Engineering the atomic interface of porous ceria nanorod with single palladium atoms for hydrodehalogenation reaction
Bibliographic record
Abstract
Tuning the electronic properties of single atom catalysts (SACs) between the central metal and the neighboring surface atoms has emerged as an efficient strategy to boost catalytic efficiency and metal utilization. Here we describe a simple and efficient approach to create atomically dispersed palladium atoms supported over defect-containing porous ceria nanorod containing palladium up to 0.26 wt.%. The existence of singly dispersed palladium atoms is confirmed by spherical aberration correction electron microscopy and extended X-ray absorption fine structure measurements. This catalyst shows excellent efficiency in hydrodehalogenation reactions at low H 2 pressure under mild conditions, along with satisfactory recyclability and scalability. Density functional theory (DFT) calculations reveal that the high activity stems from the spatial isolation of palladium atoms and the modified electronic structure of palladium confined in defect-containing ceria nanorod. This work may lay the foundation for the facile creation of single atom catalysts within the synthetic community and shed light on the possibility for scale-up production.
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 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".