Facile green synthesis of highly efficient carbon nanospheres@g-C3N4 catalysts for photodegradation of Bisphenol A
Bibliographic record
Abstract
Novel Carbon nanospheres@graphitic-carbon nitride nanocomposites were successfully synthesized by a simple, inexpensive and ecofriendly chemical method (hydrothermal). The as-prepared materials Carbon nanospheres (CNS), pure g-C 3 N 4 , CNS@g-C 3 N 4 and heat treated (HT)CNS@g-C 3 N 4 were characterized by FTIR, Raman spectroscopy , XPS, XRD , TEM, EDX and N 2 -adsorption desorption, UV-Visible DRS , and Photoluminescence (PL). The photodegradation of bisphenol A (a typical endocrine disruptor) using photocatalysts was followed by HPLC-UV technique. The results show that (HT)CNS@g-C 3 N 4 exhibits high photocatalytic efficiency for BPA degradation (99 %), which is 45 and 8.5 times greater than that of pure g-C 3 N 4 and CNS@g-C 3 N 4 , respectively. Additionally, the (HT)CNS@g-C 3 N 4 photocatalyst displays a high constant rate of apparent pseudo-first-order (k app = 94.78 × 10 −3 min –1 ) and low electrical energy per order consumption (EEO = 0.24 kWh/m 3 ). These excellent abilities of (HT)CNS@g-C 3 N 4 were attributed to its excellent morphological, structural and optical properties induced during the heat treatment: ( i ) The presence of CNS reduces the bad gap and consequently enhances the absorption of visible light and promotes the charge carriers separation, (ii) the high specific surface area and porosity and therefore availability of a high number of active sites to interact with BPA, ( iii ) high presence of different functional groups on the catalyst surface that enhance the interaction between the surface and BPA molecules, and ( iv ) The heterojunction interface created between CNS and g-C 3 N 4 constitutes an efficient structure that enhances interfacial charge transfer and prevents direct recombination of charge carriers originating from g-C 3 N 4 . Based on the identification of the products and intermediates of the BPA photodegradation reaction, by HPLC−MS, a plausible mechanism of photocatalytic degradation of BPA using the prepared photocatalysts was proposed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".