Intrinsic Reaction Kinetics of Higher Alcohol Synthesis from Synthesis Gas over a Sulfided Alkali-Promoted Co−Rh−Mo Trimetallic Catalyst Supported on Multiwalled Carbon Nanotubes (MWCNTs)
Bibliographic record
Abstract
A statistically designed set of experiments was run in a continuous downflow fixed-bed reactor to evaluate the intrinsic kinetics of the formation of methanol, higher alcohols, total hydrocarbon, and carbon dioxide from synthesis gas under a range of experimental conditions. To eliminate mass-transfer resistance, a multiwalled carbon nanotube (MWCNT)-supported K-promoted trimetallic sulfided Co−Rh−Mo catalyst was used in the particle size range of 147−210 μm. To predict the reaction rate for higher alcohol synthesis, the power law model was used for the reaction between CO and H 2 on the catalyst surface. The operating conditions, such as reactor temperature ( T ), pressure ( P ), gas hourly space velocity (GHSV), and H 2 /CO molar ratio, were varied in the ranges of 275−350 °C, 800−1400 psig (5.52−9.65 MPa), 2.4−4.2 m 3 standard temperature and pressure (STP) (kg of catalyst) −1 h −1, and 0.5−2.0, respectively. The data of this study are well-fitted by the power law model. The activation energies of ethanol and higher alcohols obtained over Co−Rh−Mo−K/MWCNT were low compared to those values reported in the literature.
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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".