Long‐Lasting Hydrophilicity Induced by Ultraviolet Light on Surface Modified Hydrophobic Polylactic Acid
Bibliographic record
Abstract
ABSTRACT Surface treatments are used to tailor the wettability of compostable polymers for outdoor applications. However, imparting hydrophobicity can have direct and indirect consequences on the polymer's eventual degradation during use. In this research, a solvent‐treated hydrophobic (water contact angle of 147.2° ± 0.6°) polylactic acid (PLA) substrate could be altered significantly to a wicking sample (22.5° ± 3.1°) with a single 2‐h ultraviolet‐C (UVC) exposure. Wicking behavior remains consistent even 1 year post‐exposure, implying a long‐lasting hydrophilic change to the polymer surface. UVC irradiation induced chain scission near the surface, reducing considerably the molecular weight. Reduction in molecular weight impacts properties, including lower glass transition, melting, and degradation temperatures. However, no significant chemical composition changes could be detected with X‐ray Photoelectron Spectroscopy (XPS). Infrared spectroscopy has shown a very minor oxidation with an increasing signal of the peak related to carbonyl groups at 1724 cm−1 from α‐cleavage. Force‐distance spectroscopy confirmed the increase in polarity of the UVC‐exposed solvent‐treated surfaces. The increase in wettability and more precisely surface polarity relates to an orientation of polar oxygen bonds towards the surface made possible by the chain scissions.
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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".