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Enhanced Oxygen Evolution Reaction Performance of ZnO Nanorods on Activated Carbon Cloth

2025· article· en· W4408578188 on OpenAlexafffund
Chandra Prakash, Ula Suliman, Sadegh Pour-Ali, Ambesh Dixit, Jing Liu, Shiva Mohajernia

Bibliographic record

VenueEnergy & Fuels · 2025
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Alberta
FundersScience and Engineering Research BoardNatural Sciences and Engineering Research Council of CanadaAlberta Innovates
KeywordsNanorodCarbon fibersOxygenChemical engineeringOxygen evolutionMaterials scienceActivated carbonNanotechnologyChemistryAdsorptionComposite materialPhysical chemistryComposite numberOrganic chemistry

Abstract

fetched live from OpenAlex

The employment of an abundant and cost-effective electrocatalyst for water splitting gained significant attention, as there is a need for a substitute for precious metals in the production of affordable H 2 as a promising energy carrier. This study addresses the need for cost-effective, high-activity, and binder-free oxygen evolution reaction (OER) electrocatalysts by investigating ZnO nanorods (ZnO NRs) integrated with electrochemically activated carbon cloth (ECAT@CC). Various characterization techniques, including XRD, XPS, and FE-SEM, confirmed the formation of ZnO NRs on ECAT@CC during conventional hydrothermal synthesis in an aqueous solution containing (CH 3 COO) 2 Zn·2H 2 O and C 6 H 12 N 4 at 95 °C. The electrochemical performance was evaluated using linear sweep voltammetry, chronopotentiometry, and electrochemical impedance spectroscopy in alkaline conditions. The ZnO NRs/ECAT@CC annealed for 3 h at 450 °C exhibited superior OER activity, with an overpotential of 1.58 V vs RHE at a current density of 10 mA/cm 2, and improved charge transfer resistance of 65.89 Ω·cm 2, significantly lower than that of pristine and ECAT@CC samples. During the stability test, the robustness of the ZnO NRs/ECAT@CC-3h sample was demonstrated over the prolonged operation. This research highlights ZnO NRs/ECAT@CC-3h as a promising, binder-free, and self-supported OER electrocatalyst, which can contribute to more efficient and sustainable processes in electrochemical water splitting.

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 score0.004

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)0.0010.000

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 head0.005
GPT teacher head0.210
Teacher spread0.205 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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