A computational investigation of the selectivity and mechanism of the Lewis acid catalyzed oxa‐Diels–Alder cycloaddition of substituted diene with benzaldehyde

Abstract

The selectivity and the mechanism of the uncatalyzed and AlCl3 catalyzed hetero‐Diels–Alder reaction (HDR) between ([E]‐4‐methylpenta‐2,4‐dienyloxy)(tert‐butyl)dimethylsilane 1 and benzaldehyde 2 have been studied using density functional theory at the MPWB1K/6‐31G(d) level of theory. The uncatalyzed HDR between diene 1 and alkene 2 is characterized by a polar character and proceeds via an asynchronous one‐step mechanism for the meta paths and synchronous for the ortho ones. In the presence of AlCl3 catalyst, the mechanism changes to be stepwise, while the first step is the rate‐determining step. The activation energies widely decrease, and the polar character increases dramatically. A large analysis of the mechanism is performed using the activation strain model/energy decomposition analysis (ASM/EDA) model, the natural bond orbital (NBO) and state specific dual descriptors (SSDDs). The obtained results indicate that the combined interaction energy associated with the distortion of the reactants in these HDR are at the origin of the observed kinetics. NBO analyses were applied to estimate the Lewis‐acid catalyst donor‐acceptor interaction with the molecular system. The SSDD analysis shed light into the orientation effects on the reaction kinetics by providing important information about charge transfer interactions during the chemical reaction. It indicates that the more favorable HDR pathway have the lowest excitation energies, facilitating the interaction between diene 1 and benzaldehyde 2 moieties. Non‐covalent interaction (NCI) and QTAIM analyses of the meta‐endo structure indicate that the presence of several weak NCIs formed at this approach is at the origin of the meta‐endo selectivity.

Coordination mode and stability of the tetrahydroborate ligand in group 10 metal pincer complexes

“…Atoms in Molecules (AIM) topology analysis and Interaction Region Indicator (IRI) analysis were extensively used to explore bonding in different systems. [21][22][23][24][25][26] In order to further confirm the coordination and that of Pt-PBP displayed absorptions at 2393 and 2082 cm −1 , corresponding to the B-H t and B-H b stretching vibrations. 1,4 The spectral pattern is similar to that of the related pincer nickel and palladium complexes with a η 2 -H 2 BH 2 ligand.…”

“…Atoms in Molecules (AIM) topology analysis and Interaction Region Indicator (IRI) analysis were extensively used to explore bonding in different systems. 21–26 In order to further confirm the coordination mode of the BH 4 − ligand in Pt-POCOP , we performed the AIM and IRI analyses. The results are presented in Fig.…”

Synergy of machine learning and density functional theory calculations for predicting experimental Lewis base affinity and Lewis polybase binding atoms

“…Among computational methods, density functional theory (DFT) has been demonstrated to be a powerful prediction tool for binding energy, electron population, excited states, and other properties of Lewis acid-base adducts. 7,[9][10][11][12][13] The Lewis bases with multiple LB atoms (hereinafter called Lewis polybases) 14 have been recognized in numerous promising applications of Lewis interactions, especially organic semiconducting materials. [15][16][17][18] Understanding the binding propensity and related properties of each LB atom in a Lewis polybase would contribute to the theoretical framework of Lewis interactions as well as improve their effectiveness in different applications.…”

“…Therefore, predictive controls and rational designs of Lewis acid–base adducts require chemistry fundamentals, experimental experience, and computational simulations. Among computational methods, density functional theory (DFT) has been demonstrated to be a powerful prediction tool for binding energy, electron population, excited states, and other properties of Lewis acid–base adducts 7,9–13 …”

Synergy of Machine Learning and Density Functional Theory Calculations for Predicting Experimental Lewis Base Affinity and Lewis Polybase Binding Atoms

“…Among computational methods, DFT has been demonstrated to be a powerful prediction tool for binding energy, electron population, excited states, and other properties of Lewis acid-base adducts. 7,[9][10][11][12][13] The Lewis bases with multiple LB atoms (hereinafter called Lewis polybases) 14 have been recognized in numerous promising applications of Lewis interaction, especially organic semiconducting materials. [15][16][17][18] Understanding the binding propensity and related properties of each LB atom in a Lewis polybase would contribute to the theoretical framework of Lewis interaction as well as improve their effectiveness in different applications.…”