Regiospecific, one-pot, and pseudo-five-component synthesis of 6,6′-(arylmethylene)bis(2-(<i>tert</i>-butyl)4-methylphenol) antioxidants using highly sulfonated multi-walled carbon nanotubes under solvent-free conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This is the first report of an innovative, one-pot, pseudo-five-component, and solvent-free synthesis of 6,6′-(arylmethylene)bis(2-(tert-butyl)4-methylphenol) antioxidants from p-cresol, methyl tert-butyl ether, and aldehydes in the presence of sulfonated multi-walled carbon nanotubes (MWCNTs-SO 3 H) as heterogeneous, robust, and reusable catalysts under solvent-free conditions. MWCNTs-SO 3 H was prepared and characterized by some microscopic and spectroscopic techniques including scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, Raman spectroscopy, dispersibility in different solvent, and thermogravimetric analysis (one functionality every approximately five carbon atoms). The acidity of the catalyst was measured by acid–base titration (1.80 mmol g −1 ). This reaction proceeds smoothly to give the products in good yields. The catalyst was reused several times without efficient loss of its activity for the preparation of 6,6′-(arylmethylene)bis(2-(tert-butyl)4-methylphenol) antioxidants. In addition, high yields of the products and solvent-free and nontoxicity of the catalyst are other worthwhile advantages of the present method.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it