Stable Cu Catalysts Supported by Two‐dimensional SiO<sub>2</sub> with Strong Metal–Support Interaction
Bibliographic record
Abstract
Abstract Cu‐based catalysts exhibit excellent performance in hydrogenation reactions. However, the poor stability of Cu catalysts under high temperatures has restricted their practical applications. The preparation of stable Cu catalysts supported by SiO 2 with strong metal–support interaction (SMSI) has thus aroused great interest due to the high abundance, low toxicity, feasible processability, and low cost of SiO 2 . The challenge in the construction of such SMSI remains to be the inertness of SiO 2 . Herein, a simple and scalable method is developed to prepare 2D silica (2DSiO 2 ) supported Cu catalysts with SMSI by carefully manipulating the topological exfoliation of CaSi 2 with CuCl 2 and thereafter calcination. The prepared Cu‐2DSiO 2 catalysts with the unique encapsulated Cu nanoparticles exhibit excellent activity and long‐term stability in high‐temperature CO 2 hydrogenation reactions. This feasible and low‐cost solution for stabilizing Cu catalysts might shed light on their realistic applications.
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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".