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Record W3123338790 · doi:10.1002/cjce.24033

Study on the preparation, characterization, and electrocatalytic performance of <scp>Gd</scp> ‐doped <scp> PbO <sub>2</sub> </scp> electrodes

2021· article· en· W3123338790 on OpenAlexvenueno aff
Yuhan Diao, Feng Wei, Liman Zhang, Yang Yang, Yingwu Yao

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsMaterials scienceOverpotentialElectrodeElectrochemistryScanning electron microscopeDopingDegradation (telecommunications)Chemical engineeringAnalytical Chemistry (journal)Composite materialChemistryOptoelectronicsPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract In this work, Gd‐doped PbO 2 electrodes were prepared by electrodeposition procedure. In the accelerated life test, the service life of Gd‐doped PbO 2 electrodes are more stable and durable. Scanning electron microscope and x‐ray diffraction tests reveal that Gd‐doped PbO 2 electrodes have more compact structure and finer grain size. Electrochemical measurements and fluorescence experiments show that Gd‐doped PbO 2 electrodes have higher oxygen evolution overpotential, a larger electrochemically active surface area, and stronger ability to generate hydroxyl radicals. The electrocatalytic performance of the Gd‐doped PbO 2 electrode for the electrochemical degradation of thiamethoxam was studied. The degradation process accorded with pseudo‐first‐order kinetics, with higher thiamethoxam and total organic carbon removal capabilities, as well as higher mineralization current efficiency and lower energy consumption. In the degradation process, it has favourable reusability. The experimental results demonstrate that Gd‐doped PbO 2 electrodes have an excellent treatment effect and a wider application prospect in the field of pollutant degradation.

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 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 score0.014
Threshold uncertainty score0.424

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 head0.006
GPT teacher head0.187
Teacher spread0.180 · 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.

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

Citations9
Published2021
Admission routes1
Has abstractyes

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