Fischer‐Tropsch synthesis: Effect of solvent on the H<sub>2</sub>‐D<sub>2</sub> isotopic exchange rate over an activated cobalt catalyst
Bibliographic record
Abstract
The effect of solvent on the hydrogen‐deuterium isotopic homomolecular exchange over a traditional Fischer‐Tropsch cobalt catalyst (25 % Co/Al2O3) was investigated using a plug flow reactor at two different reaction temperatures (room temperature (26 °C) and –20 °C) and at atmospheric pressure. In this study, three different solvents were tested, including n‐pentane, n‐hexadecane, and C‐30 oil. The consumption of H2 and D2 is the same, and the concentration of the HD produced is twice the consumption of H2 or D2 at dry (without solvent) conditions. At room temperature and at –20 °C, conditions without solvent exhibited 100 mol% exchange with the formation of H2:HD:D2 having a 1:2:1 ratio. For n‐pentane solvent, the exchange rates were ∼97 and ∼80 mol% at 26 and −20 °C, respectively. For the n‐hexadecane and C30 oil solvents, the initial exchange rate was ∼50 mol%, with the exchange rate decreasing over time. The lower exchange rate with the n‐hexadecane and C30 oil solvents, and also n‐pentane at –20 °C, is likely due primarily to the limited mobility of reactant molecules in the liquid‐filled pores of the catalyst. Blocking or covering of the pores of the catalyst depends on the molecular mass and density of the solvent. No isotopic partitioning preference was observed at two different temperatures and various solvents for the active cobalt catalyst.
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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".