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Record W2947357807 · doi:10.1021/acsami.9b02675

Interface in Solid-State Lithium Battery: Challenges, Progress, and Outlook

2019· article· en· W2947357807 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

VenueACS Applied Materials & Interfaces · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaDeutsche ForschungsgemeinschaftUniversity of CalgaryAlexander von Humboldt-Stiftung
KeywordsMaterials scienceInterface (matter)Lithium (medication)Solid-stateBattery (electricity)Lithium metalNanotechnologyEngineering physicsSystems engineeringEngineeringComposite materialPower (physics)Thermodynamics

Abstract

fetched live from OpenAlex

All-solid-state batteries (ASSBs) based on inorganic solid electrolytes promise improved safety, higher energy density, longer cycle life, and lower cost than conventional Li-ion batteries. However, their practical application is hampered by the high resistance arising at the solid-solid electrode-electrolyte interface. Although the exact mechanism of this interface resistance has not been fully understood, various chemical, electrochemical, and chemo-mechanical processes govern the charge transfer phenomenon at the interface. This paper reports the interfacial behavior of the lithium and the cathode in oxide and sulfide inorganic solid-electrolytes and how that affects the overall battery performance. An overview of the recent reports dealing with high resistance at the anodic and cathodic interfaces is presented and the scientific and engineering aspects of the approaches adopted to solve the issue are summarized.

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 score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.001

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 head0.011
GPT teacher head0.245
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