Activation and deactivation scenarios in a plasma‐synthesized Co/C catalyst for Fischer‐Tropsch synthesis
Bibliographic record
Abstract
ABSTRACT A carbon‐supported cobalt nano‐catalyst (Co/C) synthesized through plasma was tested for Fischer‐Tropsch activity. Catalyst deactivation and activation protocols studied included in situ sample pre‐treatment at 673 K in gas flowing at the rate of 250 cm3 · min−1 in: (a) H2 only, (b) CO only, and (c) CO followed by H2, with each cycle lasting 24 h. The so‐treated catalyst samples were then tested for FTS activity for over 50 h of time‐on‐stream (TOS), at 2.2 MPa pressure and 493 or 518 K temperature in a 3‐phase continuously‐stirred tank slurry reactor (3‐φ‐CSTSR) using squalane (C30H62) as the carrier liquid phase. The feed gas composition of molar H2:CO = 1.7 comprising 50 % H2, 30 % CO, and 10 % CO2 balanced in Ar for mass balance determination, flowing at a gas hourly space velocity (GHSV) of 3360 cm3 · h−1 · g−1 of catalyst. Fresh catalysts and those reduced by CO‐only were completely inactive at 493 K and initial inactivity was attributed to the excessive C matrix formed around the metal nanoparticles during catalyst synthesis. The sample that was reduced by H2 only was the most active, although it showed the fastest declining activity due to cumulative high H2O vapour pressure in the FTS reactor, while the sample pre‐treated in both CO and H2 demonstrated a higher degree of stability with TOS.
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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".