Decoding Composition-Structure-Performance Relations in Sodium Layered Oxide Positive Electrode Materials
Abstract
Layered sodium transition-metal (TM) oxides, NaxTMO2, are among the most promising sodium-ion positive electrode materials, yet their Na/vacancy orderings, layer stacking sequences, and cooperative Jahn--Teller distortions are known only for a few single-TM compounds. We compile the Na/vacancy orderings reported in earlier studies into a single library of 41 unique orderings and apply this uniformly to five single-TM and all ten NaxTM0.5TM'0.5O2 oxides (TM = Ti, Mn, Fe, Co, Ni), screening more than 120,000 structures with machine-learning interatomic potentials prior to 1,025 accurate first-principles calculations. The phase diagrams explain the observed O3/P3/O1 sequences and voltages, and the O3-to-P3 competition hinges on ordering energies of a few meV per atom that scalar descriptors, such as the cationic potential and the interlayer-slab distance, miss. Our extensive analysis reveals that the redox couples form a nearly partner-independent ladder, Ti3+/4+ < Mn3+/4+ < Co3+/4+ < Ni2+/3+ < Fe3+/4+, explaining pristine charge transfer and the oxidation sequence. Van Vleck analysis of every TMO6 octahedron reveals that TM mixing suppresses the cooperative Jahn--Teller distortions of Mn3+ and Ni3+ through charge transfer to Jahn--Teller-inactive states or dilution of Jahn--Teller-active centers. We formulate an energy-density-versus-strain map that yields a design rule: a high-voltage couple without Jahn--Teller strain, which Mn4+/Ni2+ charge transfer realizes in NaxMn0.5Ni0.5O2, the most practical composition. We release the ordering-resolved dataset as a training set for subsequent training of accurate machine-learning interatomic potentials.
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BibTeX
@misc{choi2026decoding,
title = {{Decoding Composition-Structure-Performance Relations in Sodium Layered Oxide Positive Electrode Materials}},
author = {Yunyeong Choi and Hasindhi H. Lokuge and Joshua D. Bocarsly and Pieremanuele Canepa},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.30591},
eprint = {2610.30591},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.30591},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - Decoding Composition-Structure-Performance Relations in Sodium Layered Oxide Positive Electrode Materials
AU - Yunyeong Choi
AU - Hasindhi H. Lokuge
AU - Joshua D. Bocarsly
AU - Pieremanuele Canepa
PY - 2026
DA - 2026/10/26
PB - arXiv
DO - 10.48550/arxiv.2610.30591
UR - https://arxiv.org/abs/2610.30591
AB - Layered sodium transition-metal (TM) oxides, Na_xTMO_2, are among the most promising sodium-ion positive electrode materials, yet their Na/vacancy orderings, layer stacking sequences, and cooperative Jahn--Teller distortions are known only for a few single-TM compounds. We compile the Na/vacancy orderings reported in earlier studies into a single library of 41 unique orderings and apply this uniformly to five single-TM and all ten Na_xTM_0.5TM'_0.5O_2 oxides (TM = Ti, Mn, Fe, Co, Ni), screening more than 120,000 structures with machine-learning interatomic potentials prior to 1,025 accurate first-principles calculations. The phase diagrams explain the observed O3/P3/O1 sequences and voltages, and the O3-to-P3 competition hinges on ordering energies of a few meV per atom that scalar descriptors, such as the cationic potential and the interlayer-slab distance, miss. Our extensive analysis reveals that the redox couples form a nearly partner-independent ladder, Ti^3+/4+ < Mn^3+/4+ < Co^3+/4+ < Ni^2+/3+ < Fe^3+/4+, explaining pristine charge transfer and the oxidation sequence. Van Vleck analysis of every TMO_6 octahedron reveals that TM mixing suppresses the cooperative Jahn--Teller distortions of Mn^3+ and Ni^3+ through charge transfer to Jahn--Teller-inactive states or dilution of Jahn--Teller-active centers. We formulate an energy-density-versus-strain map that yields a design rule: a high-voltage couple without Jahn--Teller strain, which Mn^4+/Ni^2+ charge transfer realizes in Na_xMn_0.5Ni_0.5O_2, the most practical composition. We release the ordering-resolved dataset as a training set for subsequent training of accurate machine-learning interatomic potentials.
ER -