Tuning of Acid/Base Functionalities in the MgAlO System for Ethanol Upgrade to n-Butanol
Bibliographic record
Abstract
Hydrotalcite-derived mixed metal oxides (MgAlO)-based catalysts are used for the catalytic upgrade of ethanol to butanol which adjust the catalyst structure and number of relevant active sites through changes in the Mg/Al ratio. By performing a series of reaction activity tests, kinetic experiments, FTIR characterization, CO2-TGA analysis, and in situ active center titration, qualitative and quantitative relationships between catalyst structure and catalytic performance are obtained. We found the MgAlO mixed metal oxide system can catalyze the ethanol-to-butanol process through a Guerbet reaction pathway, though the process is kinetically limited. The data suggest that strong basic centers hosted in Mg-O sites are the most catalytically relevant function in the MgAlO material, as they control enolate formation, which is likely the rate limiting step of the aldol condensation stage in the Guerbet reaction.
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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) | 0.000 | 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 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".