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Record W4410551697 · doi:10.1002/batt.202500161

Adenine and D‐Ribose Coderived Activated Carbon with N‐Methyl‐2‐Pyrrolidone‐Modified Aqueous Electrolyte for Long‐Life Zinc‐Ion Capacitors

2025· article· en· W4410551697 on OpenAlexafffund
Li Tao, Xuejun Lu, Rameez Ahmad Mir, Nieves López‐Salas, Jian Liu

Bibliographic record

VenueBatteries & Supercaps · 2025
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsWestern UniversityUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaCanada Foundation for Innovation
KeywordsAqueous solutionElectrolyteChemistryZincActivated carbonInorganic chemistryIonElectrolytic capacitorRiboseNuclear chemistryOrganic chemistryElectrodePhysical chemistryAdsorption

Abstract

fetched live from OpenAlex

Aqueous zinc (Zn)‐ion capacitors (AZICs) have addressed considerable attention due to their high energy density, low toxicity, and rich abundance of Zn metal. However, the development of ultra‐long cycle life and high energy density AZICs is often hindered by the lack of adequately optimized active carbon (AC) electrodes and compatible electrolytes. Herein, high‐performance, free‐standing AC electrodes for AZICs are derived from sustainable precursors—adenine and D‐ribose—using magnesium chloride hexahydrate as an activation agent via a eutectic template strategy. Furthermore, an aqueous hybrid electrolyte tailored to the designed AC electrodes is developed, significantly enhancing the stability and cycle life of AZICs. The resulting AZIC achieves a high specific capacity of 164.39 F g −1 at 0.1 A g −1 and a magnificently long cell life of over 50 000 cycles with nearly 94.5% capacitance retention at 10 000 th cycles, and 76.3% at 50 000 th cycle. The pouch cell assembly also demonstrates comparable specific capacitance and energy density to the coin cell, underscoring the potential of large‐scale applications of AZICs.

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)
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 score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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