Shaping Chirality via Stereoselective, Organocatalytic [4+2] Cycloadditions involving Heterocyclic ortho-Quinodimethanes

Polycyclic compounds bearing a complex heterocyclic core such as an aromatic heterocycle "fused" with one or more functionalized rings, are widespread leading molecules in the domain of synthetic organic chemistry and pharmaceuticals. Although many synthetic methodologies have been devised to access achiral, fused heteroaromatic scaffolds, or related chiral variants adorned with out-of-cycle stereogenic elements, equally efficient strategies to afford chiral heterocycles featuring in-cycle stereocenters, exist to a lesser extent and presently represent a growing field of investigation. The mild, organocatalytic generation of elusive ortho-quinodimethane intermediates (oQDMs), derived from suitable heteroaromatic carbonyl- or carbonyl-like pronucleophiles has recently proved successful in the synthesis of such peculiar chiral architectures via stereoselective [4+2] cycloadditions. This review provides an overview of the most important advances attained in this field over the last decade.

A genetic optimization strategy with generality in asymmetric organocatalysis as a primary target

A catalyst possessing a broad substrate scope, in terms of both turnover and enantioselectivity, is sometimes called "general". Despite their great utility in asymmetric synthesis, truly general catalysts are difficult or expensive to discover via traditional high-throughput screening and are, therefore, rare. Existing computational tools accelerate the evaluation of reaction conditions from a pre-defined set of experiments to identify the most general ones, but cannot generate entirely new catalysts with enhanced substrate breadth. For these reasons, we report an inverse design strategy based on the open-source genetic algorithm NaviCatGA and on the OSCAR database of organocatalysts to simultaneously probe the catalyst and substrate scope and optimize generality as a primary target. We apply this strategy to the Pictet-Spengler condensation, for which we curate a database of 820 reactions, used to train statistical models of selectivity and activity. Starting from OSCAR, we define a combinatorial space of millions of catalyst possibilities, and perform evolutionary experiments on a diverse substrate scope that is representative of the whole chemical space of tetrahydro-β-carboline products. While privileged catalysts emerge, we show how genetic optimization can address the broader question of generality in asymmetric synthesis, extracting structure-performance relationships from the challenging areas of chemical space.

Methods for the Preparation of Silica and Its Nanoparticles from Different Natural Sources

Silica (SiO2), a component of the earth's crust, has been in use for many nanotechnological applications. This review presents one of the newest methods for safer, more affordable, and more ecologically friendly production of silica and its nanoparticles from the ashes of agricultural wastes. The production of SiO2 nanoparticles (SiO2NPs) from different agricultural wastes, including rice husk, rice straw, maize cobs, and bagasse, was systematically and critically discussed. The review also emphasizes current issues and possibilities linked with contemporary technology to raise awareness and stimulate scholars' insight. Furthermore, the processes involved in isolating silica from agricultural wastes were explored in this work.

Kinetic Barrier Diagrams to Visualize and Engineer Molecular Nonequilibrium Systems

Molecular nonequilibrium systems hold great promises for the nanotechnology of the future. Yet, their development is slowed by the absence of an informative representation. Indeed, while potential energy surfaces comprise in principle all the information, they hide the dynamic interplay of multiple reaction pathways underlying nonequilibrium systems, i.e., the degree of kinetic asymmetry. To offer an insightful visual representation of kinetic asymmetry, we extended an approach pertaining to catalytic networks, the energy span model, by focusing on system dynamics - rather than thermodynamics. Our approach encompasses both chemically and photochemically driven systems, ranging from unimolecular motors to simple self-assembly schemes. The obtained diagrams give immediate access to information needed to guide experiments, such as states' population, rate of machine operation, maximum work output, and effects of design changes. The proposed kinetic barrier diagrams offer a unifying graphical tool for disparate nonequilibrium phenomena.

Theory-guided development of homogeneous catalysts for the reduction of CO2 to formate, formaldehyde, and methanol derivatives

The stepwise catalytic reduction of carbon dioxide (CO₂) to formic acid, formaldehyde, and methanol opens non-fossil pathways to important platform chemicals. The present article aims at identifying molecular control parameters to steer the selectivity to the three distinct reduction levels using organometallic catalysts of earth-abundant first-row metals. A linear scaling relationship was developed to map the intrinsic reactivity of 3d transition metal pincer complexes to their activity and selectivity in CO₂ hydrosilylation. The hydride affinity of the catalysts was used as a descriptor to predict activity/selectivity trends in a composite volcano picture, and the outstanding properties of cobalt complexes bearing bis(phosphino)triazine PNP-type pincer ligands to reach the three reduction levels selectively under different reaction conditions could thus be rationalized. The implications of the composite volcano picture were successfully experimentally validated with selected catalysts, and the challenging intermediate level of formaldehyde could be accessed in over 80% yield with the cobalt complex 6. The results underpin the potential of tandem computational-experimental approaches to propel catalyst design for CO₂-based chemical transformations.

