Механизмы реакций перекрестного сцепления Suzuki

FTIR spectroscopy can provide quantitative interpretation, but this is more challenging when spectra lack distinct or diagnostic features, even though the underlying spectral data contain subtle variations that correlate with reaction progress. Machine learning can extract these patterns, but typical workflows require large, experimentally generated datasets, creating a substantial barrier when each dataset must be collected through repeated reaction trials.

To reduce this experimental burden, the authors employed a linear mixture approximation in which each species contributes proportionally to the total absorbance. Because peak intensities scale with molecular abundance, the spectrum of a reaction mixture can be approximated as a weighted sum of the spectra of its individual components. By combining ReactIR spectra of pure reactants and products, synthetic “mimicked spectra” were generated that reproduce the major features of real mixtures. This enables construction of large training datasets using only a limited number of measured spectra.

The Suzuki–Miyaura cross‑coupling reaction was selected as a model system due to its minimal structural changes and correspondingly subtle FTIR signatures. After preprocessing, a neural network trained on mimicked spectra accurately predicted reaction yield from inline ReactIR measurements. The prediction model was capable of detecting subtle differences in reaction conditions that were not evident from physical parameters alone. Integrated into an automated flow platform, the model enabled real‑time yield estimation and efficient closed‑loop optimization. This approach demonstrates that ReactIR, when paired with synthetic spectral generation and machine learning, can serve as a quantitative process analytical technology for data‑efficient reaction development and autonomous optimization.

Ashikari, Y., Tamaki, T., Tomite, K., Yonekura, Y., & Nagaki, A. (2025). Real-time inline-IR-analysis via linear-combination strategy and machine learning for automated reaction optimization. Communications Chemistry, 8(1), 287. https://doi.org/10.1038/s42004-025-01676-y

The authors commented on the importance of elucidating the structure and composition of the catalytic active center in ordered organometallic catalytic nano-films in order to optimize the catalytic efficiency and understand the catalytic mechanism. In this work a novel ferrocene-based self-assembled hetero-bimetallic Pd/Co film (Si@FMP-Pd_xCo_1-x) on silicon wafers was synthesized and evaluated for Suzuki cross-coupling reactions. Specifically, the activity of Si@FMP-Pd_0.2/Co_0.8.was found to be significantly higher than that of either Si@FMP-Pd or homogeneous catalyst Li₂PdCl₄/CoCl₂. The researchers suggested that orientation and arrangement of catalyst on the surface and the synergism between Pd and Co was the source of the enhanced catalytic activity. 

In investigating the reaction mechanism, ReactIR measurements monitored the catalytic process in real time, tracking the evolution of intermediates related to the oxidative addition and transmetallation steps in the Suzuki reaction, with a band at 752 cm⁻¹ band serving as a marker for these surface-bound species during the catalytic cycle. These measurements revealed that there was an induction period for Si@FMP-Pd0.2Co0.8, also indicative of a heterogeneous catalytic process and in contrast to the homogeneous system (Li₂PdCl₄/CoCl₂), which did not demonstrate the induction period. The ReactIR data, combined with hot filtration and poisoning tests, confirmed that the catalysis occurred on the surface of the film and not via leached metal species in solution. This work showed that the active center contained Pd, Pd/PdO, Pd/CoO/Co₂O₃ clusters in situ formed on the organometallic surface. Thus, ReactIR played a crucial role in elucidating the catalytic mechanism for this novel bimetallic catalyst in the Suzuki reaction, verifying the heterogeneous nature and providing kinetic insights into the reaction process.

Li, T., Chen, P., Wang, M., & Wu, Y. (2024). Ferrocene assisted PD/PDO/COO Active Center in suit formed on the surface of Self-Assembly Organometallic PD/CO Film: Investigation on the formation, synergistic, and catalytic mechanism in Suzuki Cross Coupling Reaction. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4735448

The study presents a detailed mechanistic investigation of the Suzuki–Miyaura cross‑coupling under biphasic conditions, revealing how phase‑transfer catalysts (PTCs) dramatically accelerate the reaction by shifting the dominant transmetalation pathway. Using benzylic electrophiles as a challenging model system, the authors show that PTCs convert the mechanism from the classical oxo‑palladium route to a boronate‑driven pathway, enabling up to a twelve‑fold rate enhancement and allowing catalyst loadings as low as 0.001 mol%. This mechanistic understanding results from the use of DirectInject-LC technology through its online HPLC measurements, which provides reproducible, real‑time kinetic profiles even in heterogeneous mixtures that are not amenable to NMR and IR measurement. The automated LC platform allows precise tracking of electrophile consumption, boronate formation, halide inhibition, and catalyst speciation—data that would be inaccessible or unreliable with manual sampling due to phase‑separation artifacts and sample aging. These dense kinetic datasets reveal the strong influence of aqueous‑to‑organic phase ratios, the antagonistic roles of hydroxide and halide, and that PTCs modulate both palladium speciation and arylboron equilibria, clarifying the turnover‑limiting transmetalation regime and enabling exceptionally low catalyst loadings with broad substrate scope.

Shi, Y., Derasp, J. S., Maschmeyer, T., & Hein, J. E. (2024). Phase transfer catalysts shift the pathway to transmetalation in biphasic Suzuki-Miyaura cross-couplings. Nature Communications, 15(1), 5436. https://doi.org/10.1038/s41467-024-49681-4