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Record W4303700000 · doi:10.3390/catal12101184

Facile Synthesis of ZnSe/Co3O4 Heterostructure Nanocomposites for the Photocatalytic Degradation of Congo Red Dye

2022· article· en· W4303700000 on OpenAlexaff
Adeel Zia, Abdul Basit Naveed, Aftab Javaid, Muhammad Fahad Ehsan, Azhar Mahmood

Bibliographic record

VenueCatalysts · 2022
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsCape Breton University
Fundersnot available
KeywordsPhotocatalysisMaterials scienceNanocompositeCrystallinityCongo redHeterojunctionChalcogenideAbsorption edgeVisible spectrumBand gapChemical engineeringOxideHydrothermal circulationAbsorption (acoustics)SuperstructureNanotechnologyOptoelectronicsChemistryComposite materialCatalysisMetallurgyAdsorptionOrganic chemistry

Abstract

fetched live from OpenAlex

In the present paper, simple hydrothermal and solid-state methods are reported for the synthesis of metal chalcogenide (ZnSe), metal oxide (Co3O4) and their nano-heterostructure (ZnSe/Co3O4 3:1, 1:1 and 1:3 ratios by weight), while their photocatalytic efficiencies are also investigated. The X-ray diffraction results corroborate the good crystallinity and purity of all synthesized products, i.e., ZnSe, Co3O4 and their nanocomposites. The scanning electron micro-images of ZnSe show a mixed morphology of nanoparticles (≈16 nm), including spherical and distorted cubes, while Co3O4 has a worm-like morphology (≈20 × 50 nm). The EDX results show that all the elements are present in accordance with their anticipated amounts in the products. The UV/visible absorption spectrum of ZnSe depicts a sharp absorption at around 480 nm, while Co3O4 demonstrates two prominent peaks, 510 nm and 684 nm. The prepared samples were employed for the photocatalytic degradation of Congo red dye and the nano-heterostructure (ZnSe/Co3O4 3:1) shows an exceptional photocatalytic degradation efficiency of 96%. This enhanced photocatalytic activity was due to the synergic effect of ZnSe and Co3O4 that reduced the electron/hole recombination and caused suitable bandgap alignment.

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 score0.019
Threshold uncertainty score0.744

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 science0.0010.000
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 head0.014
GPT teacher head0.254
Teacher spread0.240 · 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

Citations17
Published2022
Admission routes1
Has abstractyes

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