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 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".