MétaCan
Menu
Back to cohort
Record W4412438922 · doi:10.1016/j.fub.2025.100092

A tert-butyl functionalized quinone as active material for rechargeable aqueous zinc-ion batteries exhibiting high round-trip efficiency

2025· article· en· W4412438922 on OpenAlexaff
Alejandra Ibarra Espinoza, Thomas James Baker, Storm Gourley, Caio M. Miliante, Kevin J. Sanders, Gillian R. Goward, Oleg Rubel, Brian D. Adams, Drew Higgins

Bibliographic record

VenueFuture Batteries · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsMEG-3 (Canada)McMaster University
Fundersnot available
KeywordsAqueous solutionZincQuinoneIonMaterials scienceInorganic chemistryChemistryMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

The implementation of renewable electricity into the grid requires efficient grid-energy storage systems for balancing supply and demand. Rechargeable zinc-ion batteries (ZIBs) are a low-cost, safe option for grid energy storage; however, challenges pertaining to energy storage capacity, round-trip efficiency, stability, and reliance on critical minerals still need to be addressed. Herein, 3,5-di-tert-butyl-ortho-benzoquinone (TBOBQ) was evaluated as an organic cathode material for ZIBs, achieving a maximum theoretical specific capacity of 246 mAh/g at 40 mA/g (C/4) with a 1 to 1 mass ratio of TBOBQ-to-acetylene black. The observed charge and discharge curves presented a voltage hysteresis of only 100 mV, resulting in a round-trip efficiency of 90%. Degradation of the TBOBQ cathode was attributed to fractional dimerization and dissolution during discharge, as observed by nuclear magnetic resonance, mass spectroscopy, and rotating ring disk electrode. This work sets the stage for the development of organic ZIB cathodes based on TBOBQ with high discharge capacities and energy efficiency.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.237
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.255
Teacher spread0.246 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueFuture BatteriesSame topicAdvanced battery technologies researchFrench-language works237,207