An information encrypted heterogeneous hydrogel with programmable mechanical properties enabled by 3D patterning
Bibliographic record
Abstract
Heterogeneous architectures with defined patterns found in nature have stimulated the burgeoning development of biomimetic materials. However, the construction of soft matter like hydrogels that mimic biological materials with a combination of strong mechanical performance and unique functionality remains difficult. In this work, we developed a simple and adaptable strategy of a 3D printing complex structure within hydrogels utilising all-cellulosic materials (hydroxypropyl cellulose/cellulose nanofibril, HPC/CNF) as ink. The structural integrity of the patterned hydrogel hybrid is ascertained by the interfacial interaction between cellulosic ink and the surrounding hydrogels. Through designing the geometry of the 3D printed pattern, programmable mechanical properties of hydrogels are achieved. In addition, the thermally induced phase separation properties of HPC confer thermally responsive behaviour on patterned hydrogels, providing them potential to be assembled into double information encryption devices and shape-morphing materials. We anticipate that this all-cellulose ink-enabled 3D patterning technique within hydrogels can serve as a promising and sustainable alternative for designing biomimetic hydrogels with desired mechanical properties and functions for a variety of applications.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".