Multiphase catalytic reactors: a perspective on current knowledge and future trends
Bibliographic record
Abstract
Conventional and emerging processes that require the application of multiphase reactors are reviewed with an emphasis on catalytic processes. In the past, catalyst discovery and development preceded and drove the selection and development of an appropriate multiphase reactor type. This sequential approach is increasingly being replaced by a parallel approach to catalyst and reactor selection. Either approach requires quantitative models for the flow patterns, phase contacting, and transport in various multiphase reactor types. This review focuses on these physical parameters for various multiphase reactors. First, fixed-bed reactors are reviewed for gas-phase catalyzed processes with an emphasis on unsteady state operation. Fixed-bed reactors with two-phase flow are treated next. The similarities and differences are outlined between trickle beds with cocurrent gas–liquid downflow, trickle-beds with countercurrent gas–liquid flow, and packed-bubble columns where gas and liquid are contacted in cocurrent upflow. The advantages of cyclic operation are also outlined. This is followed by a discussion on conventional reactors with mobile catalysts, such as slurry bubble columns, ebullated beds, and agitated reactors. Several unconventional reactor types are reviewed also, such as monoliths for two-phase flow processing, membrane reactors, reactors with circulating solids, rotating packed beds, catalytic distillation, and moving-bed chromatographic reactors. Numerous references are cited throughout the review, and the state-of-the-art is also summarized. Measurements and experimental characterization methods for multiphase systems as well as the role of computational fluid dynamics are not covered in a comprehensive manner due to other recent reviews in these areas. While it is evident that numerous studies have been conducted to elucidate the behavior of multiphase reactors, a key conclusion is that the current level of understanding can be improved further by the increased use of fundamentals.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".