Photochemical Patterning and Characterization of Mechanical Properties on Soft Materials
Bibliographic record
Abstract
Abstract Although different chemistries for the spatio‐temporal localization of molecules and gradients of chemical signals within soft materials are now available, the achievement of spatio‐temporal patterns of mechanical properties in such materials and their characterization remain considerable challenges. This study presents the syntheses of two novel photo‐sensitive and thermoresponsive hydrogel systems, a photo‐stiffening and a photo‐softening hydrogel. Their potential for fabricating soft materials with patterned mechanical properties is then demonstrated by fabricating an actuator whose higher‐order bending properties can be switched on with light, and by encoding mechanical properties for digital information encryption and storage. Microindentation and a custom‐made data analysis software are essential for the characterization of all the materials. From a general perspective, this work opens a route to the fabrication of soft materials with patterned mechanical properties, addressing an important emerging challenge in soft materials science with applications in soft robotics and information encryption and storage.
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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".