Expedited Screening of Active and Regioselective Catalysts for the Hydroformylation Reaction

Conspectus For 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 fundame...

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Section: Kinetic Volcano Plotsproof Of Conceptmentioning

confidence: 99%

The Genesis of Molecular Volcano Plots

et al. 2021

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“…In this regard, computational methods are relevant and can be applied to screen through a large ensembles of functionalized TM complexes [17,18] . Recently such approaches have been applied to screen TM complex including pincer complexes for activity, regioselectivity and ligand effects [19–21] …”

Section: Introductionmentioning

confidence: 99%

Metal‐ligand cooperative activation of HX (X=H, Br, OR) bond on Mn based pincer complexes

Krieger

Sinha

Kalikadien

et al. 2021

Zeitschrift anorg allge chemie

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Reversible dissociation of H−X bond (M−L+H−X→M(X)‐L(H); ΔGHX ) is an important step during pre‐activation, catalysis and possible deactivation of acid‐base cooperative pincer based transition metal catalysts (M−L). Herein we carried out a high‐throughput computational investigation of the thermodynamic stability of different adducts in various functionalized Mn(I) based pincer complexes. We used a combination of density functional theory (DFT) and density functional tight binding (DFTB) calculations to analyze ΔGHX of >700 (M(X)‐L(H)) intermediates based on functionalized variants of four pincer type ligand scaffolds derived from PCP, CNC, PNP and SNS ligands. We discovered linear scaling relations between ΔGHX of various species. Strongest correlations were found between species of similar size and chemical nature e. g. ΔGtBuOH correlated best with ΔGiPrOH and worst with ΔGHBr . Such scaling relations can be useful for property based screening of catalysts and selection of (co)solvent/substrate/base for optimized reaction conditions. We also investigated the influence of the ligand backbone and the functionalization of donor and backbone sites in the ligand. Our analysis reveals the crucial role of the second coordination sphere functionalization for the reactivity of the complexes with impact in some cases exceeding that of the variation of the functional groups directly attached to the donor atoms.

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“…One particular tool that can particularly aid in such an understanding of the overall trends in catalytic behavior is molecular volcano plots. Over the past few years, our research group has been developing and utilizing these plots to screen homogeneous catalysts for several important chemical processes [10][11][12][13][14][15][16][17][18]. Molecular volcano plots predict the performance of a catalyst (in terms of turn over frequencies or a particular energetic criterion) based on an easily computed descriptor variable.…”

Section: Introductionmentioning

confidence: 99%

Uncovering the Activity of Alkaline Earth Metal Hydrogenation Catalysis Through Molecular Volcano Plots

et al. 2021

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Recent advances in alkaline earth (Ae) metal hydrogenation catalysis have broadened the spectrum of potential catalysts to include candidates from the main group, providing a sustainable alternative to the commonly used transition metals. Although Ae-amides have already been demonstrated to catalyze hydrogenation of imines and alkenes, a lucid understanding of how different metal/ligand combinations influence the catalytic activity is yet to be established. In this article, we use linear scaling relationships and molecular volcano plots to assess the potential of the Ae metal-based catalysts for the hydrogenation of alkenes. By analyzing combinations of eight metals (mono-, bi-, tri-, and tetravalent) and seven ligands, we delineate the impact of metal-ligand interplay on the hydrogenation activity. Our findings highlight that the catalytic activity is majorly determined by the charge and the size of the metal ions. While bivalent Ae metal cations delicately regulate the binding and the release of the reactants and the products, respectively, providing the right balance for this reaction, ligands play only a minor role in determining their catalytic activity. We show how volcano plots can be utilized for the rapid screening of prospective Ae catalysts to establish a guideline to achieve maximum activity in facilitating the hydrogenation process.

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Expedited Screening of Active and Regioselective Catalysts for the Hydroformylation Reaction

Cited by 23 publications

References 72 publications

The Genesis of Molecular Volcano Plots

The Genesis of Molecular Volcano Plots

Metal‐ligand cooperative activation of HX (X=H, Br, OR) bond on Mn based pincer complexes

Uncovering the Activity of Alkaline Earth Metal Hydrogenation Catalysis Through Molecular Volcano Plots

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