MétaCan
Menu
Back to cohort
Record W4324130177 · doi:10.1021/acsami.3c00186

Coordinatively Cross-Linked Binders for Silicon-Based Electrodes for Li-Ion Batteries: Beneficial Impact on Mechanical Properties and Electrochemical Performance

2023· article· en· W4324130177 on OpenAlexafffund
Lucas Huet, Driss Mazouzi, Philippe Moreau, Nicolas Dupré, Michaël Paris, Sébastien Mittelette, Danielle Laurencin, Thomas Devic, Lionel Roué, Bernard Lestriez

Bibliographic record

VenueACS Applied Materials & Interfaces · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsInstitut National de la Recherche Scientifique
FundersEuropean Regional Development FundNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceElectrodeElectrochemistrySiliconCarboxylateChemical engineeringCoatingFourier transform infrared spectroscopyPropylene carbonateComposite materialInorganic chemistryOrganic chemistryMetallurgyPhysical chemistry

Abstract

fetched live from OpenAlex

) into a preoptimized poly(carboxylic acids) binder solution is proposed. These binders lead systematically to a significantly improved electrochemical performance when used for the formulation of silicon-based negative electrodes. The formation of carboxylate-Zn(II) coordination bonds formation is investigated by rheology and FTIR and NMR spectroscopies. Mechanical characterizations reveal that the coordinated binder offers a better electrode coating cohesion and adhesion to the current collector, as well as higher hardness and elastic modulus, which are even preserved in the presence of a carbonate solvent (i.e., in battery operation conditions). Ultimately, as shown from operando dilatometry experiments, the electrode expansion during lithiation is reduced, mitigating electrode mechanical failure. Such coordinatively reticulated electrodes outperform their uncoordinated counterparts with an improved capacity retention of over 30% after 60 cycles.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0020.001

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 head0.026
GPT teacher head0.277
Teacher spread0.250 · 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 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

Citations9
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueACS Applied Materials & InterfacesSame topicAdvancements in Battery MaterialsFrench-language works237,207