Behavior of colloidal gels made of thermoresponsive anisotropic nanoparticles
Bibliographic record
Abstract
Amongst colloidal gels, those designed by the assembly of anisotropic colloidal particles tend to form fibrillar gels and are attracting interest as artificial cell growth environments since they have a structure reminiscent of biological extracellular matrices. Their properties can be tuned by controlling the size, shape, and rigidity of the nanoparticles used during their formation. Herein, the relationship between the physical and mechanical properties of the nanocolloidal building blocks and the properties of the resulting gels is investigated. Thermoresponsive particles with different aspect ratios and controlled rigidity were prepared, and the gelation and the properties of the resulting gels were studied. The results show how the aspect ratio and rigidity of polymer colloids tune the properties of the gels. An increase in the aspect ratio of the nanocolloid used led to a sol-gel transition observed at lower particle concentration, but an increase in the rigidity of the nanocolloids delayed the sol-gel transition to higher concentration. However, at a constant concentration, increases in the anisotropy produced gels with higher modulus and lower yield strain. Similarly, an increase in rigidity of the colloids increased the modulus and reduced the yield strain of the resulting gels.
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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) | 0.000 | 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 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".