Strain-Induced Cu-LaO<sub><i>x</i></sub> Strong Interaction Structures for Tandem Catalytic Upgrading of Ethanol
Bibliographic record
Abstract
Metal-oxide strong interaction (MOSI) structures are ideal arrangements of active sites to facilitate multistep reactions in a tandem manner. Up to date, however, the choice of metal oxides used to construct MOSI structures is limited to reducible oxides for most of the currently available synthesis strategies, significantly restricting the application scope of MOSI catalysts. Herein, an innovative strain-induced strategy is proposed to construct metal-irreducible oxide strong interaction catalysts. A Cu-LaO x /C catalyst can be directly achieved by reducing copper nitrate on lanthanum atomically loaded mesoporous carbon at 450 °C under argon. Combining the experimental characterization and the first-principles calculations, the La atoms are found to be favorable to locate outside the Cu nanoparticle due to the dominant strong strain effect between Cu and La atoms. The resulting Cu-LaO x /C MOSI structure exhibited excellent performance in tandem catalytic upgrading of ethanol with the product selectivity of C 4 –C 8 alcohols over 70% at an ethanol conversion of about 40% and the robust catalytic activity for more than 120 h in gas-phase catalytic ethanol conversion at 250 °C and 2 MPa. This work offers an alternative formation mechanism for the MOSI structure catalyst.
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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".