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Record W2883022360 · doi:10.1680/jenes.18.00003

Polypyrrole- and polyaniline-supported TiO<sub>2</sub> for removal of pollutants from water

2018· article· en· W2883022360 on OpenAlexvenueno aff
Reza Katal, Mohammad Hossein Davood Abadi Farahani, Saeid Masudy‐Panah, Say Leong Ong, Jiangyong Hu

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2018
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsTitanium dioxidePhotocatalysisMaterials sciencePolypyrrolePolyanilinePhotodegradationChemical engineeringTitaniumAqueous solutionConductive polymerInorganic chemistryPolymerChemistryCatalysisOrganic chemistryComposite materialMetallurgyPolymerization

Abstract

fetched live from OpenAlex

In recent decades, the modification of titanium dioxide (TiO 2 ) as a well-known photocatalyst with different strategies, such as morphological change, doping and supported substrate, has been investigated. The main goals of the modification process can be described as (a) enhancing titanium dioxide performance and (b) providing a situation that uses titanium dioxide under visible or sunlight radiation. Different types of materials have been used for titanium dioxide support, among them polymers; in particular, polypyrrole (PPy) and polyaniline (Pan), that seem to be very effective due to considerable chemical and environmental stability in the aqueous phase. Meanwhile, by combining PPy and Pan with titanium dioxide, the energy of the band gap of supported titanium dioxide may be reduced and the photocatalytic process can be carried out under visible light illumination. This review demonstrates different strategies (their mechanisms and drawbacks) for enhancing titanium dioxide performance. In the field of PPy- and Pan-supported titanium dioxide, photocatalysts present a comprehensive study on their synthesis and application for removal of dye and organic pollutants. The effects of various parameters on the photocatalytic performance of PPy/titanium dioxide and Pan/titanium dioxide are also demonstrated. The main mechanisms of organic contaminants’ photodegradation by PPy/titanium dioxide and Pan/titanium dioxide in water (via an aqueous solution) are also investigated.

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 score0.010
Threshold uncertainty score0.328

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 head0.005
GPT teacher head0.208
Teacher spread0.203 · 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

Citations12
Published2018
Admission routes1
Has abstractyes

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