MétaCan
Menu
Back to cohort
Record W3025922600 · doi:10.1149/ma2020-011112mtgabs

A Bispyridinylidene Anolyte for an All-Organic Redox Flow Battery

2020· article· en· W3025922600 on OpenAlexaff
Fahad Alkhayri, C. Adam Dyker

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsRedoxFlow batteryRenewable energyChemistryEnergy storageAnodeAqueous solutionOrganic radical batteryFossil fuelCathodic protectionChemical engineeringInorganic chemistryElectrochemistryPower (physics)Organic chemistryElectrolyteElectrodeElectrical engineeringThermodynamics

Abstract

fetched live from OpenAlex

Global warming associated with CO 2 emissions caused by the excessive use of fossil fuels has become a worldwide concern. The use of renewable energy resources as an alternative power source can help reduce the amount of CO 2 in air. Redox flow batteries (RFBs) have attracted a lot of attention recently as promising systems for energy storage from intermittent renewable resources and to allow integration with the power grid. Most RFBs are based on metallic active species in aqueous media, however there is a growing interest around the use of soluble organic redox couples in non-aqueous solvents to achieve higher energy density. Organic compounds with high redox potentials (catholyte) are readily available, but new organic compounds that undergo multi-electron redox processes at a low redox potential (anolyte) are needed to boost the energy density of RFBs. This presentation will outline efforts to demonstrate a new bispyridinylidene-based anolyte that undergoes a reversible two-electron oxidation (-1.69 V vs. ferrocene) and assess its applicability in a RFB. In addition to stability tests for the bispyridinylidene, an all-organic non-aqueous RFB employing 2,2,6,6-tetramethyl-1-piperidinyloxy and bispyridinylidene as cathodic and anodic active materials, respectively has been investigated.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.167
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
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 head0.037
GPT teacher head0.276
Teacher spread0.239 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueECS Meeting AbstractsSame topicAdvanced battery technologies researchFrench-language works237,207