Combined Electrochemical & Biological Treatment of Industrial Wastewater Using Porous Electrodes and a Packed Bed Aerator
Bibliographic record
Abstract
Zinc, nickel and propylene glycol methyl ether were simultaneously removed from simulated wastewater in a column containing a counter-current packed bed and an electrochemical cell. Rectangular porous aluminum foam cathode and porous stainless steel anode were used in a plate-in-tank configuration. During combined biological and electrochemical treatment the wastewater flux was 0.00183 and 0.00915 m³.m̈².s̈¹ at a constant volumetric air flux of 0.0518 m³.m̈².s̈¹. Over a 72 hour treatment period the BOD5 was reduced by 32% and 55% for each volumetric liquid flux, respectively; zinc was reduced by 98% for both fluxes, and nickel was reduced by 95% and 82%, respectively. For sole electrochemical treatment of 48 hours, laminar and turbulent flow conditions were studied. Operating in the laminar flow region of 0.00183 and 0.00915 m³.m̈².s̈¹; zinc was reduced by 95% for both fluxes; nickel was reduced by 80% and 60%, respectively. For the turbulent region in the electrochemical cell, the volumetric liquid fluxes were 0.0137, 0.0229, 0.0321 and 0.0366 m³.m̈².s̈¹. Per cent reduction of both zinc and nickel in this region was less than that encountered in laminar flow. For all the fluxes in the turbulent region zinc was reduced by 82%; nickel was reduced by 55% at a flux of 0.0137 m³.m̈².s̈¹ and 60% at a flux of 0.0366 m³.m̈².s̈¹. Increasing electrode surface area as a means of improving heavy metal reduction by using rectangular porous material in a plate-in-tank configuration is not a viable option at higher volumetric liquid fluxes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".