Kayahan Saritas, Fernando Agustín Reboredo, Jaron T. Krogel
Cited by: 1
References: 87

Abstract

High Resolution Image Download MS PowerPoint Slide Accurate benchmarks are particularly important for highly correlated oxides as mean-field approximations often fail to describe the subtle balance of charge transfer and magnetism in these materials with an accuracy comparable to experimental needs. Here we present accurate diffusion Monte Carlo (DMC) results of the electronic charge and spin densities for the tunable highly correlated oxide Li 1– x NiO 2 for x = 0, 1/2, and 1. To enable quantitative comparisons, we introduce a robust density-partitioning scheme, extending Voronoi analysis to assign atomic charges from spatially noisy DMC densities. We then benchmark common approximations used in density functional theory (DFT). Comparison against DMC shows that r 2 SCAN delivers the most balanced performance across charge, spin, and radial density descriptors, nearly reproducing DMC results for LiNiO 2 and apical Ni sites in Li 0.5 NiO 2 . Hybrid functionals (PBE0, SCAN0) perform unexpectedly poorly, and PBE + U + V yields inconsistent trends between charge and spin densities. Therefore, the r 2 SCAN functional minimizes errors relative to DMC while capturing the variable valence of the Ni ion and also retaining the computational efficiency of DFT for large-scale simulations of the tunable structural and electronic phases of Li 1– x NiO 2 . Our study highlights the importance of accurate benchmarking of the fundamental quantities involved in DFT to select appropriate DFT approximations in order to advance the predictive modeling of charge-transfer-driven phenomena in correlated electron systems.

Fields of Study & Subjects

Advancements in Battery Materials Transition Metal Oxide Nanomaterials Advanced Battery Materials and Technologies

Publication details

Journal / source
Journal of Chemical Theory and Computation
Publisher
American Chemical Society (ACS)
Volume
22
Issue
9
Pages
4346–4357
Publication date
20 April 2026
Language
EN