Kinetic Study of Pd-Promoting Effect on Cu/ZnO/Al2O3 Catalyst for Glycerol Hydrogenolysis to Produce 1,2-Propanediol at Low Hydrogen Pressure
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Bibliographic record
Abstract
The promoting effect of Pd on a Cu/ZnO/Al2O3 catalyst for the aqueous glycerol hydrogenolysis process to produce 1,2-propanediol was studied. At a lower hydrogen pressure (2.07 MPa), using the Cu/ZnO/Al2O3 catalyst with 2 wt% Pd doped, could significantly improve the glycerol conversion (97.2%) and 1,2-propanediol selectivity (93.3%) compared with the unpromoted catalyst (69.4% and 89.7%, respectively). A power-law kinetic model, which took into account all the elementary reactions including glycerol dehydration and its reverse reaction, acetol hydrogenation, side reactions and ethylene glycol formation, was developed to comprehensively investigate the effect of Pd. Though the rate of glycerol dehydration using the Pd-promoted catalyst was found to be slightly lower, mainly due to the reduced number of acidic sites after adding Pd, the glycerol conversion rate was notably higher compared with using the unpromoted catalyst, mainly attributed to the enhanced activity of acetol hydrogenation by Pd. The rapid hydrogenation of acetol can inhibit the reverse reaction of glycerol dehydration, resulting in a higher glycerol conversion rate, so that glycerol dehydration is considered as the rate-determining step. In contrast, when the unpromoted catalyst was used, the rate of reverse glycerol dehydration was drastically increased due to the elevated acetol concentration, especially at a lower hydrogen pressure, resulting in a slower glycerol conversion rate; thus, acetol hydrogenation became the rate determining step. In addition, Pd can improve the reducibility of the catalyst, allowing the CuO to be reduced in situ during the reaction. Therefore, catalyst deactivation due to any potential oxidation of metallic copper during the reaction can be prevented.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it