Catalytic degradation of methyl red using <scp>PZnW<sub>11</sub></scp>/<scp>m‐Go</scp> as a high‐performance photocatalyst
Bibliographic record
Abstract
Abstract In this research, zinc (II)‐substituted Keggin‐type polyoxometalate [(C4H9)4N] PZnW11O39 (PZnW11) was prepared and stabilized on the modified graphene oxide (m‐GO) for removal of methyl red (MR) dye from aqueous solution. The maximum dye degradation and significance of variables on the decolorization system in static conditions were determined using response surface methodology (RSM). The main variables affecting the decolorization performance on dye decolorization, including system temperature (25–40°C), catalyst amount (0.001–0.005 g), and irradiation time (5–25 min), were evaluated. The optimum temperature, catalyst applying amount, and irradiation time were identified as 35°C, 0.003 g, and 20 min, respectively, and the experimental dye removal value was 96.8%. The high regression coefficient between the response and the variables (R2 = 0.9335) showed a good investigation of the experimental results by regression‐based polynomial model. In comparison with the previously reported photocatalytic decolorization systems, the dye removal system suggested in this work is quick, easy and involves a small amount of catalyst. Polyoxometalate‐based photocatalyst (PZnW11/m‐GO) shows potent visible‐light photocatalytic activity for the decolorization of methyl red dye, due to the generates the strong oxidants hydroxyl radical (OH) and superoxide anion radical (O2−) via photoelectrochemical decomposition of H2O and O2 in the presence of visible light irradiation. Efficient decolorization and degradation of organic contaminants by synthesized catalyst PZnW11/m‐GO suggest its potential for real industrial applications in removal of synthetic dye wastewater.
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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) | 0.000 | 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".