Hydrodynamics and mass transfer studies on plate‐type microchannel reactor for liquid–liquid systems
Bibliographic record
Abstract
Abstract This work reports hydrodynamic and mass transfer studies on a novel microreactor that can passively break up liquid–liquid slugs using judiciously placed internals. The reactors were fabricated in stainless steel (SS‐316 L, hereafter SS) and PMMA (hereafter acrylic). The performance of both is comparable to the current state‐of‐the‐art in microreactor technologies. A separated flow model is proposed to estimate the pressure drop for two‐phase flows, with a mean absolute error (MAE) of 15.44% in SS and 19.83% in acrylic, respectively. Pulse tracer experiments were performed for residence time distribution (RTD) studies. They are fitted to a model for the prediction of RTD for single and two‐phase flows. The results obtained from mass transfer experiments show that the volumetric mass transfer coefficient () in the case of SS reactor is, on average, 2.4 times higher than acrylic. A correlation is developed for estimating the based on total velocity and phase fraction, providing better fits than the models based on energy dissipation. All studies show that wall characteristics significantly impact the hydrodynamics and mass transfer phenomena since the pressure drop and the are greater in (the rougher) SS than in acrylic.
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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 | 0.000 | 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".