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Record W2951399170 · doi:10.1016/j.elecom.2019.106483

Electrospun ceramic nanofibers as 1D solid electrolytes for lithium batteries

2019· article· en· W2951399170 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

VenueElectrochemistry Communications · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsHydro-QuébecInstitut National de la Recherche Scientifique
FundersHydro-QuébecNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsMaterials scienceFast ion conductorElectrolyteLithium (medication)CalcinationCeramicIonic conductivitySinteringFlammable liquidNanotechnologyElectrospinningChemical engineeringLithium metalLithium batteryIonic bondingIonComposite materialChemistryElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

All-solid-state lithium batteries (ASSLBs) are undoubtedly among the most promising technologies to replace conventional lithium-ion batteries. Their key component is a thin solid-state electrolyte, which is safer than its flammable liquid counterpart and enables the use of metallic lithium, thus ensuring high energy densities (over 500 W h kg -1 ). Several solid electrolytes are currently being investigated, such as NASICON-like materials, perovskites, and garnets. Typical techniques used to synthesize most such electrolytes still involve prolonged high-temperature calcination and sintering steps. An alternative approach is to couple electrospinning with the well-known sol-gel method to lower the temperatures and synthesis times and simultaneously exploit the benefits of using anisotropic nanostructured materials. In this review, we discuss advances in the synthesis of ceramic nanofibrous materials having high ionic conductivity and present our perspective regarding their potential application as electrolytes in ASSLBs.

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 categoriesMeta-epidemiology (narrow)
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 score0.054
Threshold uncertainty score1.000

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 science0.0010.000
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 head0.006
GPT teacher head0.241
Teacher spread0.235 · 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