In Situ Investigation of Swelling Dynamics of Acrylamide‐Acrylic Acid Superabsorbent Microparticles at a Single Particle Level
Bibliographic record
Abstract
Abstract Investigating the swelling behavior of superabsorbent polymer microparticles (SAP‐MPs) at a single‐particle level using traditional methods is constrained by low resolution and insufficient real‐time data, especially for particles smaller than 300 µm. To address these challenges, a novel microfluidic device capable is developed of real‐time, high‐precision single‐particle analysis. This platform hydrodynamically traps individual SAP‐MPs, enabling continuous monitoring of their swelling dynamics under controlled conditions. SAP‐MPs with varying sizes (90–270 µm), crosslinker concentrations (0.25% 2 >0.98) and minimal equilibrium volumetric swelling ratio deviations (ΔVSR eq <4%), confirming diffusion as the primary swelling mechanism, particularly for smaller particles. Smaller SAP‐MPs exhibited enhanced performance, with VSR eq of ≈140 m 3 /m 3 —40% higher than their larger counterparts—and swelling rates (SR) up to 10 m 3 m − 3 ·s. This study establishes microfluidics as a transformative tool for single‐particle characterization and provides insights into engineering hydrogels tailored for advanced applications in drug delivery, tissue engineering, and environmental sensing.
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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".