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Trends in Metallophilic Bonding in Pd-Zn and Pd-Cu Complexes

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Trends in Metallophilic Bonding in Pd-Zn and Pd-Cu Complexes Research Collection Journal Article Trends in Metallophilic Bonding in Pd-Zn and Pd-Cu Complexes Author(s): Paenurk, Eno; Gershoni-Poranne, Renana; Chen, Peter Publication Date: 2017-12-26 Permanent Link: https://doi.org/10.3929/ethz-b-000234635 Originally published in: Organometallics 36(24), http://doi.org/10.1021/acs.organomet.7b00748 Rights / License: In Copyright - Non-Commercial Use Permitted This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library Trends in Metallophilic Bonding in Pd- Zn and Pd-Cu Complexes Eno Paenurk, Renana Gershoni-Poranne, and Peter Chen* Laboratorium für Organische Chemie, ETH Zürich, Vladimir-Prelog-Weg 2, CH-8093 Zürich, Switzerland Abstract Metallophilic interactions stabilize the bond between closed-shell metal centers, which electrostatically repel one another. Since its introduction, the origin of this interaction has been argued to be either London dispersion forces or dative bonding, but as yet there is no definitive answer. Insight into the nature of metallophilic bonding would provide the key for rational tuning of the stabilizing interaction, for example, in specific transmetalation transition states. We now report on a computational study focused on the metallophilic d8-d10 bond in recently published families of Pd(II)-Cu(I) and Pd(II)-Zn(II) heterobimetallic compexes. We show that dative bonding outweighs dispersion interaction in controlling the metallophilic bonding energy in the studied heterobimetallic complexes, and elucidate the governing orbital interactions. 1. Introduction The term “metallophilic attraction” was suggested in 1994 by Pyykkö to describe the counterintuitive attraction between two closed-shell cationic metals, which otherwise would be expected to repel each other.1 The nomenclature for this type of interaction specifies the last filled subshell of the interacting metals, for example: d10-d10, d10-d8, d8-d8, d8-s2, d10-s2 or s2-s2 (where d8 is an extension of the closed-shell definition, which applies when crystal-field splitting is large).2 The earliest clear example of such bonding was reported in 1964 in a Co(I)-Hg(II) complex, which contains a d8-d10 bond,3 using the conventional nomenclature. The nature of this type of bond – whether it is mainly a dative bond or a dispersion interaction – has been disputed for some time. Nowell and Russell, who reported on the Co(I)-Hg(II) complex, 1 suggested that the compound is a Lewis acid-base complex.3 This Lewis acid-base description of the metallophilic bonds gained general popularity and these types of complexes are now often referred to as Metal-Only Lewis Pairs. Moret has reviewed this type of bonding for specific cases in which Pd(II) and Pt(II) are the d8 components,4 and presents the respective square-planar complexes as two-electron donors, with the dz2 orbital available to form dative bonds to Lewis- acidic metals. Dewhurst and coworkers have recently published a broader review on Metal-Only Lewis Pairs and point out that discerning different types of bonding between transition metals is not easy, because the overall bonding interaction may comprise several components, such as ionic, covalent, dative, and closed-shell interactions.5 An alternative description of the metallophilic bonding was proposed by Pyykkö, who, based on his studies on aurophilicity (attraction between Au cations), ascribed the attraction to a dispersion effect, i.e. an effect stemming from the correlated motion of electrons.1,6 In addition to its fundamental value in chemical bonding theory, more detailed knowledge regarding the nature of metallophilic interaction has potential applicability in several fields of chemistry, e.g. supramolecular design7 or catalysis. A relevant example was recently reported by Espinet, with regard to metallophilic interaction in heterobimetallic complexes and transition- metal catalyzed cross-coupling catalysis. In a series of studies on the Pd-catalyzed Negishi cross- coupling, Espinet and coworkers proposed that the bonding interaction between an electron-rich Pd(II) and positively-charged Zn(II) in the transmetalation transition state (TS) is responsible for lowering the reaction barrier, which leads to reversible transmetalation and undesired homocoupling.8–11 Similarly, the favorable metal-metal interaction between Pd(II) and Cu(I) in the transmetalation TS of the Sonogashira cross-coupling has been used to rationalize the low rearrangement barriers.12 Insight into the nature of the intermetallic attraction would provide the foundation for tuning the interaction energy and, in turn, the transmetalation reaction barriers. This required insight can, in principle, be accessed by quantum mechanical calculations. However, computational investigation of transition-metal compounds is notoriously difficult. Depending on the system, transition-metal compounds can have partially-filled and/or nearly degenerate d orbitals, which lead to significant static