High throughput multilayer microfluidic particle separation platform using embedded thermoplastic-based micropumping
Bibliographic record
Abstract
We present an integrated thermoplastic elastomer (TPE) based multilayer microfluidic device with an embedded peristaltic micropump and through-holes membrane for high throughput particle sorting and separation. Fluidic and pneumatic layers of the device were fabricated using hot-embossing lithography and commercially available polycarbonate membranes were succcessfully sandwiched between two thermoplastic elastomer fluidic layers integrated to a peristaltic micropumping layer. The integrated peristaltic micropump induces turbulence at the top-microfluidic layer ring which successfully avoids particle aggregation and membrane blocking even at nanorange size. We present herein the general design of the device structure and pumping characteristics for three devices with membrane pore sizes of 10 μm, 5 μm and 800 nm. By using this design we have successfully demonstrated a separation efficiency as high as 99% of polystyrene microbeads with different sizes and most importantly the separation of 390 nm particles from 2 μm beads was achieved. Using this device, we were also able to separate red blood cells with size of about 6-8 μm from osteoblasts typically larger than 10 μm to demonstrate the potential applicability of this platform for biological samples. The produced microfluidic chip operating at flow rates up to 100 μl min(-1) allows us to achieve efficient high-throughput sorting and separation of target particles/cells.
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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 | 0.001 |
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".