Effect of Ultrasound and Electrode Material on Electrochemical Treatment of Industrial Wastewater
Bibliographic record
Abstract
The effect of ultrasound (US) and electrode material on electrochemical treatment of industrial wastewater was studied. Samples were taken from three industries i.e. battery, ghee and tannery. Treatment efficiency was monitored by comparing the results of electrochemical and sonoelectrochemical processes in terms of metals and chemical oxygen demand COD removal. Experiments were performed in ultrasonic bath. In sonoelectrochemical process concentration of Pb decreased from 11.5 to 0.6 ppm at 80 kHz form battery industry. Similarly about 95 % removal of Cr (III) was observed from tannery wastewater using lead cathode. Titanium anode was found best counter electrode in metals removing. High COD removal was obtained by using steel anode at 80 kHz. Use of ultrasound is very effective in removing heavy metals and organic pollutants from industrial 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 | 0.001 |
| 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 | 0.001 | 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".