Comparison of Hydrodenitrogenation of Model Basic and Nonbasic Nitrogen Species in a Trickle Bed Reactor Using Commercial NiMo/Al<sub>2</sub>O<sub>3</sub> Catalyst
Bibliographic record
Abstract
A systematic study has been conducted in a trickle-bed reactor using a commercial NiMo/Al 2 O 3 catalyst to understand the effects of different variables such as H 2 S concentration in the feed by adding different amount of butanethiol, reaction pressure, temperature, liquid hourly space velocity (LHSV), and H 2 /feed ratio on the hydrodenitrogenation (HDN) of typical basic (acridine) and nonbasic (carbazole and 9-ethylcarbazole) nitrogen compounds present in heavy gas oil. The HDN conversion of basic compound was higher than that of nonbasic compounds at all butanethiol concentrations (0−4 wt %) in the feed. The HDN conversion of acridine was 98−99 wt % at 355−400 °C, whereas, with an increase in temperature from 355 to 400 °C, the conversion of carbazole and 9-ethylcarbazole increased somewhat from 92 to 95 wt % and from 94 to 97 wt %, respectively. Pressure (1120−1420 psig) had no effect on the HDN conversion of basic and nonbasic nitrogen compounds. Also, an increase in LHSV did not have a significant effect on the conversion of acridine and 9-ethylcarbazole. However, the conversion of carbazole increased from 92 to 99 wt % with a decrease in LHSV from 2 to 0.5 h - 1 . The increase in H 2 /feed ratio from 200 to 800 mL/mL caused a significant increase in conversion of carbazole from 90 to 98 wt %. The present studies showed no steric hindrance effect of the alkyl group present in 9-ethylcarbazole.
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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) | 0.000 | 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 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".