Synthesis and Hydrodeoxygenation Activity of Carbon Supported Molybdenum Carbide and Oxycarbide Catalysts
Bibliographic record
Abstract
Carbothermal hydrogen reduction (CHR) of ammonium heptamolybdate impregnated activated charcoal (AC) yields a mixed Mo 2 C/MoO x C y catalyst. As the CHR temperature increases (from 600 to 800 °C) the Mo 2 C content increases. At 675 °C graphite networks are generated that attach to the β-Mo 2 C particles, and at ≥700 °C agglomeration and sintering occur, all of which decrease catalyst activity. An optimal CHR temperature of ∼650 °C is identified based on the catalyst activity for the hydrodeoxygenation (HDO) of 4-methylphenol (4-MP) at 350 °C and 4.3 MPa H 2 and the high selectivity for direct deoxygenation (DDO: to yield toluene) versus hydrogenation (HYD: to yield cyclohexane). The Mo 2 C/MoO x C y catalysts have higher DDO selectivity than MoP, MoO 2, or MoS 2 when operated at similar conditions. The apparent activation energies for DDO (125 kJ/mol) and HYD (89 kJ/mol) are invariant among the catalysts with varying Mo 2 C content, but the rate per g Mo correlates with the CO uptake. The fact that the kinetics are not strong functions of the CHR reduction temperature and hence relative content of Mo 2 C versus MoO x C y suggests that the active site of the catalyst is a result of O adsorption and/or exchange with the catalyst during reaction, and these active sites occur on both Mo 2 C and MoO x C y during the HDO reaction.
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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".