Electrokinetic Flotation of Process Water from Paint Booths
Bibliographic record
Abstract
Abstract Electrokinetic flotation (EKF) for separation of paint solids and process water from automotive assembly paint booths was investigated in a series of laboratory-scale batch experiments. The EKF process employs a single electrode-module and a DC (direct current) power supply, but does not use any chemical agents or air supplier. The electrode-module, which consists of parallel electrode plates, was developed and used in the experiments. The influencing parameters of the EKF process for the process water treatment, including the type of paint, initial suspended paint solids (SS) concentration, and applied electric current, were investigated in the experimental program. It was found from this study that the EKF process decreased the SS concentration from 300 to 100 mg/L in 30 minutes at 55 A/m2 in the water-borne paint water, from 150 to 50 mg/L in 5 minutes at 22 A/m2 in the solvent-borne paint water, and from 550 to 100 mg/L in 5 minutes at 44 A/m2 in the mixed paint water, as well as reduced colour and chemical oxygen demand (COD). The study concluded that paint type, initial SS concentration, and electric current are the most important parameters in the EKF process governing the effectiveness of solid/water separation, treatment time, and power consumption. A comparison of SS removal between the chemical coagulation and the EKF treatments showed that SS removal by the EKF process was similar to the chemical treatment. The study concluded that the EKF is an effective technique for solid/water separation in paint booths with simultaneous COD and colour removal.
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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 | 0.003 | 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 | 0.001 |
| 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 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".