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Record W2954526761 · doi:10.1002/cjce.23579

Preparation and electrochemical performance of uniform RuO<sub>2</sub>/Ti and RuO<sub>2</sub>‐IrO<sub>2</sub>/Ti electrode for electrolysis of NaCl solution

2019· article· en· W2954526761 on OpenAlexvenueno aff
Jie Ren, Yi‐Ling Liu, Li Feng, Chun‐Wei Liu

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsnot available
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsNational Natural Science Foundation of China
KeywordsElectrolysisElectrochemistryElectrodeMaterials scienceElectroplatingX-ray photoelectron spectroscopyChemical engineeringDeposition (geology)TitaniumInorganic chemistryAnalytical Chemistry (journal)ElectrolyteChemistryMetallurgyNanotechnologyPhysical chemistry

Abstract

fetched live from OpenAlex

The electrochemical preparation of NaClO has been widely used for the production of industrial disinfectant. To reduce the cost of electrode preparation using the brushing method, this paper introduces a method for the electrodeposition for RuO 2 /Ti and RuO 2 ‐IrO 2 /Ti preparation and NaCl solution electrolysis. The deposition of Ir improves the uniformity and stability of the RuO 2 /Ti electrode. The optimum preparation conditions and additive concentrations were investigated in detail through the orthogonal experiment. By adjusting the electroplating time, temperature and voltage, the electrode with a high content of available chlorine was synthesized successfully. The physicochemical properties of the as‐prepared RuO 2 /Ti and RuO 2 ‐IrO 2 /Ti were determined by XRD, SEM‐EDS, and XPS, and the electrochemical performance and lifetime of the RuO 2 /Ti and RuO 2 ‐IrO 2 /Ti was verified via an electrochemical workstation. Uniform and stable RuO 2 /TiO 2 and RuO 2 ‐IrO 2 /TiO 2 were synthesized successfully for the electrolysis of the NaCl solution.

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 score0.030
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.003
GPT teacher head0.177
Teacher spread0.174 · 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

Citations8
Published2019
Admission routes1
Has abstractyes

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