Multiple Surface Site Three-Dimensional Structure Determination of a Supported Molecular Catalyst
Bibliographic record
Abstract
The structural characterization of supported molecular catalysts is challenging due to the low density of active sites and the presence of several organic/organometallic surface groups resulting from the often complex surface chemistry associated with support functionalization. Here, we provide a complete atomic-scale description of all surface sites in an N-heterocyclic carbene based on iridium and supported on silica, at all stages of its synthesis. By combining a suitable isotope labeling strategy with the implementation of multinuclear dipolar recoupling DNP-enhanced NMR experiments, the 3D structure of the Ir-NHC sites, as well as that of the synthesis intermediates were determined. As a significant fraction of parent surface fragments does not react during the multistep synthesis, site-selective experiments were implemented to specifically probe proximities between the organometallic groups and the solid support. The NMR-derived structure of the iridium sites points to a well-defined conformation. By interpreting EXAFS spectroscopy and chemical analysis data augmented by computational studies, the presence of two coordination geometries is demonstrated: Ir-NHC fragments coordinated by a 1,5-cyclooctadiene and one Cl ligand, as well as, more surprisingly, a fragment coordinated by two NHC and two Cl ligands. This study demonstrates a unique methodology to disclose individual surface structures in complex, multisite environments, a long-standing challenge in the field of heterogeneous/supported catalysts, while revealing new, unexpected structural features of metallo-NHC-supported substrates. It also highlights the potentially large diversity of surface sites present in functional materials prepared by surface chemistry, an essential knowledge to design materials with improved performances.
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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".