Spectral Analysis of Catalytic Oxidation and Degradation of Bromophenol Blue at Low pH with Potassium Dichromate
Bibliographic record
Abstract
Abstract This research investigated the efficacy of potassium dichromate (K2Cr2O7), ultraviolet (UV) solar irradiation and UV in combination with two diprotic acid i-e sulphuric and oxalic acid (UV chromate/carbonate), for decolorizing bromophenol blue (BPB). The results suggested that alone UV and solar exposure was the poor decolorizer of the dye waste water. Up to 10% color removal with alone UV and solar treatment were achieved which indicated that, only solar and UV were not effective for dye removal even though UV was slightly more effective as compared to solar one. The decline reaction rate was observed as a result of increased concentration of dye. Increase in concentration of dichromate showed two peaks at 592 and 515 which showed that bromophenol degraded into two smaller components through complex formation. Addition of sodium carbonate as a catalyst in dye chromate-oxalate system found to be effective in degradation of BPB with reduced time period. The reaction was rapid and almost maximum of the dye converted into CO2. Research outcome suggests that chromate-oxalate system is very effective techniques for reducing color of dye waste water for safety of aquatic environment. Reaction pathway of oxidation of BPB is discussed in the relevant section of the paper.
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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".