Hybrid organic‐inorganic Cu(II) iminoisonicotine@TiO <sub>2</sub> @Fe <sub>3</sub> O <sub>4</sub> heterostructure as efficient catalyst for cross‐couplings
Bibliographic record
Abstract
Abstract Two novel mononuclear copper (II) complex catalysts were synthesized from a new tridentate iminoisonicotine ligand (HL) by coordination with Cu(II) ion, with (CuL@TiO 2 @Fe 3 O 4 ) and without (CuL) immobilization on TiO 2 ‐coated nanoparticles of Fe 3 O 4 . The ester moiety on the back of the ligand was utilized for immobilization on nanoparticles of Fe 3 O 4 . Both ligand and CuL complex were fully characterized by using alternative spectral techniques (nuclear magnetic resonance, infrared, ultraviolet‐visible and mass spectroscopy, and elemental analyses). Different analytical techniques were used to identify the structural feature and morphology of the immobilized copper catalyst (CuL@TiO 2 @Fe 3 O 4 ) shell‐shell‐core system. The structural analysis revealed that the catalyst system is composed of both agglomerated nanospheres and deformed nanorods. Both copper catalysts, immobilized CuL@TiO 2 @Fe 3 O 4 and un‐immobilized CuL were studied in heterogeneous and homogeneous catalysis, respectively, for Suzuki‐Miyaura (C–C) and Buchwald‐Hartwig (C–N) cross‐coupling reactions of various heteroaryl halides. Both catalysts showed good catalytic potential under the controlled optimal reaction conditions. In contrast to the homogeneous catalyst (CuL), the heterogeneous catalyst (CuL@TiO 2 @Fe 3 O 4 ) showed slightly better catalytic performance. The characteristic obtains supported the catalytic potential of the current samples. Reusability/recycling of both catalysts was also investigated in C–C cross‐coupling reactions. It was found that the homogeneous catalyst (CuL) could be only recycled up to three times, whereas the heterogeneous one (CuL@TiO 2 @Fe 3 O 4 ) could be reused up to seven times with good efficiency.
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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".