Modelling and kinetics of the toluene/methylcyclohexane‐based hydrogen storage system
Bibliographic record
Abstract
Abstract The coupling of toluene and methylcyclohexane is one of the most promising liquid organic hydrogen carriers. In this study, the kinetics models of toluene hydrogenation and methylcyclohexane dehydrogenation are established. The reactions were carried out in fixed bed reactors, and the kinetics parameters were fitted with the obtained data. In this experiment, hydrogenation and dehydrogenation reactions were carried out under ambient pressure. Ni/SGA_C n TES catalyst was employed for toluene hydrogenation, the fitting activation energy is 36.27 kJ/mol, and the preexponential factor is 1212 s −1 . Meanwhile, the catalyst of Pt/MgAl 2 O 4 was for methylcyclohexane dehydrogenation, the fitting activation energy is 83.92 kJ/mol, and the preexponential factor is 7.28 × 10 6 s −1 . Aspen Plus was used to simulate on a larger scale and determine the optimal process conditions: the optimum reaction conditions for toluene hydrogenation were determined to be 185°C and 0.3 MPa, and the optimized hydrogen flow rate is 3970 kg/d (The molar ratio is 5.88). Additionally, the optimal conditions for methylcyclohexane dehydrogenation are 325°C and 0.15 MPa.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".