Direct Synthesis of Atomically Dispersed Palladium Atoms Supported on Graphitic Carbon Nitride for Efficient Selective Hydrogenation Reactions
Bibliographic record
Abstract
Heterogeneous catalysts with atomically precise metal sites have enabled unique insight into structure–property relationships in materials science. Herein, we report the construction and selective hydrogenation performance of a single-atom palladium catalyst by confining the palladium atoms into the six-fold N-coordinating cavities of graphitic carbon nitride (g-C3N4) through a facile spatial confinement-reduction approach under mild reducing conditions. Spherical aberration correction electron microscopy and extended X-ray absorption fine structure measurements confirm the presence of atomically dispersed palladium atoms stabilized by the g-C3N4 support. Its exceptional catalytic activity was demonstrated by the hydrogenation of styrene (98% conversion, 1.5 h) and furfural (conversion of 64% and selectivity of 99%, 4 h) and hydrodechlorination of 4-chlorophenol (99% conversion and 99% selectivity, 10 min). This palladium catalyst can be reused at least five times with negligible deterioration of its activity. Importantly, the palladium atoms retained their atomic dispersion following the thermal treatment. Moreover, this synthetic method can be scaled up while retaining similar catalytic activity. Fundamental insights are provided to elucidate how the material’s structure significantly impacts the catalytic performance at the atomic scale.
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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) | 0.001 | 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) | 0.000 | 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".