The DOI matches its Crossref record.
Computational Study of the Mechanisms of Superoxide-Induced Decomposition of Organic Carbonate-Based Electrolytes
Abstract
There is increasing experimental evidence that organic carbonate-based electrolytes are incompatible with the discharge products of the nonaqueous lithium−air (oxygen) battery. Theoretically, the lithium−air battery offers the highest gravimetric density for energy storage applications, promising to revolutionize electric vehicle transportation. Calculations suggest that propylene carbonate, ethylene carbonate, and dimethyl carbonate, commonly used electrolytes in Li-ion batteries, are easily decomposed by the superoxide ion via nucleophilic attack at the ethereal carbon atom. In the case of propylene carbonate, base-mediated proton abstraction from the methyl group has to be considered as an additional solvent decomposition pathway. The present study provides a mechanistic understanding of solvent instability to assist the design of stable electrolytes for Li−air energy storage systems.
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
Cited by
Electrolytes and Interphases in Li-Ion Batteries and Beyond
Xu, K. (2014) · Chemical Reviews · doi:10.1021/cr500003w · Cited by 5,566
Electrochemical in situ investigations of SEI and dendrite formation on the lithium metal anode
Bieker, G., Winter, M., & Bieker, P. (2015) · Physical Chemistry Chemical Physics · doi:10.1039/c4cp05865h · Cited by 777
Borodin, O., Behl, W., & Jow, T. R. (2013) · The Journal of Physical Chemistry C · doi:10.1021/jp400527c · Cited by 365
Metadata
- Authors
- Bryantsev, V. S., & Blanco, M.
- Venue
- The Journal of Physical Chemistry Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2011-02-02
- Volume
- 2
- Issue
- 5
- Pages
- 379-383
- ISSN
- 1948-7185 (ISSN-L)
- OpenAlex
- W2329303392
- Cited by
- 200
- References
- 0
- FWCI
- 18.94
- 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: Computational Study of the Mechanisms of Superoxide-Induced Decomposition of Organic Carbonate-Based Electrolytes. https://app.cochat.ai/papers/10.1021/jz1016526
- The paper
- Bryantsev, V. S., & Blanco, M. (2011). Computational Study of the Mechanisms of Superoxide-Induced Decomposition of Organic Carbonate-Based Electrolytes. The Journal of Physical Chemistry Letters. https://doi.org/10.1021/jz1016526
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.