Plasma-Sprayed and Sintered Silver-Based Antimicrobial Coatings for Industrial and Biomedical Application
Bibliographic record
Abstract
Bacteria are ever-present in many industries, especially food and water processing, and medicine.Bacteria can colonize the surfaces of equipment and implants, risking potential infection.An antimicrobial coating that could be applied to an alloy would prove invaluable in these industries.This thesis suggests using silver as an active antibacterial agent and details the experimental data and analysis of coatings produced via plasmaspraying and sintering.The coatings were applied to cobalt chromium, an alloy used in both industries.The plasma-sprayed coatings used cobalt chromium as a base metal, containing 0%, 2%, and 5% silver by weight.The sintered coatings had a greater adhesion strength than the plasma-sprayed coatings (25.86 MPa versus 24.66 MPa in the 2% silver coating).The plasma-sprayed coatings saw no leaching of silver in sterile water, and the 2% and 5% silver plasma-sprayed coatings reduced bacteria proliferation relative to the 0% (99.9% and 63.4% reduction).
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 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".