Polymers with Dual Light-Triggered Functions of Shape Memory and Healing Using Gold Nanoparticles
Bibliographic record
Abstract
Shape-memory and stimuli-healable polymers (SMP and SHP) are two types of emerging smart materials. Among the many stimuli that can be used to control SMP and SHP, light is unique because of its unparalleled remote activation and spatial control. Generally, light-triggered shape memory and optically healable polymers are different polymers and it is challenging to endow the same polymer with the two light-triggered functions because of their structural incompatibility. In this paper, we describe a general polymer design that allows a single material to exhibit both light-controlled shape memory and optical healing capabilities. We show that by chemically cross-linking a crystalline polymer and loading it with a small amount of gold nanoparticles (AuNPs), the polymer displays optically controllable shape memory and fast optical healing based on the same localized heating effect arising from the surface plasmon resonance of AuNPs. The photothermal effect controls, on the one hand, the shape memory process by tuning the temperature with respect to Tm of the crystalline phase and, on the other hand, activates the damage healing through crystal melting and recrystallization. Moreover, we show that these two features can be triggered separately in a sequential manner.
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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".