FUNCTIONAL ANTIBACTERIAL SURFACES MADE BY ULTRAFINE POWDER COATING
Bibliographic record
Abstract
Surface bio-contamination is a serious problem which contributes to outbreaks of nosocominal infection. An effective antimicrobial surface coating can significantly reduce the average surface population of pathogens available for transmission to a susceptible host. To respond to these problems, a functional antibacterial surface has been developed. For the use in medical devices, food industries, aviation sector and many other areas, a strong antibacterial property is required for the surface coating to effectively resist bacterial colonization. Recently, the introduction of new silver based antibacterial surfaces has drawn more attention not only for their non-toxicity of the activeAg ion to human cells but also of their novel ability of being a long lasting biocide.\nA synthetic zeolite and three other natural zeolites have been selected in this work as carrier materials for silver. Silver acts as the active material that is incorporated within zeolite and blended with ultrafme polyester resin. It shows strong antibacterial properties against Escherichia coli. A commercially available sample has been selected to compare with all the experimental results. ICP-OES analysis shows the highest silver concentration being within the ion exchanged synthetic zeolite. Different polyester ultrafme powders have made with different ion exchanged zeolites and their antimicrobial efficacy tested by repeated use of the same coated chips followed by washing with liquid detergent and water. For final formulation, silver was incorporated into natural zeolite LBN (chabazite) through ion exchange with 0.05M silver nitrate for 24 hours at pH below 5.0 and IPC-OES analysis confirmed the amount of silver as 0.52% in the ultrafme coating powder. SEM and EDX analysis also show the uniform distribution and amount of silver within the coating respectively. The durability of coated chips show more than 99% reduction of microorganism even after ten consecutive uses. The coated chips were also characterized by checking the effectiveness against autoclave tests and accelerated weather tests as well as the antibacterial efficiency for each condition.\nFor high efficiency, the coating needs to have a certain amount of active component. The controlled silver release capability of the formulated coating with this concentration of silver is promising compared to the commercial counter parts. These coated surfaces have shown uniform homogeneous antibacterial properties with excellent durability for extended period.
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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 | 0.001 |
| 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".