Surface modification of <scp>PET</scp> fabric by plasma pre‐treatment for <scp>long‐lasting</scp> permethrin deposition
Bibliographic record
Abstract
The mosquito‐transmitted diseases are of serious concern and are affecting several millions of peoples worldwide. Instead of medication afterward the disease initiated, self‐protection against the mosquito's is preferable, specifically in endemic areas. For this purpose, the permethrin coated clothing is a suitable choice to avoid mosquitos' bites. Unfortunately, the permethrin coating on fabrics is not long‐lasting, and its laundering resistance is very low on hydrophobic fabric. In this study, the effect of plasma surface modification of PET fabric on the adhesion of permethrin and its laundering resistance are evaluated. The plasma processing is carried out in nitrogen, oxygen, and nitrogen–oxygen mixture plasma. The samples are analyzed using Fourier Transform Infrared spectroscopy, X‐ray photoelectron spectroscopy, scanning electron microscope and chromatography. The results show that the oxygen plasma pre‐treated samples exhibit the higher residual contents of permethrin after 60 wash cycles as compared with other gasses. Without plasma pre‐treatment, the 95% loss, whereas the sample with oxygen plasma pre‐treatment shows that only 22% loss of initial concentration of permethrin occurs after washing. This study shows that plasma pre‐treatment is valuable to improve the absorption of permethrin in PET and its laundering‐resistance. As plasma treatment is a cost‐effective technique, it needs less processing time and eco‐friendly, thus it is a great choice to deposit long‐lasting permethrin coating by plasma pre‐treatment, instead of conventional binding agents. Remarkably, the plasma treatment technique is a well‐established and industrially acceptable technique, thus expected to be of noteworthy importance for insecticide garments manufacturers.
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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".