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Record W4377294235 · doi:10.1016/j.heliyon.2023.e16506

Enhanced photocatalytic activity of Cu and Ni-doped ZnO nanostructures: A comparative study of methyl orange dye degradation in aqueous solution

2023· article· en· W4377294235 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHeliyon · 2023
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsUniversity of Alberta
FundersJashore University of Science and Technology
KeywordsMethyl orangePhotocatalysisAqueous solutionDegradation (telecommunications)Materials scienceDopingNanostructureChemical engineeringNuclear chemistryInorganic chemistryNanotechnologyChemistryCatalysisOrganic chemistryOptoelectronics

Abstract

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Heterogeneous photocatalysis has been considered one of the most effective and efficient techniques to remove organic contaminants from wastewater. The present work was designed to examine the photocatalytic performance of metal (Cu and Ni) doped ZnO nanocomposites in methyl orange (MO) dye degradation under UV light illumination. The wurtzite hexagonal structure was observed for both undoped/doped ZnO and a crystalline size ranging between 8.84 ± 0.71 to 12.91 ± 0.84 nm by X-ray diffraction (XRD) analysis. The scanning electron microscope (SEM) and energy dispersive X-ray (EDX) revealed the irregular spherical shape with particle diameter (34.43 ± 6.03 to 26.43 ± 4.14 nm) and ensured the purity of the individual elemental composition respectively. The chemical bonds (O–H group) and binding energy (1021.8 eV) were identified by Fourier transform infrared (FTIR) and X-ray photoelectron spectroscopy (XPS) results respectively. The bandgap energy was decreased from 3.44 to 3.16 eV when Ni dopant was added to the ZnO lattice. The comparative photocatalytic activity was observed in undoped and doped nanocomposites and found to be 76.31%, 81.95%, 89.30%, and 83.39% for ZnO, Cu/ZnO, Ni/ZnO, and Cu/Ni/ZnO photocatalysts, respectively, for a particular dose (0.210 g) and dye concentration (10 mg L −1 ) after 180 min illumination of UV light. The photocatalytic performance was increased up to 94.40% with the increase of pH (12.0) whereas reduced (35.12%) with an increase in initial dye concentration (40 mg L −1 ) using Ni/ZnO nanocomposite. The Ni/ZnO nanocomposite showed excellent reusability and was found 81% after four consecutive cycles. The best-fitted reaction kinetics was followed by pseudo-first-order and found reaction rate constant (0.0117 min −1 ) using Ni/ZnO nanocomposite. The enhanced photodegradation efficiency was observed due to decreases in bandgap energy and the crystalline size of the photocatalyst. Therefore, Ni/ZnO nanocomposite could be used as an emerging photocatalyst to degrade bio-persistent organic dye compounds from textile wastewater.

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.

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 score0.018
Threshold uncertainty score0.333

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 head0.061
GPT teacher head0.314
Teacher spread0.253 · 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