Antibacterial activity enhancement of silver deposited on TiO<inf>2</inf> nanotube array
Bibliographic record
Abstract
E. coli is an emerging cause of food borne and waterborne illnesses. The pathogenic serotypes produce a powerful toxin that may cause severe illness. Nanotechnology has significantly contributed to the lowering cost of waterborne E. coli bacteria elimination, using materials such as nano-scale Titanium dioxide (TiO2). In this work, using anodization method, nanotube arrays of TiO2with 90-100 nm pore diameter were synthesized in an organic electrolyte containing fluoride ions. Deposition of Silver (Ag) on the large-surface TiO2nanotubes showed significant antibacterial activity on E. coli. A reductive doping was performed to increase the conductivity of the TiO2nanotubes, resulting in an improved uniformity of the silver deposition. Silver deposition was performed in a three-electrode electrodeposition cell using a cyanide-base silver electrolyte. Characterization of the fabricated structure, using scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX), confirmed the uniform deposition of silver onto the TiO2porous layer. Liquid medium test under light illumination followed by serial dilutions, resulted in perfect photo biocide efficiency of the immobilized Ag/TiO2against E. Coli.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".