Photocatalytic C(sp<sup>3</sup>)-H and C(sp<sup>2</sup>)-H Carboxylation of Amines with CO<sub>2</sub> Using a Sustainable Covalent Organic Framework/gC<sub>3</sub>N<sub>4</sub> Composite
Bibliographic record
Abstract
Carboxylation of amines is an important route to obtain amino acids. Herein, we have reported the synthesis and characterizations of a new COF/gC 3 N 4 composite which acted as a heterogeneous photocatalyst for the carboxylation of unprotected indoles and N-Boc-benzyl amines. We have used SnO 2 nanoparticles as the cocatalyst and CO 2 as the carbon source under visible light irradiation. This gave a range of carboxylated products both with unprotected indoles and N-Boc-benzylamines with high yield. Control experiments gave the optimum reaction conditions for this photocatalytic carboxylation. Light dependency of this reaction was confirmed by altering the intensity of light. Here, we have synthesized two different catalysts, TpBpy and Tz COF, and the gC 3 N 4 heterojunction which showed excellent photocatalytic activity. The photocatalysts, COF/gC 3 N 4, are recyclable and reusable for several cycles without a significant loss in performance. The synthesis of a drug compound Clopidogrel and drug formation unit Tirofiban is demonstrated with these photocatalytic protocols.
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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".