Enhanced Antibacterial Properties of Copper Surfaces Using Cold Spray Shot Peening
Bibliographic record
Abstract
Abstract Metal surface characteristics play a significant role in interacting with their biological environment. Copper surfaces have been identified for their antimicrobial properties. Improvement of antibacterial and antiviral performances can be tailored by surface microstructure modification. Severe plastic deformation is an effective surface modification procedure to improve the mechanical performance of metal surfaces. This technique can be adapted to obtain surface grain refinement and induce surface roughness. In this work, cold spray shot peening is used to modify copper substrate surfaces and study the effects on their antibacterial properties. To modify the grain structure of copper, different shot-peening parameters were examined. The surface roughness and microstructure were investigated by employing optical and scanning electron microscopy. The bactericidal activity of copper substrates after shot peening treatment is discussed and a comparison between the bacterial load on treated (shot-peened surface and cold sprayed copper coating) and untreated surfaces (as-received) is provided. Testing of the surfaces after their exposure to the biological environment demonstrated improved microbial inactivation performances for surfaces that had undergone grain refinement without exceeding a certain roughness value.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".