The DOI matches its Crossref record; 258 of the 258 references it cites were found in a registry or an index.
Layered Cathode Materials for Lithium-Ion Batteries: Review of Computational Studies on LiNi1–x–yCoxMnyO2 and LiNi1–x–yCoxAlyO2
Abstract
At present the most successful rechargeable battery is the Li-ion battery, due to the small size, high energy density, and low reduction potential of Li. Computational materials science has become an increasingly important tool to study these batteries, and in particular cathode properties. In silico studies of cathode materials have proven to be a valuable tool to understand the workings of cathodes, without having to do sophisticated experiments. First-principles and empirical computations have been used by various groups to study key properties, such as structural stability, electronic structure, ion diffusion mechanisms, equilibrium cell voltage, thermal and electrochemical stability, and surface behavior of Li-ion battery cathode materials. Arguably, the most practical and promising Li-ion cathode materials today are layered oxide materials, and in particular LiNi 1– x – y Co x Mn y O 2 (NCM) and LiNi 1– x – y Co x Al y O 2 (NCA). Here, some of the computational approaches to studying Li-ion batteries, with special focus on issues related to layered materials, are discussed. Subsequently, an overview of theoretical and related experimental work performed on layered cathode materials, and in particular on NCM and NCA materials, is provided.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Generalized Gradient Approximation Made Simple
Perdew, J. P., Burke, K., & Ernzerhof, M. (1996) · Physical Review Letters · doi:10.1103/physrevlett.77.3865 · Cited by 215,824
Projector augmented-wave method
Blöchl, P. E. (1994) · Physical Review B · doi:10.1103/physrevb.50.17953 · Cited by 92,732
Kresse, G., & Furthmüller, J. (1996) · Computational Materials Science · doi:10.1016/0927-0256(96)00008-0 · Cited by 75,638
Self-Consistent Equations Including Exchange and Correlation Effects
Kohn, W., & Sham, L. J. (1965) · Physical Review · doi:10.1103/physrev.140.a1133 · Cited by 64,135
Grimme, S., Antony, J., Ehrlich, S., & Krieg, H. (2010) · The Journal of Chemical Physics · doi:10.1063/1.3382344 · Cited by 59,686
Density-functional exchange-energy approximation with correct asymptotic behavior
Becke, A. D. (1988) · Physical Review A · doi:10.1103/physreva.38.3098 · Cited by 53,711
Hohenberg, P., & Kohn, W. (1964) · Physical Review · doi:10.1103/physrev.136.b864 · Cited by 53,541
Ab initio molecular dynamics for liquid metals
Kresse, G., & Hafner, J. (1993) · Physical Review B · doi:10.1103/physrevb.47.558 · Cited by 45,727
Semiempirical GGA‐type density functional constructed with a long‐range dispersion correction
Grimme, S. (2006) · Journal of Computational Chemistry · doi:10.1002/jcc.20495 · Cited by 31,038
Kresse, G., & Hafner, J. (1994) · Physical Review B · doi:10.1103/physrevb.49.14251 · Cited by 23,019
Metadata
- Authors
- Chakraborty, A., Kunnikuruvan, S., Kumar, S., Markovsky, B., Aurbach, D., Dixit, M., & Major, D. T.
- Venue
- Chemistry of Materials
- Publisher
- American Chemical Society (ACS)
- Published
- 2020-01-06
- Volume
- 32
- Issue
- 3
- Pages
- 915-952
- ISSN
- 0897-4756 (ISSN-L)
- 1520-5002
- OpenAlex
- W3000617101
- Cited by
- 322
- References
- 258
- FWCI
- 15.70
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Layered Cathode Materials for Lithium-Ion Batteries: Review of Computational Studies on LiNi1–x–yCoxMnyO2 and LiNi1–x–yCoxAlyO2. https://app.cochat.ai/papers/10.1021/acs.chemmater.9b04066
- The paper
- Chakraborty, A., Kunnikuruvan, S., Kumar, S., Markovsky, B., Aurbach, D., Dixit, M., & Major, D. T. (2020). Layered Cathode Materials for Lithium-Ion Batteries: Review of Computational Studies on LiNi1–x–yCoxMnyO2 and LiNi1–x–yCoxAlyO2. Chemistry of Materials. https://doi.org/10.1021/acs.chemmater.9b04066
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.