Phthalocyanine formation using metals in primary alcohols at room temperature
Bibliographic record
Abstract
Lithium metal added to a solution of 4-neopentoxyphthalonitrile in 1-octanol or other long-chain primary alcohols at room temperature resulted in phthalocyanine formation at a reasonable rate in good yield, while preformed lithium 1-octanolate under the same conditions gave 2,9,16,23-tetraneopentoxyphthalocyanine, but in lower yield at a slower rate. The use of lower-molecular-weight alcohols slowly gave a phthalocyanine in lower yields. Reverse micelle formation when using long-chain alcohols is proposed as a possibility for enhanced phthalocyanine formation at room temperature. 2,9,16,23-Tetrasubstituted phthalocyanines and metallated phthalocyanines were prepared at room temperature from 4-neopentoxyphthalonitrile, 4-bis(4-methoxyphenyl)methoxyphthalonitrile, 4-[1-(4-ethoxy-3-methoxyphenyl)-1-phenyl]methoxyphthalonitrile and phthalonitrile using lithium 1-octanolate in 1-octanol or by the addition, to a solution of the phthalonitrile in ethanol, of calcium turnings or, to a solution of the phthalonitrile in methanol, of magnesium, zinc, iron or copper powder. The tetrasubstituted phthalocyanines produced exhibited a non-statistical distribution of regioisomers, indicating that electronic effects become important in room-temperature cyclotetramerization of phthalonitriles to phthalocyanines.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".