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Record W4398180211 · doi:10.1080/24701556.2024.2354485

Photocatalytic activity and electrochemical properties of a ternary-based-TiO <sub>2</sub> nanocomposite

2024· article· en· W4398180211 on OpenAlexaff
Mabrouka Ghiloufi, Beyram Trifi, Saloua Kouass Sahbani, Ouassim Ghodbane, Fathi Touati, Hassouna Dhaouadi, Salah Kouass

Bibliographic record

VenueInorganic and Nano-Metal Chemistry · 2024
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPhotocatalysisNanocompositeTernary operationElectrochemistryMaterials scienceChemical engineeringNanotechnologyChemistryCatalysisElectrodePhysical chemistryOrganic chemistryComputer science

Abstract

fetched live from OpenAlex

A TiO2 photocatalyst modified with g-C3N4 and different wt% of CuO, is performed via hydrothermal method. The structural, morphological and spectroscopic characterizations are carried out. The ternary composite, g-C3N4/CuO/TiO2, exhibits greater photocatalytic activity than CuO/TiO2. The highest degradation of Levofloxacin reaches 99% and 44%, after 10 and 60 min UV irradiation over ternary and binary composites for 20 wt% of CuO, respectively, with a concentration of 5.10−3 g/L of LEVO and a photocatalyst mass of 2.10−2 g. The stability of g-C3N4/CuO/TiO2 is confirmed allowing its reuse for five successive cycles with a longer treatment time. Under solar irradiation, the degradation yield of Levo using g-C3N4/CuO/TiO2 is 100% after only 20 min. The as-synthesized nanocomposite present interesting electrochemical properties. In the medium-frequency region, the diameter of the semicircle for the g-C3N4/CuO/TiO2 electrode is much smaller than that of the CuO/TiO2 electrode, indicating a lower charge-transfer resistance.

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 score0.002
Threshold uncertainty score0.003

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 head0.006
GPT teacher head0.211
Teacher spread0.205 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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