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Record W4290726815 · doi:10.1002/bte2.20220016

Transforming silicon slag into high‐capacity anode material for lithium‐ion batteries

2022· article· en· W4290726815 on OpenAlexafffund
Victor Vanpeene, Alexandre Heitz, Natalie Herkendaal, Patrick Soucy, Thierry Douillard, Lionel Roué

Bibliographic record

VenueBattery energy · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceAnodeAmorphous solidNanocrystalline materialElectrodeElectrolyteScanning electron microscopeChemical engineeringSiliconLithium (medication)Ball millLithium-ion batteryIonMetallurgyBattery (electricity)Composite materialNanotechnologyCrystallographyChemistry

Abstract

fetched live from OpenAlex

Abstract The conception of cheaper and greener electrode materials is critical for lithium (Li)‐ion battery manufacturers. In this study, a by‐product of the carbothermic reduction of SiO 2 to Si, containing 65 wt% Si, 31 wt% SiC, and 4 wt% C, is evaluated as raw material for the production of high‐capacity anodes for Li‐ion batteries. After 20 h of high‐energy ball milling, C is fully converted to SiC and a micrometric powder ( D 50 ∼1 μm) is obtained in which submicrometric SiC inclusions are embedded in a nanocrystalline/amorphous Si matrix. This material is able to maintain a capacity >1000 mAh g −1 (>3 mAh cm −2 ) over 100 cycles. No crystalline Li 15 Si 4 phase is formed upon cycling as shown from the differential dQ / dV curves. The good mechanical resiliency of the electrode is evidenced by monitoring its morphological changes from sequential focused ion beam scanning electron microscopy analyses. However, a progressive and irreversible increase in the electrode mass and thickness is observed over cycling (reaching 125% and 60% after 200 cycles, respectively), which is mainly attributed to the accumulation of solid electrolyte interphase products in the electrode.

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 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), Insufficient payload (model declined to judge)
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 score0.165
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.214
Teacher spread0.202 · 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 teacher head, not a consensus.

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

Citations14
Published2022
Admission routes2
Has abstractyes

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