Anodized Aluminum with Nanoholes Impregnated with Quaternary Ammonium Compounds Can Kill Pathogenic Bacteria within Seconds of Contact
Bibliographic record
Abstract
Bacterial contamination of surfaces results in the spread of pathogens in public spaces such as hospitals and public transport. The development of antibacterial surfaces that rapidly kill bacteria is therefore highly desirable. Here, we investigate the antibacterial efficacy of a novel anodized aluminum surface featuring nanoholes impregnated with quaternary ammonium compounds, referred to as A3S. The antimicrobial activity of A3S was assessed using both Gram-positive and Gram-negative bacteria in a novel assay which simulates pathogen transfer from a contaminated "finger" to a clean finger in a real-world scenario. Enumeration of colony-forming units shows that the number of viable bacteria on the second "finger" contacting A3S is significantly reduced compared to a control surface. Furthermore, bacterial contact with the A3S material results in compromised cell membranes in less than 1 min, and a kill zone assay shows that an exposure time as short as 5 s is sufficient to kill pathogenic bacteria. The rapid antimicrobial action of A3S was particularly evident against Gram-positive bacteria, that account for more than 70% of nosocomial infections. Taken together, these findings demonstrate that A3S is a promising candidate for the fabrication of antibacterial surfaces that can be used in a wide range of clinical and commercial applications to stop the spread of harmful bacteria.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 | 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".