Knölker Iron Catalysts for Hydrogenation Revisited: A Nonspectator Solvent and Fine-Tuning

%VBur index and steric maps: from predictive catalysis to machine learning

Steric indices are parameters used in chemistry to describe the spatial arrangement of atoms or groups of atoms in molecules. They are important in determining the reactivity, stability, and physical properties of chemical compounds. One commonly used steric index is the steric hindrance, which refers to the obstruction or hindrance of movement in a molecule caused by bulky substituents or functional groups. Steric hindrance can affect the reactivity of a molecule by altering the accessibility of its reactive sites and influencing the geometry of its transition states. Notably, the Tolman cone angle and %VBur are prominent among these indices. Actually, steric effects can also be described using the concept of steric bulk, which refers to the space occupied by a molecule or functional group. Steric bulk can affect the solubility, melting point, boiling point, and viscosity of a substance. Even though electronic indices are more widely used, they have certain drawbacks that might shift preferences towards others. They present a higher computational cost, and often, the weight of electronics in correlation with chemical properties, e.g. binding energies, falls short in comparison to %VBur. However, it is worth noting that this may be because the steric index inherently captures part of the electronic content. Overall, steric indices play an important role in understanding the behaviour of chemical compounds and can be used to predict their reactivity, stability, and physical properties. Predictive chemistry is an approach to chemical research that uses computational methods to anticipate the properties and behaviour of these compounds and reactions, facilitating the design of new compounds and reactivities. Within this domain, predictive catalysis specifically targets the prediction of the performance and behaviour of catalysts. Ultimately, the goal is to identify new catalysts with optimal properties, leading to chemical processes that are both more efficient and sustainable. In this framework, %VBur can be a key metric for deepening our understanding of catalysis, emphasizing predictive catalysis and sustainability. Those latter concepts are needed to direct our efforts toward identifying the optimal catalyst for any reaction, minimizing waste, and reducing experimental efforts while maximizing the efficacy of the computational methods.

Stereoretentive Formation of Cyclobutanes from Pyrrolidines: Lessons Learned from DFT Studies of the Reaction Mechanism

The stereoselective synthesis of cyclobutanes that possess an array of stereocenters in a contiguous fashion has attracted the wide interest of the synthetic community. Cyclobutanes can be generated from the contraction of pyrrolidines through the formation of 1,4-biradical intermediates. Little else is known about the reaction mechanism of this reaction. Here, we unveil the mechanism for this stereospecific synthesis of cyclobutanes by means of density functional theory (DFT) calculations. The rate-determining step of this transformation corresponds to the release of N₂ from the 1,1-diazene intermediate to form an open-shell singlet 1,4-biradical. The formation of the stereoretentive product is explained by the barrierless collapse of this open-shell singlet 1,4-biradical. The knowledge of the reaction mechanism is used to predict that the methodology could be amenable to the synthesis of [2]-ladderanes and bicyclic cyclobutanes.

Photoredox catalysis leading to triazolo-quinoxalinones at room temperature: selectivity of the rate determining step

The interest in the fusion product of quinoxalinone skeletons and 1,2,3-triazole units has greatly increased in recent years since they are known to be agonists of G-protein-coupled Niacin receptor 109A and inhibitors of the benzodiazepine and adenosine receptors. Here, we unveil the mechanism for the photoredox catalyzed synthesis of those scaffolds by means of DFT calculations. The calculations indicate that the rate determining step of this transformation is the attack of the in situ generated radical intermediate on the CN bond of the quinoxalinone species to form a new C-C bond. Predictive chemistry here reveals that the energy difference is so subtle, and gives the recipe of which substituents, sterically and electronically, can fit to perform the reaction at room temperature.

A predictive journey towards trans-thioamides/amides

The cis-trans isomerization of (thio)amides was studied by DFT calculations to get the model for the higher preference for the cis conformation by guided predictive chemistry, suggesting how to select the alkyl/aryl substituents on the C/N atoms that lead to the trans isomer. Multilinear analysis, together with cross-validation analysis, helped to select the best fitting parameters to achieve the energy barriers of the cis to trans interconversion, as well as the relative stability between both isomers. Double experimental check led to the synthesis of the best trans candidate with sterically demanding t-butyl substituents, confirming the utility of predictive chemistry, bridging organic and computational chemistry.