Antimicrobial performance of microstructured metal materials in water and wastewater: proof-of-concept and scale-up
Bibliographic record
Abstract
It is necessary to disinfect treated wastewater prior to discharge to reduce exposure risks to humans and the environment. The currently practiced wastewater disinfection technologies are challenged by toxic by-products, chemicals, and energy demand, a range of effectiveness limitations, among other concerns. An effective, eco-friendly, and energy-efficient alternative disinfection technique is desirable to modernize and enhance wastewater treatment operations. Copper and nickel micro-structured metal foams, and a conventional copper mesh, were evaluated as disinfecting surfaces for treating secondary-treated wastewater contaminated with coliform bacteria. The micro-structured copper foam was adopted for antiviral and scale-up study due to its stable and satisfactory antimicrobial performance obtained over a wide range of bacterial concentrations and metal-to-liquid ratios. Three scales of experiments, using two types of reactor designs, were performed using municipal wastewater to determine the optimal scale-up factors: small lab-scale batch reactor, intermediate lab-scale batch reactor, and pilot-scale continuous tubular reactor experiments. The performance was evaluated with the aim of minimizing metal material requirements with respect to bactericidal efficiency and leaching risks at all scales. Copper foam, at or above optimal conditions, consistently inactivated over 95 % of total coliforms, fecal coliforms, and E.coli in wastewater at various scales, and leachate copper concentrations were determined to be below Canadian guideline values for outfall. Furthermore, copper foam performed higher killing rates on the virus with the presence of host cells compared to in a virus-only water environment. The result demonstrated the contact-killing effect caused by the intensified structure of copper foam played an important role in its superior antimicrobial properties. This study successfully implemented the “structure” strategy of process intensification and opened up the possibility of applying micro-structured copper foam in a range of other water disinfection systems, from pre-treatment to point-of-use, and should thus become a topic of further research, which may help to resolve the water safety crisis and provide safe water supply to communities in need.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".