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Record W3132203218 · doi:10.3390/polym13040631

Polymer Binders: Characterization and Development toward Aqueous Electrode Fabrication for Sustainability

2021· review· en· W3132203218 on OpenAlexafffund
Aleksander Cholewinski, Pengxiang Si, Marianna Uceda, Michael A. Pope, Boxin Zhao

Bibliographic record

VenuePolymers · 2021
Typereview
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceCharacterization (materials science)Aqueous solutionNanotechnologyPolymerElectrodeEnergy storageSustainabilityProcess engineeringComposite materialChemistryOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Binders play an important role in electrode processing for energy storage systems. While conventional binders often require hazardous and costly organic solvents, there has been increasing development toward greener and less expensive binders, with a focus on those that can be processed in aqueous conditions. Due to their functional groups, many of these aqueous binders offer further beneficial properties, such as higher adhesion to withstand the large volume changes of several high-capacity electrode materials. In this review, we first discuss the roles of binders in the construction of electrodes, particularly for energy storage systems, summarize typical binder characterization techniques, and then highlight the recent advances on aqueous binder systems, aiming to provide a stepping stone for the development of polymer binders with better sustainability and improved functionalities.

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)0.001
metaresearch head score (Gemma)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.059
GPT teacher head0.335
Teacher spread0.276 · 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
GenreReview

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

Citations132
Published2021
Admission routes2
Has abstractyes

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