Magnetically recyclable nanocatalysts based on magnetite: an environmentally friendly and recyclable catalyst for esterification reactions
Bibliographic record
Abstract
Solid magnetic nanoparticles (magnetite = Mag) composed of Fe3O4 and magnetite coated with silica (Fe3O4/SiO2 = Mag/Si) were prepared from inexpensive starting materials. The catalytic activity of the solids was investigated for palmitic acid esterification with methanol under solvothermal conditions. Both pure Fe3O4 (Mag) and silica-coated (Mag/Si) nanoparticles exhibited high catalytic activities and were easy to recover from the reaction environment using an external magnet. Furthermore, the magnetic nanoparticle catalysts were reused without significant loss of catalytic activity and showed high durability in typical acid-catalyzed reactions. XRD and SEM analyses were conducted before and after esterification, showing almost identical particle distribution in both fresh and reused catalysts.
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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".