Characterization of the Hydrodynamics and Mixing Performance of a Split-and-Recombination (SAR) Prototype Microreactor and a Multilamination Commercial Microreactor
Bibliographic record
Abstract
The aim of this work was to quantify the performance of two well-known mixing mechanisms used in microreactors: the split-and-recombination (SAR) and the multilamination by means of an interdigital structure. The residence time distribution (RTD) and the mixing performance in laminar flow regime were experimentally characterized by the tracer pulse-input technique and the iodide-iodate Villermaux/Dushman method. RTD analysis indicates bypassing caused by uneven flow distribution in the manifolds of both microreactors. A decrease of the quadratic dependence of axial dispersion on fluid velocity is produced by the improved tracer homogenization achieved in the microfluidic structures. The iodide-iodate method shows that below a critical Damköhler number the microreactors exhibit a superior mixing performance than a conventional T-junction. The interdigital microreactor displayed the best mixing capabilities for all the flow conditions investigated. However, the estimation of energy dissipation confirms that the improved mixing performance of the interdigital unit is obtained at the expense of greater energy expenditure when compared with the split-and-recombination microreactor.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".