Laponite-Enabled Freeform Manufacturing of Tough Hydrogels with Colorimetric pH Sensitivity
Bibliographic record
Abstract
Hydrogels are ideal sensor platforms in aqueous media. Colorimetric assays deliver information intuitively; preventing chromophore leaching has been a challenge in aqueous media. Direct ink writing is a versatile free-form manufacturing method for hydrogels; a generalizable formula to enable three-dimensional (3D) printability can be impactful. In this study, a dual-network hydrogel of polyacrylamide and alginate is 3D printed by incorporating Laponite as a universal aqueous rheological modifier. Copolymerization of methacrylated phenol red with polyacrylamide enables colorimetric response to pH, ranging from yellow (pH = 5) to fuchsia (pH = 10). Rheological analysis of the precursor solutions reveals that a critical quantity of Laponite to achieve substantial shear thinning behavior exists at 4–4.5 wt %, which is consistent with a pervaded volume-based model. X-ray diffraction confirms the formation of 5-layer thick Laponite aggregates when their content exceeds the critical quantity. For 3D printing, 8 wt % of Laponite provides the optimal shear thinning and viscosity at rest for the best print fidelity. Strong anisotropicity in printed strands leads to a contrast in the mechanical properties with respect to the printing directions. Optimized printing produces hydrogels that can stretch 18 times their original length. Our colorimetric pH sensing hydrogel showcases a scalable freeform manufacturing-enabled platform technology with chemically bound chromophores.
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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 | 0.000 |
| 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".