Dodging the Conventional Reactivity of o-Alkynylanilines under Gold Catalysis for Distal 7-endo-dig Cyclization

A direct ring-closing strategy involving a less facile 7-endo-dig carbacyclization of o-alkynylaniline derivatives for the synthesis of benzo[b]azepines has been presented. The trivial well-documented 5-endo-dig cyclization in o-alkynylaniline derivatives due to high nucleophilicity of nitrogen has been overcome by using their vinylogous amides under gold catalysis to access a wide array of benzo[b]azepines in an atom economical way with excellent functional group compatibility. Deuterium scrambling experiments and DFT studies favor a mechanism involving stabilizing conformational change of the initially formed seven-membered vinyl gold intermediate through a key cyclopropyl gold carbene intermediate and its subsequent protodeauration mediated by the counter anion.

Overreact, an in silico lab: Automative quantum chemical microkinetic simulations for complex chemical reactions

Today's demand for precisely predicting chemical reactions from first principles requires research to go beyond Gibbs' free energy diagrams and consider other effects such as concentrations and quantum tunneling. The present work introduces overreact, a novel Python package for propagating chemical reactions over time using data from computational chemistry only. The overreact code infers all differential equations and parameters from a simple input that consists of a set of chemical equations and quantum chemistry package outputs for each chemical species. We evaluate some applications from the literature: gas-phase eclipsed-staggered isomerization of ethane, gas-phase umbrella inversion of ammonia, gas-phase degradation of methane by chlorine radical, and three solvation-phase reactions. Furthermore, we comment on a simple solvation-phase acid-base equilibrium. We show how it is possible to achieve reaction profiles and information matching experiments.

Mapping Catalyst–Solvent Interplay in Competing Carboamination/Cyclopropanation Reactions

Group 9 metals, in particular Rh^III complexes with cyclopentadienyl ligands, are competent C−H activation catalysts. Recently, a Cp*Rh^III‐catalyzed reaction of alkenes with N‐enoxyphthalimides showed divergent outcome based on the solvent, with carboamination favored in methanol and cyclopropanation in 2,2,2‐trifluoroethanol (TFE). Here, we create selectivity and activity maps capable of unravelling the catalyst‐solvent interplay on the outcome of these competing reactions by analyzing 42 cyclopentadienyl metal catalysts, Cp^XM^III (M=Co, Rh, Ir). These maps not only can be used to rationalize previously reported experimental results, but also capably predict the behavior of untested catalyst/solvent combinations as well as aid in identifying experimental protocols that simultaneously optimize both catalytic activity and selectivity (solutions in the Pareto front). In this regard, we demonstrate how and why the experimentally employed Cp*Rh^III catalyst represents an ideal choice to invoke a solvent‐induced change in reactivity. Additionally, the maps reveal the degree to which even perceived minor changes in the solvent (e. g., replacing methanol with ethanol) influence the ratio of carboamination and cyclopropanation products. Overall, the selectivity and activity maps presented here provide a generalizable tool to create global pictures of anticipated reaction outcome that can be used to develop new experimental protocols spanning metal, ligand, and solvent space.

Exploring the temperature effect on enantioselectivity of a Baeyer-Villiger biooxidation by the 2,5-DKCMO module: The SLM approach

Temperature is a crucial parameter for biological and chemical processes. Its effect on enzymatically catalysed reactions has been known for decades, and the stereo- and enantiopreference are often temperature-dependent. For the first time, we present the temperature effect on the Baeyer-Villiger oxidation of rac- bicyclo[3.2.0]hept-2-en-6-one by the type II Bayer-Villiger monooxygenase, 2,5-DKCMO. In the absence of a reductase and driven by the hydride-donation of a synthetic nicotinamide analogue, the clear trend for a decreasing enantioselectivity at higher temperatures was observed. "Traditional" approaches such as the determination of the enantiomeric ratio (E) appeared unsuitable due to the complexity of the system. To quantify the trend, we chose to use the 'Shape Language Modelling' (SLM), a tool that allows the reaction to be described at all points in a shape prescriptive manner. Thus, without knowing the equation of the reaction, the substrate ee can be estimated that at any conversion.

