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Record W1501690652 · doi:10.5539/ijc.v7n2p39

Study Self-cleaning of Congo Red from Cotton Fabric Loaded by Zno-Ag

2015· article· en· W1501690652 on OpenAlexvenueno aff
Amjed Mirza Oda, Hameed Ali, Abbas J. Lafta, Hussein Esmael, Ali A. Jameel, Abbas Mohammed, Inas J. Mubarak

Bibliographic record

VenueInternational Journal of Chemistry · 2015
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsnot available
Fundersnot available
KeywordsCongo redFourier transform infrared spectroscopyZincChemistryScanning electron microscopePhotocatalysisNuclear chemistryChemical engineeringOxideDopingSilver oxideCatalysisComposite materialMaterials scienceAdsorptionOptoelectronicsOrganic chemistry

Abstract

fetched live from OpenAlex

The current work involves modification of zinc oxide by doping silver, this was achieved by photodeposition method. Modified zinc oxide was investigated using X-ray diffraction (XRD), fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). Both of ZnO and Ag doped ZnO was fabricated on a cotton texture. The photocatalytic activity of these materials was investigated by following the decolorization of congo red from simulated industrial wastewater. The decolorization of congo red over fabricated-ZnO-Ag was more efficient in comparison with non- fabricated catalysts. Different reaction parameters were undertaken including the effect of pH of the solution, irradiation time and the effect of light intensity. Complete dye removal over fabricated materials took three hours while it took 4.5 for non-fabricated materials.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.016
GPT teacher head0.256
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 source (direct Gemma or distilled Codex), 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

Citations12
Published2015
Admission routes1
Has abstractyes

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