Development of Micro to Milli-Scale Multiphase Reactors with and Without Solids for Integration Into Mini-Monoplants
Bibliographic record
Abstract
Typical modes of chemical processing differ between the bulk and pharmaceutical industries. Bulk chemicals are produced in large-scale, dedicated, continuous processes that are known to be more economical when flexibility in the equipment, reactions, and capacity is not required. In the pharmaceutical industry, flexibility is typically required in order to accommodate the constantly changing product market, where production campaigns may be shorter and have product amounts in the order of a few kilograms to 100 tonnes per year. Accordingly, pharmaceutical and fine chemical production is typically performed in flexible batch reactors, where larger scale vessels inherit both reduced heat transfer through a loss in surface-to-volume ratio, and decreased mass transfer through solvent dilution. As a result, pharmaceutical production processes are often run at suboptimal efficiency with large amounts of waste relative to the amount of generated product. In this work, an alternative method of intensified and dedicated pharmaceutical process design is proposed. ‘Mini-monoplant’ development is outlined through three stages; including lab-based development of best-in-class processes, factory-based development for an accelerated time to market, and mini-monoplant production at commercial scale. Within the scope of such a method of process design, several intensified reactor technologies are developed and characterized for implementation into mini-monoplants. Plate-type LL microreactors are characterized through two experimental programs. In the first, the impact of fluids (CO₂(g), water) flow rates, channel geometry, and presence of surfactant (ethanol) on the resulting gas-liquid flow regime (bubble, bubble/slug, annular), pressure drop and interphase mass transfer coefficient (𝑘𝑙𝑎) are investigated. Here, the interphase mass transfer coefficients ranged from ~0.05 to 1 s- and were found to correlate well with an energy dissipation rate model in the bubble flow regime. In the second, scale-up calculations are performed for LL microreactors within the context of running a viscous nitration reaction, leading to scale-up rules derived with the goal of maintaining mean micromixing performance. In this study, mean energy dissipation rates and relative contributions of chaotic flow were used as measures for the overall micromixing performance, with both being conserved or increased upon reactor scale-up when either water or 96 wt% H₂SO₄ (aq) were used as the fluid. Then, the solid suspension handling of a baffleless oscillatory flow coil reactor is characterized through two solid forming reactions, with the first being a model precipitation reaction and the second being a more mixing intensive phase transfer catalysis reaction having difficulties associated to gas and salt formation. In the first reaction, an oscillatory energy dissipation rate of 13 W/kg was effective in continuously keeping solids suspended at concentrations of 7.9 wt% and 5.8 wt% for 2 hours and 5 hours, respectively, whereas gas generation in the phase transfer catalysis reaction resulted in a 10-fold decrease of the oscillatory energy dissipation rate leading to subsequent clogging. Finally, and as a result of its success in continuous solid handling, a larger scale baffleless oscillatory flow coil reactor is then implemented for the continuous production of an active pharmaceutical ingredient (API) suspension at elevated temperature and pressure. Development of both the reaction apparatus itself as well as the operating conditions are outlined, leading to final operating conditions that produced 40 g/hr of the API at lab scale. A mixing-based design methodology is then proposed for maintaining geometric similarity and energy dissipation rates in a production scale reactor with an API production rate of 11.9 kg/hr. This work thus expands on the toolbox approach developed by Plouffe et al [1] for reactor selection, with the objective of implementation into continuous and dedicated pharmaceutical processes at commercial scale.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
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 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".