Chemical reaction network knowledge graphs: the OntoRXN ontology

Abstract

The organization and management of large amounts of data has become a major point in almost all areas of human knowledge. In this context, semantic approaches propose a structure for the target data, defining ontologies that state the types of entities on a certain field and how these entities are interrelated. In this work, we introduce OntoRXN, a novel ontology describing the reaction networks constructed from computational chemistry calculations. Under our paradigm, these networks are handled as undirected graphs, without assuming any traversal direction. From there, we propose a core class structure including reaction steps, network stages, chemical species, and the lower-level entities for the individual computational calculations. These individual calculations are founded on the OntoCompChem ontology and on the ioChem-BD database, where information is parsed and stored in CML format. OntoRXN is introduced through several examples in which knowledge graphs based on the ontology are generated for different chemical systems available on ioChem-BD. Finally, the resulting knowledge graphs are explored through SPARQL queries, illustrating the power of the semantic approach to standardize the analysis of intricate datasets and to simplify the development of complex workflows.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13321-022-00610-x.

A Theoretical Study on the Structural, Electronic, and Magnetic Properties of Bimetallic Pt13−nNin (N = 0, 3, 6, 9, 13) Nanoclusters to Unveil the Catalytic Mechanisms for the Water-Gas Shift Reaction

In this work, first-principles calculations by using density functional theory at the GFN-xTB level, are performed to investigate the relative stability and structural, electronic, and magnetic properties of bimetallic Pt13−nNin (n = 0, 3, 6, 9, 13) nanoclusters by using corrected Hammer and Nørskov model. In addition, by employing the reaction path and the energetic span models, the energy profile and the turnover frequency are calculated to disclose the corresponding reaction mechanism of the water-gas shift reaction catalyzed by these nanoclusters. Our findings render that Ni causes an overall shrinking of the nanocluster’s size and misalignment of the spin channels, increasing the magnetic nature of the nanoclusters. Pt7Ni6 nanocluster is the most stable as a result of the better coupling between the Pt and Ni d-states. Pt4Ni9 maintains its structure over the reaction cycle, with a larger turnover frequency value than Pt7Ni6. On the other hand, despite Pt10Ni3 presenting the highest value of turnover frequency, it suffers a strong structural deformation over the completion of a reaction cycle, indicating that the catalytic activity can be altered.

Investigating the mechanism and origins of selectivity in palladium-catalysed carbene insertion cross-coupling reactions

The mechanism of palladium-catalysed carbene insertion cross-coupling reactions has been experimentally and computationally studied, with carbene insertion identified as the likely selectivity determining step.

Dynamic Microkinetic Modeling for Heterogeneously Catalyzed Hydrogenation Reactions: a Coverage-Oriented View

In most studies, the microkinetics for multistep reactions are numerically solved due to their complexity; the obtained numerical results are only valid under given reaction conditions at a static point. In this work, the microkinetics of heterogeneously catalyzed hydrogenation reactions are analytically solved as a function of three coupled physical parameters, which are energy, reaction rate, and coverage. The results correlate the surface reactions and the gaseous-phased reactant/product by energy and thus provide a dynamic view over the whole reaction process rather than at a static point. The analytical expressions are given for a simple hydrogenation reaction and three more complicated hypothetical hydrogenation reactions with side products, side reaction paths, or even multiple active sites. Compared with the numerical solution, the analytical solution is valid under all reaction conditions in practice and can provide more guidance to optimize the overall outcome or catalyst development.

Chalcogen vs Halogen Bonding Catalysis in a Water-Bridge-Cocatalyzed Nitro-Michael Reaction

Recently, a tellurium-based chalcogen-bond-catalyzed nitro-Michael reaction was reported ( Angew. Chem. Int. Ed. 2019, 58, 16923), taking advantage of the strong Lewis acidity of the catalyst. This species was found to be more effective than an analogous iodine-based halogen bond organocatalyst. Herein, we present a detailed mechanistic and kinetic analysis of these catalytic cycles including the influence of the solvent (and the performance of different intrinsic solvation models). While the chalcogen bonding interaction is fundamental to activate the C-C bond formation, we found that the presence of a two-water molecular bridge is critical to allow the following, otherwise high-energy proton transfer step. Even though the iodine-based halogen bonding interaction is stronger than the tellurium-based chalcogen bonding one, which makes the former a stronger Lewis acid and hence in principle a more efficient catalyst, solvation effects explain the smaller energy span of the latter.

