Homogeneous catalysis using transition metal complexes is ubiquitously used for organic synthesis, as well as technologically relevant in applications such as water splitting and CO2 reduction. The key steps underlying homogeneous catalysis require a specific combination of electronic and steric effects from the ligands bound to the metal center. Finding the optimal combination of ligands is a challenging task due to the exceedingly large number of possibilities and the non-trivial ligand–ligand interactions. The classic example of Vaska's complex, trans-[Ir(PPh3)2(CO)(Cl)], illustrates this scenario. The ligands of this species activate iridium for the oxidative addition of hydrogen, yielding the dihydride cis-[Ir(H)2(PPh3)2(CO)(Cl)] complex. Despite the simplicity of this system, thousands of derivatives can be formulated for the activation of H2, with a limited number of ligands belonging to the same general categories found in the original complex. In this work, we show how DFT and machine learning (ML) methods can be combined to enable the prediction of reactivity within large chemical spaces containing thousands of complexes. In a space of 2574 species derived from Vaska's complex, data from DFT calculations are used to train and test ML models that predict the H2-activation barrier. In contrast to experiments and calculations requiring several days to be completed, the ML models were trained and used on a laptop on a time-scale of minutes. As a first approach, we combined Bayesian-optimized artificial neural networks (ANN) with features derived from autocorrelation and deltametric functions. The resulting ANNs achieved high accuracies, with mean absolute errors (MAE) between 1 and 2 kcal mol−1, depending on the size of the training set. By using a Gaussian process (GP) model trained with a set of selected features, including fingerprints, accuracy was further enhanced. Remarkably, this GP model minimized the MAE below 1 kcal mol−1, by using only 20% or less of the data available for training. The gradient boosting (GB) method was also used to assess the relevance of the features, which was used for both feature selection and model interpretation purposes. Features accounting for chemical composition, atom size and electronegativity were found to be the most determinant in the predictions. Further, the ligand fragments with the strongest influence on the H2-activation barrier were identified.

https://pubs.rsc.org/en/content/articlepdf/2020/sc/d0sc00445f

Machine learning dihydrogen activation in the chemical space surrounding Vaska's complex

Transformation of sterically hindered tertiary alkyl electrophiles under nickel-catalyzed conditions to forge C(sp3)-C bonds and simultaneously create challenging all-carbon quaternary centers has received growing attention in the recent years. The unique nature of nickel featuring flexible oxidation states ranging from Ni0 to NiIV, allows the effective activation of tertiary alkyl electrophiles through ionic (2e) or radical pathways. In nickel-catalyzed coupling of tertiary alkyl electrophiles, the competitive β-H elimination upon the resulting alkyl-Ni intermediate is relatively slow, thus benefiting the C-C bond forming process. Meanwhile, nickel-catalyzed radical addition of tertiary alkyl electrophiles to unsaturated C-C bonds has also advanced rapidly due to the successful incorporation of carboxylic acid and alcohol derivatives as radical precursors, and more importantly due to further interception of the intermediate radical adducts with nucleophiles and electrophiles to accomplish three-component cascade reactions. This review highlights these state-of-the-art nickel-catalyzed transformations of tertiary electrophiles, organized by reaction types with emphasis on the reaction mechanisms.

Nickel-catalyzed formation of quaternary carbon centers using tertiary alkyl electrophiles.

Here we report the use of pulse radiolysis and spectroelectrochemistry to generate low-valent nickel intermediates relevant to synthetically important Ni-catalyzed cross-coupling reactions and interrogate their reactivities toward comproportionation and oxidative addition processes. Pulse radiolysis provided a direct means to generate singly reduced [(dtbbpy)NiBr], enabling the identification of a rapid Ni(0)/Ni(II) comproportionation process taking place under synthetically relevant electrolysis conditions. This approach also permitted the direct measurement of Ni(I) oxidative addition rates with electronically differentiated aryl iodide electrophiles (kOA = 1.3 × 104-2.4 × 105 M-1 s-1), an elementary organometallic step often proposed in nickel-catalyzed cross-coupling reactions. Together, these results hold implications for a number of Ni-catalyzed cross-coupling processes.

The Application of Pulse Radiolysis to the Study of Ni(I) Intermediates in Ni-Catalyzed Cross-Coupling Reactions.

Although the catalytic carboxylation of unactivated alkyl electrophiles has reached remarkable levels of sophistication, the intermediacy of (phenanthroline)Ni(I)-alkyl species-complexes proposed in numerous Ni-catalyzed reductive cross-coupling reactions-has been subject to speculation. Herein we report the synthesis of such elusive (phenanthroline)Ni(I) species and their reactivity with CO2, allowing us to address a long-standing question related to Ni-catalyzed carboxylation reactions.

Ni(I)–Alkyl Complexes Bearing Phenanthroline Ligands: Experimental Evidence for CO2 Insertion at Ni(I) Centers

Nickel-catalyzed reductive carboxylation reactions of aryl electrophiles typically require the use of metallic reducing agents. At present, the prevailing perception is that these serve as both a s...

/pdf/ni-catalyzed-carboxylation-of-c-sp2-s-bonds-with-co2-1wlvx5x2kl.pdf

Ni-Catalyzed Carboxylation of C(sp2)–S Bonds with CO2: Evidence for the Multifaceted Role of Zn

Carbon-carbon bonds with CO2: Insights from computational studies

A caesium fluoride-mediated hydrocarboxylation of olefins is disclosed that does not rely on precious transition metal catalysts and ligands. The reaction occurs at atmospheric pressures of CO2 in the presence of 9-BBN as a stoichiometric reductant. Stilbenes, β-substituted styrenes and allenes could be carboxylated in good yields. The developed methodology can be used for preparation of commercial drugs as well as for gram scale hydrocarboxylation. Computational studies indicate that the reaction occurs via formation of an organocaesium intermediate.

/pdf/caesium-fluoride-mediated-hydrocarboxylation-of-alkenes-and-1zwizyakzn.pdf

Marc Obst

Papers

Ni(I)–Alkyl Complexes Bearing Phenanthroline Ligands: Experimental Evidence for CO2 Insertion at Ni(I) Centers

Carbon-carbon bonds with CO2: Insights from computational studies

Caesium fluoride-mediated hydrocarboxylation of alkenes and allenes: scope and mechanistic insights

Mechanistic Insights into Copper-Catalyzed Carboxylations