Characterizing Substrate–Surface Interactions on Alumina-Supported Metal Catalysts by Dynamic Nuclear Polarization-Enhanced Double-Resonance NMR Spectroscopy
Bibliographic record
Abstract
The characterization of nanometer-scale interactions between carbon-containing substrates and alumina surfaces is of paramount importance to industrial and academic catalysis applications, but it is also very challenging. Here, we demonstrate that dynamic nuclear polarization surface-enhanced NMR spectroscopy (DNP SENS) allows the unambiguous description of the coordination geometries and conformations of the substrates at the alumina surface through high-resolution measurements of 13 C– 27 Al distances. We apply this new technique to elucidate the molecular-level geometry of 13 C-enriched methionine and natural abundance poly(vinyl alcohol) adsorbed on γ-Al 2 O 3 -supported Pd catalysts, and we support these results with element-specific X-ray absorption near-edge measurements. This work clearly demonstrates a surprising bimodal coordination of methionine at the Pd–Al 2 O 3 interface.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".