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Record W3089105587 · doi:10.1002/eom2.12055

Design strategies for organic carbonyl materials for energy storage: Small molecules, oligomers, polymers and supramolecular structures

2020· article· en· W3089105587 on OpenAlex
So Young An, Tyler B. Schon, Bryony T. McAllister, Dwight S. Seferos

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEcoMat · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBattery (electricity)Materials scienceEnergy storageOrganic radical batteryNanotechnologyElectrochemistryElectrochemical energy storageSupramolecular chemistryElectrolyteEnvironmentally friendlyPolymerElectrodeOrganic moleculesMoleculeSupercapacitorOrganic chemistryChemistryComposite material

Abstract

fetched live from OpenAlex

Abstract Organic electrodes are attractive candidates for electrochemical energy storage devices because they are lightweight, inexpensive and environmentally friendly. In recent years, many researchers have focused on the development of carbonyl‐containing materials for organic electrodes. These materials demonstrate promising results as the next generation of rechargeable batteries owing to their fast redox kinetics and structural diversity in design. However, these electrodes still exhibit intrinsic drawbacks such as solubility in battery electrolytes and low electrical conductivity. This review provides recent examples of organic carbonyl‐containing electrodes that highlight strategies to overcome these inherent limitations, and pave the way to develop an organic rechargeable battery that has high‐energy density and long cycle life. image

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.

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 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: none
Teacher disagreement score0.829
Threshold uncertainty score0.939

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)0.0000.000

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 head0.020
GPT teacher head0.232
Teacher spread0.212 · 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