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Record W4384028741 · doi:10.1021/acsenergylett.3c00969

Ester-Substituted Bispyridinylidenes: Double Concerted Two-Electron Bipolar Molecules for Symmetric Organic Redox Flow Batteries

2023· article· en· W4384028741 on OpenAlexafffund
Md Al Raihan, C. Adam Dyker

Bibliographic record

VenueACS Energy Letters · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaNew Brunswick Innovation Foundation
KeywordsRedoxElectrolyteSolubilityChemistryFaraday efficiencyMoleculeMaterials scienceChemical physicsInorganic chemistryOrganic chemistryPhysical chemistryElectrode

Abstract

fetched live from OpenAlex

Organic redox-active molecules are promising materials for charge storage in redox-flow batteries (RFBs); however, the development of all-organic RFBs is hindered by material crossover, limited energy density, and poor stability of active materials. Here, ester-substituted bispyridinylidenes are reported as the first examples of intrinsic bipolar molecules that exhibit basically concerted double two-electron redox activity at a potential difference of 1.01 V. All three oxidation states of the pentylester derivative exhibited excellent temporal stability and good solubility in the electrolyte. Testing this active material in symmetric cells, which alleviates crossover issues, revealed good cyclability (fade of 0.025% and 0.35% per cycle for static and flow cells, respectively), capacities of up to 89% of the theoretical value, and Coulombic efficiencies above 99%. Considering previous evidence for active material solubility limits of ∼2 M, and the benefits of a symmetric design, such double concerted multielectron bipolar active materials will be key to developing energy dense organic RFBs.

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 score0.007

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.016
GPT teacher head0.255
Teacher spread0.238 · 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

Citations13
Published2023
Admission routes2
Has abstractyes

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