Shear-Induced Alignment of Anisotropic Nanoparticles in a Single-Droplet Oscillatory Microfluidic Platform
Bibliographic record
Abstract
Flow-induced alignment of shape-anisotropic colloidal particles is of great importance in fundamental research and in the fabrication of structurally anisotropic materials; however, rheo-optical studies of shear-induced particle orientation are time- and labor-intensive and require complicated experimental setups. We report a single-droplet oscillatory microfluidic strategy integrated with in-line polarized light imaging as a strategy for studies of shear-induced alignment of rod-shape nanoparticles. Using an oscillating droplet of an aqueous isotropic suspension of cellulose nanocrystals (CNCs), we explore the effect of the shear rate and suspension viscosity on the flow-induced CNC alignment and subsequent relaxation to the isotropic state. The proposed microfluidic strategy enables high-throughput studies of shear-induced orientations in structured liquid under precisely controlled experimental conditions. The results of such studies can be used in the development of structure-anisotropic materials.
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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".