Bibliographic record
Abstract
To improve the selectivity and yield of multiphase reactions, an attempt to intensify gas–liquid mass-transfer operations was undertaken in which screen/grid static mixers were used to promote interphase mass transfer. A modified technique was used to enhance the reproducibility of the results and to account for the depletion effect which becomes critical at high mass-transfer rates. The volumetric mass transfer coefficient, k L a, was found to increase with increasing liquid superficial velocity and gas volume fraction and reached values as high as 4.08 s –1 at low specific energy consumption rates, particularly for slowly coalescent systems, a situation that is encountered in most industrially relevant systems. The gas–liquid reactor/contactor presently investigated takes advantage of the coalescence retardation characteristics of most industrially relevant streams to achieve k L a values that surpassed those of most conventional reactor/contactors by more than an order of magnitude while maintaining a high energy utilization efficiency (up to 0.63 kg O 2 /kWh). The ability to reach 98% equilibrium within residence times of less than 800 ms, achieved without significantly increasing the power consumption rates, allows for the use of static mixing reactor volumes that are several orders of magnitude smaller than conventional units such as mechanically agitated tanks and bubble columns.
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 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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".