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Record W3024413671 · doi:10.1149/ma2020-01124mtgabs

(Invited) Deep Analysis of Lithium Metal Anodes for Rechargeable Batteries

2020· article· en· W3024413671 on OpenAlexaff
Patrick Bouchard, Abdelbast Guerfi, Kim Chisu, M Cho, Michel L. Trudeau, Karim Zaghib

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsLithium metalLithium (medication)ElectrolyteMaterials scienceAnodeRaman spectroscopyX-ray photoelectron spectroscopyIonic conductivityElectrodeMetalNanotechnologyChemical engineeringMetallurgyChemistryEngineering

Abstract

fetched live from OpenAlex

The commercial use of lithium metal batteries was delayed because of dendrite formation on the surface of the lithium electrode, and the difficulty finding a suitable electrolyte that has both the mechanical strength and ionic conductivity required for solid electrolytes. Recently, strategies have developed to overcome these difficulties, so that these batteries are currently an option for different applications, including electric cars. Deep analysis of lithium metal by XPS, In situ SEM, SEM, TEM and Raman spectroscopy will be showed. In this work, we review these strategies, and discuss the different routes that are promising for progress in the near future.

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: Other · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.008

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 head0.257
Teacher spread0.227 · 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
GenreOther

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

Citations0
Published2020
Admission routes1
Has abstractyes

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