Achieving 3-D Structural Uniformity in Cellulose Gel Beads via Salt Screening
Bibliographic record
Abstract
Cellulose microgel beads fabricated using the dropping technique suffer from structural irregularity and mechanical variability. This limits their translation to biomedical applications that are sensitive to variations in material properties. Ionic salts are often uncontrolled by-products of this technique, despite the known effects of ionic salts on cellulose assembly. In this study, the coagulation behavior of cellulose/salt solutions was explored as a way to combat these challenges. An ionic salt (NaCl) was added to a cellulose solution (cellulose/NaOH/urea) prior to coagulation in a hydrochloric acid bath. Quantification of the bead geometry and characterization of the pore architecture revealed that balancing the introduction of salt with the resultant solution viscosity is more effective at reducing structural variability and diffusion limitations than other pre-gelling techniques like thermal gelation. Three-dimensional visualization of the internal pore structure of neat cellulose, thermo-gel, and salt-gel beads revealed that adding salt to the solution is the most effective way to achieve 3-D structural uniformity throughout the bead. Coupled with nanoindentation, we confirmed that the salt produced during coagulation plays a critical role in mechanical variability, and that adding salt to the solution before dropping into the coagulation bath completely screens this effect, producing uniform microgel beads with reproducible mechanical properties.
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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) | 0.001 | 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 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".