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Record W4387401372 · doi:10.5267/j.ccl.2023.6.003

Photocatalytic degradation of Orange-II by surfactant assisted Mn/Mg co-doped TiO2 nanoparticles under visible light irradiation

2023· article· en· W4387401372 on OpenAlexvenueno aff
Sankara Rao Miditana, T. Siva Rao, Imandi Manga Raju, Shaik Abdul Alim

Bibliographic record

VenueCurrent Chemistry Letters · 2023
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsnot available
Fundersnot available
KeywordsPhotocatalysisAnataseChemistryDopantNanomaterialsNanoparticlePhotoluminescenceMethyl orangeNuclear chemistryPhotochemistryVisible spectrumDopingInorganic chemistryCatalysisNanotechnologyMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

In this research, the photocatalytic effect was studied for sol-gel synthesized Mn/Mg co-doped metal oxide (TiO2) nanoparticles (NPs), which are encapsulated with anionic Gemini surfactant. The physicochemical properties of Mn/Mg co-doped TiO2 were investigated using a variety of characterization techniques, FT-IR, UV Vis-DRS, XRD, SEM, EDX, TEM, BET and PL. Characterization results reveal that Mn/Mg dopants stabilize TiO2 in the form of anatase phase and reduce the bandgap energy. Presence of strong chemical bonding and functional groups at the interface of dopant and TiO2 NPs was confirmed with FT-IR. The photocatalytic activity of these catalysts was assessed by the degradation of Orange II (AO7) using visible light irradiation. Of the variable nanomaterials MMT5-GS2 showed remarkable results. The photoluminescence studies revealed that OH radicals are the reactive species and responsible for oxidative photocatalytic degradation of Orange II.

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)0.0000.000

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 head0.024
GPT teacher head0.264
Teacher spread0.239 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

Explore more

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