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Record W4283704739 · doi:10.3390/catal12070709

Palladium and Graphene Oxide Doped ZnO for Aqueous Acetamiprid Degradation under Visible Light

2022· article· en· W4283704739 on OpenAlexafffund
Carolina Sayury Miyashiro, Safia Hamoudi

Bibliographic record

VenueCatalysts · 2022
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversité LavalCentre in Green Chemistry and Catalysis
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhotodegradationMaterials sciencePhotocatalysisAcetamipridAqueous solutionVisible spectrumPalladiumDopingGrapheneOxidePhotochemistryNuclear chemistryChemical engineeringNanotechnologyChemistryCatalysisPesticideOrganic chemistryOptoelectronicsMetallurgy

Abstract

fetched live from OpenAlex

Acetamiprid is a neonicotinoid insecticide widely used in pest control. In recent years, it has been considered as a contaminant in groundwater, lakes, and rivers. Photocatalysis under visible light radiation proved to be an effective process for getting rid of several organic pollutants. In the present work, photodegradation of aqueous acetamiprid was investigated over bare zinc oxide (ZnO) photocatalyst as well as ZnO doped with either palladium or palladium combined with graphene oxide. Both ZnO and doped-ZnO were synthesized via a microwave-assisted hydrothermal procedure. The obtained photocatalysts were characterized using different techniques. After 5 h of reaction at ambient temperature under visible light irradiation, acetamiprid conversions attained ca. 38, 82, and 98% in the presence of bare ZnO, Pd-doped ZnO and Pd-GO-doped ZnO photocatalysts, respectively, thus demonstrating the positive effect of Pd- and GO-doping on the photocatalytic activity of ZnO. In addition, Pd-GO-doped ZnO was shown to keep its activity even when it is recycled five times, thus proving its stability in the reaction medium.

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 score0.031
Threshold uncertainty score0.449

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 head0.022
GPT teacher head0.236
Teacher spread0.214 · 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

Citations15
Published2022
Admission routes2
Has abstractyes

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