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Record W4318499620 · doi:10.3390/batteries9020087

Limiting Factors Affecting the Ionic Conductivities of LATP/Polymer Hybrid Electrolytes

2023· article· en· W4318499620 on OpenAlexafffund
Adrien Méry, Steeve Rousselot, David Lepage, David Aymé‐Perrot, Mickaël Dollé

Bibliographic record

VenueBatteries · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCeramicElectrolyteMaterials scienceIonic conductivityLithium (medication)Chemical engineeringEthylene oxideSinteringPolymerLimitingConductivityFast ion conductorComposite materialChemistryElectrodePhysical chemistry

Abstract

fetched live from OpenAlex

All-Solid-State Lithium Batteries (ASSLB) are promising candidates for next generation lithium battery systems due to their increased safety, stability, and energy density. Ceramic and solid composite electrolytes (SCE), which consist of dispersed ceramic particles within a polymeric host, are among the preferred technologies for use as electrolytes in ASSLB systems. Synergetic effects between ceramic and polymer electrolyte components are usually reported in SCE. Herein, we report a case study on the lithium conductivity of ceramic and SCE comprised of Li1.4Al0.4Ti1.6(PO4)3 (LATP), a NASICON-type ceramic. An evaluation of the impact of the processing and sintering of the ceramic on the conductive properties of the electrolyte is addressed. The study is then extended to Poly(Ethylene) Oxide (PEO)-LATP SCE. The presence of the ceramic particles conferred limited benefits to the SCE. These findings somewhat contradict commonly held assumptions on the role of ceramic additives in SCE.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.214
Teacher spread0.197 · 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

Citations16
Published2023
Admission routes2
Has abstractyes

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