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Record W2898610016 · doi:10.1038/s41467-018-06877-9

A high-energy sulfur cathode in carbonate electrolyte by eliminating polysulfides via solid-phase lithium-sulfur transformation

2018· article· en· W2898610016 on OpenAlexafffund
Xia Li, Mohammad Norouzi Banis, Andrew Lushington, Xiaofei Yang, Qian Sun, Yang Zhao, Changqi Liu, Qizheng Li, Biqiong Wang, Wei Xiao, Changhong Wang, Minsi Li, Jianwen Liang, Ruying Li, Yongfeng Hu, Lyudmila V. Goncharova, Huamin Zhang, Tsun‐Kong Sham, Xueliang Sun

Bibliographic record

VenueNature Communications · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsCanadian Light Source (Canada)Western University
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsElectrolyteSulfurElectrochemistryCarbonateCathodeInorganic chemistryLithium (medication)ChemistryLithium carbonateMaterials scienceChemical engineeringElectrodeIonOrganic chemistryIonic bondingPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract Carbonate-based electrolytes demonstrate safe and stable electrochemical performance in lithium-sulfur batteries. However, only a few types of sulfur cathodes with low loadings can be employed and the underlying electrochemical mechanism of lithium-sulfur batteries with carbonate-based electrolytes is not well understood. Here, we employ in operando X-ray absorption near edge spectroscopy to shed light on a solid-phase lithium-sulfur reaction mechanism in carbonate electrolyte systems in which sulfur directly transfers to Li2S without the formation of linear polysulfides. Based on this, we demonstrate the cyclability of conventional cyclo-S8 based sulfur cathodes in carbonate-based electrolyte across a wide temperature range, from −20 °C to 55 °C. Remarkably, the developed sulfur cathode architecture has high sulfur content (>65 wt%) with an areal loading of 4.0 mg cm−2. This research demonstrates promising performance of lithium-sulfur pouch cells in a carbonate-based electrolyte, indicating potential application in the future.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.282
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations243
Published2018
Admission routes2
Has abstractyes

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