Antibiofilm potential of graphene-dispersed alkoxysilane coatings: a materials science perspective
Bibliographic record
Abstract
This study investigates the antibiofilm properties of alkoxysilane-based coatings incorporating dispersed multilayer graphene powder. Graphene, synthesised via a proprietary method, was incorporated into a resin matrix at various concentrations (0.1%, 0.5%, and 1.0% by weight) and applied to glass substrates. Raman spectroscopy confirmed the presence of defect-rich, multilayer graphene, which is known to enhance antimicrobial surface properties. Biofilm formation by Staphylococcus epidermidis was evaluated using ISO 4768-standardised crystal violet staining. Results indicated that biofilm development was effectively suppressed at concentrations up to 0.5%, whereas an unexpected increase was observed at 1.0%, possibly due to graphene aggregation and reduced surface exposure. The findings suggest that both graphene concentration and dispersion quality critically influence antibiofilm efficacy. The study highlights the dual role of graphene, both as a physical and chemical antibacterial agent, and its potential application in medical, industrial, and hygienic materials. Further investigation is warranted to optimise dispersion and explore microbial-material interactions in real-world conditions.
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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 | 0.000 | 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".