Mechanical Characterization of APA Microcapsules by Parallel-Plate Compression
Bibliographic record
Abstract
We produced microcapsules of alginate-poly(L)lysine-alginate (APA)with diameters on the order of 10 µm. To characterize their mechanical properties, we conducted an experiment on the parallel-plate compression of a microcapsule and modeled its deformation. In the modeling task, the microcapsule was assumed to be a spherical liquid-filled elastic membrane with negligible bending stiffness and permeability. The membrane thickness was estimated by applying Reissner's linear elastic theory to the experimental force-displacement relationship during loading in the small displacement region. The initial stretch of the membrane was taken into account; it was mainly caused by the osmotic pressure difference across the membrane. The initial stretch of the microcapsule was determined by fitting the calculated and experimental force-displacement relationships during loading at small to medium displacements. At large displacements, the calculated force was smaller than the experimentally measured force because of fluid permeation across the APA membrane. The calculated and experimentally imaged shapes of the deformed microcapsule were compared. The effects of varying the membrane thickness on the force-displacement and transmural pressure-displacement curves were shown, and the limitations of applying the present deformation model were examined.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".