Ultra-fast Cu-based A<sup>3</sup>-coupling catalysts: faceted Cu<sub>2</sub>O microcrystals as efficient catalyst-delivery systems in batch and flow conditions
Bibliographic record
Abstract
Cu(I) catalysts were studied for the synthesis of a propargylamine via A3-coupling of aldehyde, amine, and alkyne, under solvent-free and low loading conditions, using batch microwave or flow thermal heating. We explored ultra-low loading conditions with Cu(I) salts as fast and active catalysts featuring turnover frequencies (TOFs) above 105 h−1. Well-defined octahedral and cubic Cu2O microcrystals were also successfully applied and compared with this reaction. Both types of microcrystals exhibited excellent catalytic activities within minutes, via in situ generation of low dose of Cu(I) ions within the reaction medium, to achieve TON beyond 2000 and recycling up to 10 times in a flow reactor. The study of the catalytic system demonstrated that the activity was surface-structure dependent and allowed for the design of low Cu contamination A3-coupling systems, affording a product at the decigram scale, with Cu contamination below FDA recommendations for drug synthesis, without the need for a purification procedure.
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.
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".