Catalytic Formylation of Primary and Secondary Amines with CO<sub>2</sub> and H<sub>2</sub> Using Abundant-Metal Catalysts
Bibliographic record
Abstract
Catalytic hydrogenation of CO 2 is an efficient and selective way to prepare formic acid derivatives, but most of the highly active catalysts used for this purpose require precious metals. In this study, in situ abundant-metal complexes have been evaluated as potential catalysts for CO 2 hydrogenation to prepare formamides, including N -formylmorpholine, 2-ethylhexylformamide, and dimethylformamide, from the corresponding amines. From these initial screening results, the most active catalysts for these reactions were found to be MX 2 /dmpe in situ catalysts (M = Fe(II), Ni(II); X = Cl –, CH 3 CO 2 –, acac –; dmpe = 1,2-bis(dimethylphosphino)ethane) in DMSO. The optimal reaction conditions were found to be 100–135 °C and a total pressure of 100 bar. Morpholine was formylated with a TON value of up to 18000, which is the highest TON for the hydrogenation of CO 2 to formamides using any abundant-metal–phosphine complex. With an appropriate selection of catalyst and reaction conditions, >90–98% conversion of amine to formamide could be achieved.
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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 | 0.000 | 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 | 0.000 |
| 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 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".