Optimization of photocatalytic degradation conditions and toxicity assessment of norfloxacin under visible light by new lamellar structure magnetic ZnO/g-C3N4
Bibliographic record
Abstract
Degradation of norfloxacin (NFX) by zinc oxide (ZnO)/g-C3N4, a magnetic sheet ZnO with g-C3N4 on its surface was studied. Through a new preparation system method, hydrothermal reaction provides a solid-layered magnetic ZnO material basis, and the simple thermal condensation method was used to transform the urea into g-C3N4 on the magnetic sheet ZnO in a uniform and orderly manner to increase the stability and photocatalytic performance of the material. Compared with previous studies, the pore volume and photocatalytic performance of the material are improved, and became more stable. By studying the degradation effect of basic and photocatalytic materials prepared in different proportions, the kinetic constant of ZGF is 0.01446 (min−1). The response surface methodology (RSM) was used to study the optimization and effect of solution pH (4−12), photocatalyst concentration (0.2–1.8 g/L), and NFX concentration (3–15 mg/L) on the degradation rate of NFX during photocatalytic degradation. The R2 value of the RSM model was 0.9656. The NFX removal rate is higher than 90% when the amount of catalyst is 1.43 g/L, the solution pH is 7.12, and the NFX concentration is less than 8.61 mg/L. After 5 cycles, the degradation rate of magnetic materials decreased to 92.8% of the first time. The capture experiment showed that the photocatalytic machine Toxicities was mainly hole action. The TOC removal rate within 2 h was 30%, a special intermediate toxicity analysis method was adopted according to the characteristics of NFX's inhibitory effect on Escherichia coli community. The toxicity of degraded NFX solution disappeared, and the possibility of non-toxic harm of by-products was verified. LC-Q-TOF method was used to detect and analyze various intermediate products converted from NFX after photocatalytic degradation, and the photocatalytic degradation pathway of NFX was proposed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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 teacher head, 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".