Influence of 1-Butene Adsorption on the Dimerization Activity of Single Metal Cations on UiO-66 Nodes
Bibliographic record
Abstract
Grafting metal cations to missing linker defect sites in zirconium-based metal-organic frameworks, such as UiO-66, produces a uniquely well-defined and homotopic catalytically active site. We present here the synthesis and characterization of a group of UiO-66-supported metal catalysts, M-UiO-66 (M = Ni, Co, Cu, and Cr), for the catalytic dimerization of alkenes. The hydrogen-deuterium exchange via deuterium oxide adsorption followed by infrared spectroscopy showed that the last molecular water ligand desorbs from the sites after evacuation at 300 °C leading to M(OH)-UiO-66 structures. Adsorption of 1-butene is studied using calorimetry and density functional theory techniques to characterize the interactions of the alkene with metal cation sites that are found active for alkene oligomerization. For the most active Ni-UiO-66, the removal of molecular water from the active site significantly increases the 1-butene adsorption enthalpy and almost doubles the catalytic activity for 1-butene dimerization in comparison to the presence of water ligands. Other M-UiO-66 (M = Co, Cu, and Cr) exhibit 1-3 orders of magnitude lower catalytic activities compared to Ni-UiO-66. The catalytic activities correlate linearly with the Gibbs free energy of 1-butene adsorption. Density functional theory calculations probing the Cossee-Arlman mechanism for all metals support the differences in activity, providing a molecular level understanding of the metal site as the active center for 1-butene dimerization.
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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
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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".