The Genesis of Molecular Volcano Plots

ConspectusFor the past two decades, linear free energy scaling relationships and volcano plots have seen frequent use as computational tools that aid in understanding and predicting the catalytic behavior of heterogeneous and electrocatalysts. Based on Sabatier's principle, which states that a catalyst should bind a substrate neither too strongly nor too weakly, volcano plots provide an estimate of catalytic performance (e.g., overpotential, catalytic cycle thermodynamics/kinetics, etc.) through knowledge of a descriptor variable. By the use of linear free energy scaling relationships, the value of this descriptor is employed to estimate the relative energies of other catalytic cycle intermediates/transition states. Postprocessing of these relationships leads to a volcano curve that reveals the anticipated performance of each catalyst, with the best species appearing on or near the peak or plateau. While the origin of volcanoes is undoubtedly rooted in examining heterogeneously catalyzed reactions, only recently has this concept been transferred to the realm of homogeneous catalysis. This Account summarizes the work done by our group in implementing and refining "molecular volcano plots" for use in analyzing and predicting the behavior of homogeneous catalysts.We begin by taking the reader through the initial proof-of-principle study that transferred the model from heterogeneous to homogeneous catalysis by examining thermodynamic aspects of a Suzuki-Miyaura cross-coupling reaction. By establishing linear free energy scaling relationships and reproducing the volcano shape, we definitively showed that volcano plots are also valid for homogeneous systems. On the basis of this key finding, we further illustrate how unified pictures of C-C cross-coupling thermodynamics were created using three-dimensional molecular volcanoes.The second section highlights an important transformation from "thermodynamic" to "kinetic" volcanoes by using the descriptor variable to directly estimate transition state barriers. Taking this idea further, we demonstrate how volcanoes can be used to directly predict an experimental observable, the turnover frequency. Discussion is also provided on how different flavors of molecular volcanoes can be used to analyze aspects of homogeneous catalysis of interest to experimentalists, such as determining the product selectivity and probing the substrate scope.The third section focuses on incorporating machine learning approaches into molecular volcanoes and invoking big-data-type approaches in the analysis of catalytic behavior. Specifically, we illustrate how machine learning can be used to predict the value of the descriptor variable, which facilitates nearly instantaneous screening of thousands of catalysts. With the large amount of data created from the machine learning/volcano plot tandem, we show how the resulting database can be mined to garner an enhanced understanding of catalytic processes. Emphasis is also placed on the latest generation of augmented volcano plots, which differ fundamentally from earlier volcanoes by elimination of the use of linear free energy scaling relationships and by assessment of the similarity of the complete catalytic cycle energy profile to that for an ideal reference species that is used to discriminate catalytic performance.We conclude by examining a handful of applications of molecular volcano plots to interesting problems in homogeneous catalysis and offering thoughts on the future prospects and uses of this new set of tools.

First-principles-informed energy span and microkinetic analysis of ethanol catalytic conversion to 1,3-butadiene on MgO

First-principles-informed models elucidate the impact of energetic and kinetic limitations on selectivity and activity of ethanol conversion to 1,3-butadiene.

On the optimum catalyst for structure sensitive heterogeneous catalytic reactions

Reaction rates in a two-step catalytic sequence, when plotted vs adsorption energy of the key or the most abundant surface intermediate, result in volcano shaped curves. In the current work, the optimal catalyst is discussed for structure sensitive reactions, which display dependence of activity on the cluster size of the active catalytic phase. An expression is derived relating the Gibbs energy for formation of the intermediate with the Gibbs energy changes in the overall reaction, difference in adsorption thermodynamics on edges and terraces and the cluster size. The kinetic expressions display dependence of activity vs the Gibbs energy of the adsorbed intermediate formation. Numerical analysis demonstrates that when the overall equilibrium constant K is high and the reaction is thermodynamically very favorable, the maxima in the rates vs the adsorption constant for the optimal catalyst are much broader being less dependent on the cluster size. When structure sensitivity is pronounced, there are smaller differences in the rates for the optimum and less optimal catalysts in comparison with reactions showing weak structure sensitivity.

Palladium-Catalyzed Synthesis of α-Carbonyl-α'-(hetero)aryl Sulfoxonium Ylides: Scope and Insight into the Mechanism

Despite recent advances, a general method for the synthesis of α-carbonyl-α'-(hetero)aryl sulfoxonium ylides is needed to benefit more greatly from the potential safety advantages offered by these compounds over the parent diazo compounds. Herein, we report the palladium-catalyzed cross-coupling of aryl bromides and triflates with α-carbonyl sulfoxonium ylides. We also report the use of this method for the modification of an active pharmaceutical ingredient and for the synthesis of a key precursor of antagonists of the neurokinin-1 receptor. In addition, the mechanism of the reaction was inferred from several observations. Thus, the oxidative addition complex [(XPhos)PhPdBr] and its dimer were observed by ³¹P{¹H} NMR, and these complexes were shown to be catalytically and kinetically competent. Moreover, a complex resulting from the transmetalation of [(XPhos)ArPdBr] (Ar = p-CF₃-C₆H₄) with a model sulfoxonium ylide was observed by mass spectrometry. Finally, the partial rate law suggests that the transmetalation and the subsequent deprotonation are rate-determining in the catalytic cycle.

Scaling relationships and volcano plots of homogeneous transition metal catalysis

This Frontier article highlights the recent applications of linear scaling relationships and volcano plots in homogeneous transition metal catalysis.