Wrinkling Non-Spherical Particles and Its Application in Cell Attachment Promotion
Bibliographic record
Abstract
Surface wrinkled particles are ubiquitous in nature and present in different sizes and shapes, such as plant pollens and peppercorn seeds. These natural wrinkles provide the particles with advanced functions to survive and thrive in nature. In this work, by combining flow lithography and plasma treatment, we have developed a simple method that can rapidly create wrinkled non-spherical particles, mimicking the surface textures in nature. Due to the oxygen inhibition in flow lithography, the non-spherical particles synthesized in a microfluidic channel are covered by a partially cured polymer (PCP) layer. When exposed to plasma treatment, this PCP layer rapidly buckles, forming surface-wrinkled particles. We designed and fabricated various particles with desired shapes and sizes. The surfaces of these shapes were tuned to created wrinkle morphologies by controlling UV exposure time and the washing process. We further demonstrated that wrinkles on the particles significantly promoted cell attachment without any chemical modification, potentially providing a new route for cell attachment for various biomedical applications.
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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 | 0.001 | 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".