Parameters governing reproducibility of flow properties of porous monoliths photopatterned within microfluidic channels
Bibliographic record
Abstract
We report the patternability as well as the reproducibility and stability of flow resistance of polymer monolithic beds photopatterned within microfluidic channels as a function of initial reagent composition and preparation conditions. 2-Hydroxyethyl methacrylate and ethylene dimethacrylate-based polymer monoliths were selectively photopatterned within microchannels and their flow resistance was evaluated using a photobleaching, TOF linear flow rate measurement method developed in our lab. This measurement technique was found to be significantly more informative for columns formed in microfluidic channels compared with bulk monolith characterization by mercury intrusion porosimetry. 1-Octanol was determined to provide sharp bed edge formation and relatively low flow resistance by photopatterning relative to other porogenic solvents. Compared with literature formulations which did not achieve good flow stability and reproducibility from batch to batch, using 2-hydroxyethyl methacrylate, ethylene dimethacrylate and 1-octanol as porogenic solvents, less than 4% RSD was achieved in flow stability over 7 days for monoliths prepared with 60-80% crosslinker(monomer+crosslinker) ratio. Column-to-column variation of 5% RSD was obtained in this composition range. These results demonstrate that photopatterning of uniform polymer monolithic beds, which is critical for applications in multiplexed microfluidic systems, requires careful attention to the parameters that affect reproducibility, specifically the porogenic solvent choice and the crosslinker to monomer ratio.
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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 | 0.004 |
| 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".