Nano-TiO<sub>2</sub>/polyurethane composites for antibacterial and self-cleaning coatings
Bibliographic record
Abstract
Grafting from polymerization was used to synthesize nano-titania/polyurethane (nTiO(2)/polyurethane) composite coatings, where nTiO(2) was chemically attached to the backbone of the polyurethane polymer matrix with a bifunctional monomer, 2,2-bis(hydroxymethyl) propionic acid (DMPA). This bifunctional monomer can coordinate to nTiO(2) through an available -COOH group, with two available hydroxyl groups that can react with diisocyanate terminated pre-polyurethane through step-growth polymerization. The coordination reaction was monitored by FTIR and TGA, with the coordination reaction found to follow first order kinetics. After step-growth polymerization, the polyurethane nanocomposites were found to be stable on standing with excellent distribution of Ti in the polymer matrix without any significant agglomeration compared to simple physical mixtures of nTiO(2) in the polyurethane coatings. The functionalized nTiO(2)-polyurethane composite coatings showed excellent antibacterial activity against gram-negative bacteria Escherichia coli; 99% of E. coli were killed within less than one hour under solar irradiation. Self-cleaning was also demonstrated using stearic acid as a model for 'dirt'.
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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) | 0.001 | 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 | 0.001 |
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".