Photo-Fenton Catalyzed by Cu2O/Al2O3: Bisphenol (BPA) Mineralization Driven by UV and Visible Light
Bibliographic record
Abstract
This work aimed to demonstrate Cu2O/Al2O3 as a catalyst of the photo-Fenton process in the UV and visible spectra. Cu2O nanoparticles were synthesized by laser ablation in liquid and supported on Al2O3. The catalytic activity of the resulting solid was assessed in the mineralization of bisphenol A (BPA). The studied variables were type of Al2O3α and γ, Cu content (0.5 and 1%), and H2O2 concentration (1, 5, and 10 times the stoichiometric amount). The response variables were BPA concentration and total organic carbon (TOC) removal percentage. The presence of Cu2O nanoparticles (11 nm) with an irregular sphere-like shape was confirmed by transmission electron microscopy (TEM) and their dispersion over the catalytic surface was verified by energy-dispersed spectroscopy (EDS). These particles improve ·OH radical production, and thus a 100% removal of BPA is achieved along with ca. 91% mineralization in 60 min. The BPA oxidation rate is increased one order of magnitude compared to photolysis and doubles that for H2O2 + UV. An increase of 40% in the initial oxidation rate of BPA was observed when switching from α-Al2O3 to γ-Al2O3. 4-hydroxybenzaldehyde, 4-hydroxybenzoic acid, acetaldehyde, and acetic acid are the BPA oxidation by-products identified using LC/MS and based on this a reaction pathway was proposed. Finally, it was also concluded that the synthesized catalyst exhibits catalytic activity not only in the UV spectrum but also in the visible one under circumneutral pH. Therefore, Cu2O/Al2O3 can be recommended to conduct a solar photo-Fenton reaction that can degrade other types of molecules.
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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) | 0.000 | 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".