Bibliographic record
Abstract
Abstract Catalytic distillation (CD) is a “green” reactor technology that combines a heterogeneous catalytic reaction and the separation of reactants and products via distillation in a single reactor/distillation column. CD is a rapidly developing field that incorporates catalysis, kinetics, and mass transfer to provide more selective and energy efficient processes. The heterogeneous catalyst provides the sites for catalytic reactions and also the interfacial surface for liquid/vapor separation. The distinct difference between the CD column and the conventional distillation column lies in the placement of solid catalysts usually incorporated in some kind of packing (CD packing) within the distillation column to provide a reaction section in addition to the traditional trays or random packings used for separations in the stripping the rectifying sections of the distillation column. Mass transfer characteristics of the CD packing in the reaction zone has significant influence on the product yield and selectivity. Equilibrium and nonequilibrium models have been developed to simulate and design CD processes. The benefits of CD include energy and capital savings, enhanced conversion and product selectivity, longer catalyst lifetime, and reduction of waste streams. Equilibrium limited and exothermic processes will benefit from CD. The first commercial application of CD was for the production of methyl tertiary butyl ether (MTBE). There are many other possible applications of CD such as the hydration of olefins, alkylations, esterifications, hydrolysis, aldol condensation, hydrogenation, desulfurization, and oligomerization of olefins. Currently most of the CD processes are related to the petroleum and petrochemical industries. The use of CD for the production of bulk and fine chemicals remain largely unexplored. Besides the development of new “green” processes using CD, fruitful areas of future research and development on CD include fundamental aspects of combining catalysis, reaction engineering, multiphase flow and separation, and the development of novel CD packings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".