Synthesis and screening of heterogeneous multimetallic nanoparticle catalysts for mono-, poly- and heteroaromatic hydrogenation activity under mild conditions
Bibliographic record
Abstract
Nanoparticle catalysts have shown to be advantageous over traditional catalysts for many reasons and active for a wide variety of reactions. This thesis describes an approach for the synthesis and screening of heterogeneous multimetallic nanoparticle catalysts for aromatic hydrogenation activity in a quick and time efficient manner, as well as detailed testing and characterization of identified active catalysts. Over 90 mono- and bimetallic nanoparticle catalysts supported on alumina were screened for toluene hydrogenation activity under ambient conditions. Through this approach, four catalysts were determined to be active: RhPt/Al2O3, RuPt/Al2O3, IrPt/Al2O3, and IrRh/Al2O3. These catalysts were further tested in bulk, and RhPt/Al2O3 was confirmed to be the catalyst with the highest observed rate of all the bimetallic combinations screened. Further studies were then performed where the metal loading, temperature, pressure and substrate to metal ratios were varied to determine the effects of these variables on the activity of the RhPt/Al2O3 catalyst, and a CS2 poisoning study was performed on this catalyst to determine the number of active sites. TEM, XPS and BET were used to characterize the active catalysts. Based on the success of the developed approach, a series of trimetallic nanoparticle catalysts were then synthesized and tested for the hydrogenation of toluene under ambient conditions and one trimetallic catalyst was selected for further studies. Next, a series of multimetallic nanoparticle catalysts supported on a variety of metal oxides were synthesized and screened for catalytic activity. Using the High Throughput Facility at the Centre for Catalysis Research and Innovation at the University of Ottawa, 72 different catalysts were screened for catalytic activity for the hydrogenation of toluene, naphthalene, pyridine, indole, quinoline, thiophene and benzothiophene under mild conditions. Bulk kinetic studies, including temperature and pressure studies, were performed using select catalysts for the hydrogenation of naphthalene and quinoline and a quinoline loading study was also conducted. Standard materials characterization techniques were used to acquire information about the size and oxidation state of the nanoparticle catalysts. To conclude this work, further research directions including expansions of this thesis work and further directions for the field of nanoparticle catalysis were suggested.
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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 | 0.000 | 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) | 0.000 | 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".