Effect of CO Concentration on the α-Value of Plasma-Synthesized Co/C Catalyst in Fischer-Tropsch Synthesis
Bibliographic record
Abstract
A plasma-synthesized cobalt catalyst supported on carbon (Co/C) was tested for Fischer-Tropsch synthesis (FTS) in a 3-phase continuously-stirred tank slurry reactor (3-φ-CSTSR) operated isothermally at 220 °C (493 K), and 2 MPa pressure. Initial syngas feed stream of H2:CO ratio = 2 with molar composition of 0.6 L/L (60 vol %) H2 and 0.3 L/L (30 vol %) CO, balanced in 0.1 L/L (10 vol %) Ar was used, flowing at hourly space velocity (GHSV) of 3600 cm3·h−1·g−1 of catalyst. Similarly, other syngas feed compositions of H2:CO ratio = 1.5 and 1.0 were used. Results showed ~40% CO conversion with early catalyst selectivity inclined towards formation of gasoline (C4–C12) and diesel (C13–C20) fractions. With prolonged time-on-stream (TOS), catalyst selectivity escalated towards the heavier molecular-weight fractions such as waxes (C21+). The catalyst’s α-value, which signifies the probability of the hydrocarbon chain growth was empirically determined to be in the range of 0.85–0.87 (at H2:CO ratio = 2), demonstrating prevalence of the hydrocarbon-chain propagation, with particular predisposition for wax production. The inhibiting CO effect towards FTS was noted at molar H2:CO ratio of 1.0 and 1.5, giving only ~10% and ~20% CO conversion respectively, although with a high α-value of 0.93 in both cases, which showed predominant production of the heavier molecular weight fractions.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".