Superhydrophilicity and antibacterial property of a Cu-dotted oxide coating surface
Bibliographic record
Abstract
BACKGROUND: Aluminum-made settings are widely used in healthcare, schools, public facilities and transit systems. Frequently-touched surfaces of those settings are likely to harbour bacteria and be a potential source of infection. One method to utilize the effectiveness of copper (Cu) in eliminating pathogens for these surfaces would be to coat the aluminum (Al) items with a Cu coating. However, such a combination of Cu and Al metals is susceptible to galvanic corrosion because of their different electrochemical potentials. METHODS: In this work, a new approach was proposed in which electrolytic plasma oxidation (EPO) of Al was used to form an oxide surface layer followed by electroplating of Cu metal on the top of the oxide layer. The oxide was designed to function as a corrosion protective and biocompatible layer, and the Cu in the form of dots was utilized as an antibacterial material. The antibacterial property enhanced by superhydrophilicity of the Cu-dotted oxide coating was evaluated. RESULTS: A superhydrophilic surface was successfully prepared using electrolytic plasma oxidation of aluminum (Al) followed by electroplating of copper (Cu) in a Cu-dotted form. Both Cu plate and Cu-dotted oxide surfaces had excellent antimicrobial activities against E. coli ATCC 25922, methicillin-resistant Staphylococcus aureus (MRSA) ATCC 43300 and vancomycin-resistant Enterococcus faecium (VRE) ATCC 51299. However, its Cu-dotted surface morphology allowed the Cu-dotted oxide surface to be more antibacterial than the smooth Cu plate surface. The enhanced antibacterial property was attributed to the superhydrophilic behaviour of the Cu-dotted oxide surface that allowed the bacteria to have a more effective killing contact with Cu due to spreading of the bacterial suspension media. CONCLUSION: The superhydrophilic Cu-dotted oxide coating surface provided an effective method of controlling bacterial growth and survival on contact surfaces and thus reduces the risk of infection and spread of bacteria-related diseases particularly in moist or wet environments.
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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 | 0.002 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".