Nanopatterning of steel by one-step anodization for anti-adhesion of bacteria
Bibliographic record
Abstract
Surface nanopatterning of metals has been an effective technique for improved performance and functionalization. However, it is of great challenge to fabricate nanostructure on carbon steels despite their extensive use and urgent needs to maintain the performance reliability and durability. Here, we report a one-step anodization technique to nanopattern a carbon steel in 50 wt.% NaOH solution for highly effective anti-adhesion by sulphate reducing bacteria (SRB), i.e., Desulfovibrio desulfuricans subsp. desulfuricans (Beijerinck) Kluyver and van Niel. We characterize the morphology, structure, composition, and surface roughness of the nanostructured film formed on the steel as a function of anodizing potential. We quantify the surface hydrophobicity by contact angle measurements, and the SRB adhesion by fluorescent analysis. The optimal anodization potential of 2.0 V is determined for the best performance of anti-adhesion of SRB to the steel, resulting in a 23.5 times of reduction of SRB adhesion compared to bare steel. We discuss the mechanisms for the film formation on the steel during anodization, and the high-performance anti-adhesion of bacteria to nanopatterned steels. Our technique is simple, cost-effective and environment-friendly, providing a promising alternative for industry-scale surface nanopatterning of carbon steels for effective controlling of bacterial adhesion.
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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 | 0.001 | 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) | 0.000 | 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".