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Record W3087911533 · doi:10.1016/j.isci.2020.101597

The Impact of Absorbed Solvent on the Performance of Solid Polymer Electrolytes for Use in Solid-State Lithium Batteries

2020· review· en· W3087911533 on OpenAlexafffund
Gabrielle Foran, Denis Mankovsky, Nina Verdier, David Lepage, Arnaud Prébé, David Aymé‐Perrot, Mickaël Dollé

Bibliographic record

VenueiScience · 2020
Typereview
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCrystallinityElectrolyteSolventLithium (medication)PolymerMaterials scienceElectrochemistryFast ion conductorBattery (electricity)Lithium batteryPolymer electrolytesChemical engineeringQuasi-solidIonic conductivityInorganic chemistryChemistryIonElectrodeOrganic chemistryIonic bondingComposite materialDye-sensitized solar cellPhysical chemistry

Abstract

fetched live from OpenAlex

The effects of solvent absorption on the electrochemical and mechanical properties of polymer electrolytes for use in solid-state batteries have been measured by researchers since the 1980s. These studies have shown that small amounts of absorbed solvent may increase ion mobility and decrease crystallinity in these materials. Even though many polymers and lithium salts are hygroscopic, the solvent content of these materials is rarely reported. As ppm-level solvent content may have important consequences for the lithium conductivity and crystallinity of these electrolytes, more widespread reporting is recommended. Here we illustrate that ppm-level solvent content can significantly increase ion mobility, and therefore the reported performance, in solid polymer electrolytes. Additionally, the impact of absorbed solvents on other battery components has not been widely investigated in all-solid-state battery systems. Therefore, comparisons will be made with systems that use liquid electrolytes to better understand the consequences of absorbed solvents on electrode performance.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.030
GPT teacher head0.304
Teacher spread0.274 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations91
Published2020
Admission routes2
Has abstractyes

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