electron correlation effects.13 In such cases, the systems are multi-reference in nature, and thus single-reference methods are unlikely to provide correct results, e.g. in transition-metal dimers.14 While Density Functional Theory (DFT) is also a single- reference method, it is nevertheless often the method of choice for computation of transition-metal 2 compounds,13 and has often been employed for studying intermetallic interactions.15 However, due to the paucity of suitable experimental reference data, the accuracy of the results cannot be easily assessed. Herein, we report on a computational study of substituent effects on the d8-d10 bond in recently reported families of Pd(II)-Cu(I)16 and Pd(II)-Zn(II)17 heterobimetallic complexes, from which we derive trends in bond strength. Furthermore, we evaluate and elucidate the different components contributing to the metallophilic bond. 2. Methods 2.1. Computational methods DFT was selected as the method of choice for the quantum chemical calculations performed, due to its low computational cost. The size of the systems studied renders use of more computationally expensive methods, such as configuration interaction or coupled cluster, prohibitive and unfeasible. As mentioned, the drawback of DFT is that the level of accuracy for a specific system is not known a priori, a problem which is especially relevant to calculations with transition metals. Various benchmark studies have been conducted to examine the accuracy of DFT for transition metal chemistry in general18 or for narrower applications, e.g. Cu complexes,19 Ni or Pd catalysis,20 or aurophilic interactions.21,22 These studies provide guidance in selecting the density functional most suitable for a given study, but concern has been raised about the transferability of such benchmark studies to any specific case of interest.23 For this reason, a preceding benchmarking process was undertaken for this work, using a pre-selected set of density functionals. This set of functionals was chosen based on the recommendations of the aforementioned reviews and studies, and we further explored their ability to accurately treat our systems. The results of the benchmarking are discussed in the Supporting Information. The following sections detail only the methods relevant to the main narrative of this report. The notations of the methodology in this work take the general form of (Hamiltonian)-Method- (Additional parameters)/Basis set. The descriptors in brackets are only specified if: a) the Hamiltonian is not the non-relativistic Hamiltonian and/or b) additional parameters are present, such as dispersion correction. If the property described was obtained by complete basis set (CBS) extrapolation, this is specified by replacing the basis set size description by “CBS”, e.g. def2-CBS 3 to denote the extrapolated value from def2-TZVP and def2-QZVPP calculations of the Ahlrichs def2 basis sets.24 2.1.1. Geometry optimizations The ORCA 3.0.3 program25 was employed for geometry optimizations and energy calculations. Geometry optimizations were performed using the meta-GGA functional M06-L26 with the def2- TZVP basis set24 and the Stuttgart effective core potential (ECP) on Pd (ECP28MWB),27 together with Grimme's D3 dispersion correction.28,29 Resolution of Identity (RI) by Coulomb fitting with the general Weigend J auxiliary basis set30 was used to increase the efficiency of the calculations. SCF (self-consistent field) convergence was set to ΔE ≤ 10-8 au and the “tight optimization” setting available in ORCA was employed together with the “Grid5” DFT integration grid. In all cases, numerical frequencies were calculated to confirm real minima (i.e., Nimag = 0) and to obtain the zero-point energy (ZPE) correction. As discussed and justified in the Supporting Information, “Grid6” was selected to resolve the numerical inaccuracies that resulted in several compounds displaying small imaginary frequencies. The general notation of the geometry optimization is M06L-D3/def2-TZVP(ECP). 2.1.2. Single point calculations All energies reported were obtained with single-point calculations performed using the meta- hybrid M06 functional31 together with the D3 dispersion correction on the optimized geometries. The calculations employed the scalar relativistic version of the 2nd order Douglas-Kroll-Hess (DKH2) Hamiltonian32,33 and the respectively recontracted all-electron def2-TZVP-DK and def2- QZVPP-DK basis sets as provided in ORCA 3.34,35 The energy change criterion for SCF convergence was set to 10-6 au and all calculations were performed using Grid5. The Ahlrichs def2 basis sets have been shown to reduce the SCF error when a complete basis set (CBS) extrapolation is performed.36 To perform this extrapolation, properties resulting from triple- ζ and quadruple-ζ calculations are combined by an equation that estimates the value of the property at the complete basis set limit. The extrapolation in this work was done using the following equation: 퐸(푋) 푒−퐵∙푌 − 퐸(푌) 푒−퐵∙푋 퐸∞ = DFT DFT (1) DFT 푒−퐵∙푌 − 푒−퐵∙푋 4 where X = 3 and Y = 4 for the triple/quadruple extrapolation used in this work.
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