Comprehensive kinetic study for <scp>Fischer</scp> – <scp>Tropsch</scp> reaction over <scp>KMoFe</scp> / <scp>CNTs</scp> nano‐structured catalyst
Bibliographic record
Abstract
Abstract The kinetics of the Fischer–Tropsch (FT) reaction was evaluated through detailed experimentation with a KMo bimetallic promoted Fe catalyst supported on carbon nanotubes (CNTs). The kinetic tests were conducted in a fixed‐bed reactor under operating conditions of P = 6.9–41.3 bar, T = 543–563 K, H 2 /CO = 1, gas hourly specific velocity (GHSV) = 2000 h −1 . This study aimed to investigate the mechanism prevailing in CO activation and the rate equation for CO consumption during FT reactions over a 0.5K5Mo10Fe/CNTs catalyst. To evaluate the synergistic effects of Fe, Mo, and K phases on the catalyst activity, both fresh and spent catalysts were thoroughly characterized using X‐ray diffraction (XRD), X‐ray photoelectron spectroscopy (XPS), scanning electron microscopy and energy‐dispersive spectroscopy (SEM‐EDS), X‐ray absorption near edge structure (XANES), and extended X‐ray absorption fine structure (EXAFS) to ascertain the different phases (active sites) present and relevant interactions. Based on the adsorption of carbon monoxide and hydrogen, 22 possible mechanisms for monomer formation were proposed for FT synthesis in accordance with the Langmuir–Hinshelwood–Hougen–Watson (LHHW) and Eley–Rideal (ER) adsorption theories. The best fit kinetic model was identified through a multi‐variable non‐linear regression analysis. The selected mechanistic model was based on carbide formation approach, where H 2 ‐assisted adsorption of CO was considered for the derivation. Kinetic parameters such as activation energy, adsorption enthalpies of H 2 , and CO were estimated to be 65.0, −13.0, and −54.0 kJ/mol, respectively. Considering the developed kinetic model, the effects of reaction temperature and pressure were assessed on Fischer–Tropsch synthesis (FTS) product distribution. Additionally, the kinetic model was compared with the typical Anderson–Schulz–Flory model, suggesting the effects of water‐gas‐shift and the existence of additional formation pathway such as secondary re‐adsorption of olefins for heavier hydrocarbons.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 teacher head, 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".