Polyurethane (<scp>PU</scp>) based multifunctional materials: Emerging paradigm for functional textiles, smart, and biomedical applications
Bibliographic record
Abstract
Abstract The advances in polymer chemistry research have revolutionized the field of smart materials and biomedical. Polyurethanes (PUs) are a versatile polymer class with diverse structure, morphology, and behavior under various conditions deemed suitable for many functional and intelligent responses. Owing to their biocompatibility, biodegradability, excellent mechanical strength, tailorable chemical, and physical forms, PU has drawn significant research attention in recent times for a wide range of applications. Herein, this review paper outlines PU's recent advances in specific applications encompassing functional textiles, intelligent functionality and medical usage. This article contains a comprehensive review of recent developments and research works concerning PU's direct involvement as coatings, 3D objects, or composite parts to add novel purpose to the textile substrates, smart objects, or medical applications. Commencing with PU's application for the waterproof breathable textiles, the review further explores recent research where PU was incorporated as a phase change material and protective clothing. This review further delves innovative functionalities and responsiveness of the polymer triggered by various stimuli. It ends with an inclusive review of PU's different forms of application concerning medical devices and activities. Finally, perspectives on future challenges and new research opportunities are also presented and discussed.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".