Hygromnemics: Programmable Material Memory Matter Actuators via Wet Pre‐Constraining
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Hygromnemic actuators that store shape memory within their dry structure using a pre‐constraining mechanism activated by humidity is introduced. Actuators are pre‐constrained for various durations at a given relative humidity level to program desired hygromnemic actuation. Hygromnemic functions, linking deformation amplitude to constraint duration, are defined following these tests. Sinusoidal actuation patterns are achieved by positioning constraining blocks at different distances from the actuators. They operate effectively in low humidity (12% relative humidity). While describing the mechanism behind hygromnemic actuation, humidity shape memory actuation is unveiled when the actuation shape is stored after Glass Transition Temperature (Tg) is lowered via humidity conditioning. The actuator systems are used to create a soft robotic window opening in both dry and wet conditions, depending on preconditioning programming. Remarkably, these hygromnemic actuators display their actuated shape in dry conditions where their strength is 253% higher and their stiffness is more than one order of magnitude larger than in the wet conditions. Finally, the shape storage capability shows potential to control the actuated shape during operational service of the robots thanks to long‐ and short‐term memory effect highlighted. The hygromnemic mechanisms described here enable low‐cost humidity‐driven programmable matter states, similar to those achieved with thermally‐induced shape memory effects.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it