Biobased plastics with insect‐repellent functionality
Bibliographic record
Abstract
Natural insecticides/repellents, such as pyrethrum (derived from chrysanthemum plants), and insect repellent N,N‐ Diethyl‐meta‐toluamide (DEET) were added to poly(lactic acid) (PLA) fibers through extrusion and spray coating on the PLA fabrics. Contact irritancy assay (CIA) showed that DEET‐treated PLA fabrics caused the lowest relative escape response of mosquitoes with an escape frequency of 33.3% ± 3.3%, indicating that DEET was less effect compared with natural insecticides/repellents. This was followed by the extruded natural pyrethrum‐treated PLA fabric with an escape frequency of 80% ± 6.3%. Finally, the PLA fabrics spray‐coated with natural pyrethrum caused the highest escape frequency of 98.3% ± 1.7%. Thus, it was found that pyrethrum/PLA fabrics functioned as a mosquito repellent better than DEET/PLA fabrics. In addition, TGA and tensile testing results demonstrated that pyrethrum was sufficiently thermally stable to be extrusion compounded with PLA. GPC results showed that DEET promoted de‐polymerization of PLA when co‐extruded. The results demonstrated that pyrethrum can be a viable additive for PLA to produce fibers that function as mosquito repellent to produce temporary garments that are compostable. The potential use of the developed biobased fibers with natural insect repellents is for single use of personal protection equipment (PPE) garments. POLYM. ENG. SCI., 59:E460–E467, 2019. © 2019 Society of Plastics Engineers
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) | 0.001 | 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) | 0.002 | 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".