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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| 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".