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Record W4313235977 · doi:10.14447/jnmes.v25i4.a03

Water Oxidation for Anodic Generation of Hydrogen Peroxide by Using Transition Metal Oxide Based Catalyst

2022· article· en· W4313235977 on OpenAlexvenueno aff
A.I.A Alzahrani, S.U. Hassan, M.H. Nazir, Amna Zafar, S.Z.J. Zaidi

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2022
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsnot available
Fundersnot available
KeywordsHydrogen peroxideElectrolysisElectrochemistryInorganic chemistryCatalysisOxideAnodeElectrolysis of waterTransition metalChemistryMaterials scienceCoatingElectrodeHydrogenChemical engineeringMetallurgyNanotechnologyOrganic chemistryPhysical chemistryElectrolyte

Abstract

fetched live from OpenAlex

Water oxidation could be helpful to have a generation of useful oxidant known as hydrogen peroxide (H2O2) via electrochemical route. A defined structured of molybdenum oxide based electrode was synthesised by a thermal compression treatment over PV-15 composite coating. The coating was then employed for electrochemical water splitting at constant potential electrolysis while the quantities of peroxide of hydrogen produced was measured in an advanced type of cell assembly. The overall findings showed that the confined values of applied potential for H2O2 production are anodic constant potentials of +0.3 V, +0.4 V and +0.5 V vs. Hg/HgO and synthesised peroxide of hydrogen up to 13 ppm in an advanced type of cell assembly.

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 score0.001
Threshold uncertainty score0.003

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 integrity0.0000.001
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 head0.021
GPT teacher head0.237
Teacher spread0.216 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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