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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.003
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

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)0.0000.000

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