A Zirconium-based Metal–Organic Framework as an Effective Green Catalyst for the Synthesis of Biodiesel
Bibliographic record
Abstract
CAU-28 (CAU = Christian-Albrechts-University) is a zirconium-based metal–organic framework (MOF) that was first dis-covered in 2017. In addition to its biorenewable linker and green synthesis, which uses a microwave for only 2 hours, this MOF also features high thermal and chemical stability, surface area, and porosity. The hexanuclear zirconium clusters in CAU-28 are connected to only eight furan-2,5-dicarboxylic acid linkers, resulting in four open metal sites per cluster. These open metal sites display Lewis acidic properties and can be taken advantage of for many applications, including catalysis. In this work, we demonstrate the high potential of CAU-28 as a green catalyst to produce biodiesel through esterification reactions. Under optimized catalytic conditions, CAU-28 is able to convert oleic acid to its fatty acid methyl ester counterpart with high selectivity, using a catalyst loading of only 5 wt.% and 1:24 molar ratio of oleic acid:methanol, at 90 °C for 90 min. Furthermore, the catalyst also shows high stability, maintaining its activity for three reaction cycles.
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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".