Insights into Dopant-Mediated Tuning of Silica-Supported Mo Metal Centers for Enhanced Olefin Metathesis
Bibliographic record
Abstract
We show that the electronic environment around active Mo centers supported on mesoporous silicates can be tuned by the addition of transition metals creating highly dispersed bimetallic catalysts that display enhanced activity for ethylene + 2-butene metathesis to propylene. The bimetallic catalysts are prepared by incorporating electrophilic Lewis acid metals (M) such as Nb, Ta, Zr, or Hf as dopant promoters into mesoporous KIT-6 supports using a one-pot sol–gel technique followed by impregnation of the Mo species. All the bimetallic Mo/M-KIT-6 catalysts display better activity than monometallic Mo/KIT-6 catalyst (28.7 ± 1.1 mmol (mol Mo s) −1 ), with (Mo/Nb-KIT-6) catalysts exhibiting maximum propylene formation rates (54.2 ± 0.5 mmol (mol Mo s) −1 ) at an identical Mo loading. Comprehensive catalyst characterization results (deploying high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), diffuse reflectance ultraviolet–visible (DR UV–vis), X-ray photoelectron spectroscopy (XPS), and X-ray absorption spectroscopy (XAS)) qualitatively show an increased population of the four-coordinated Mo sites in the promoted Mo catalysts, while Raman spectroscopy reveals the presence of Mo dioxo species (O═Mo═O) on both the monometallic and promoted bimetallic catalysts. These results suggest that the addition of transition metals alters Mo coordination, yielding isolated bimetallic precursors [(O═) 2 Mo(−O–M)(−O–Si)] in addition to the conventional ((O═) 2 Mo(−O–Si) 2 ) species. Further, the intrinsic propylene formation rates on the bimetallic formulations follow a linear correlation with the Lewis acid strengths exhibited by the Mo dioxo species (O═Mo═O) revealing that catalyst activity can be enhanced by incorporating a second metal with increasing electrophilic character. Complementary 15 N-pyridine solid-state NMR spectra display different chemical shifts associated with the metal centers suggesting that four-coordinated dioxo MoO x species with varying geometric and electronic configurations exist, depending on the added metal. A similar linear correlation was also observed between the average chemical shifts of the adsorbed 15 N-pyridine and the Lewis acid strengths (Δ H ads,pyridine ), providing informative descriptors regarding the molecular origins of the electronic effects influencing olefin metathesis on Mo-based catalysts. Our results demonstrate that simple catalyst synthesis methods can be harnessed for tuning the electronic environment around metal centers in heterogeneous catalysts for enhancing activity and selectivity.
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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 | 0.001 |
| 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 | 0.000 |
| 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 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".