Modeling of Substitutional Defects in Magnesium Dichloride

Mar 16, 2012 - and Timo Leinonen. ‡. †. University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland. ‡. Borealis Polymers Oy, P.O. Bo...
0 downloads 0 Views 2MB Size
Article pubs.acs.org/JPCC

Modeling of Substitutional Defects in Magnesium Dichloride Polymerization Catalyst Support Andrey Bazhenov,† Mikko Linnolahti,*,† Antti J. Karttunen,† Tapani A. Pakkanen,*,† Peter Denifl,‡ and Timo Leinonen‡ †

University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland Borealis Polymers Oy, P.O. Box 330, FI-06101 Porvoo, Finland



S Supporting Information *

ABSTRACT: We evaluate methods and models for the periodic quantum chemical treatment of defects in MgCl2 polymerization catalyst support and demonstrate the applicability of the approach for a study of chemical substitution of chlorine with bromine. Effects of the defects are evaluated through binding of methanol to catalytically relevant MgCl2 surfaces. Our results show that the hybrid density functional PBE0 method reproduces the MgCl2 crystal structure in good agreement with experiments and that a triple-ζ quality basis set is required to evaluate the donor binding properties. Furthermore, the effects of the defects depend on their position in the crystal lattice, and destabilization of the crystal lattice results in increased donor binding energy. Therefore, substitutions at the coordinatively unsaturated edges typically stabilize the crystallites and lower the donor binding energies, whereas substitutions at the coordinatively saturated bulk typically destabilize the crystallites and increase the donor binding energies. The effects are stronger on the (104) than on the (110) surface. The study is readily extendable to other kinds of defects occurring in crystallites.



INTRODUCTION Magnesium dichloride is one of the key components in the Ziegler−Natta olefin polymerization catalysis. As a catalyst carrier, it forms the catalytically active species via binding other catalyst components, in particular, titanium chlorides and electron-donating compounds.1,2 The understanding of the formation of the active sites remains incomplete, even though the crystalline MgCl2 itself is well-characterized. The MgCl2 bulk exists in several polymorphs, which differ in stacking of the MgCl2 layers (Figure 1a).3 The catalytically active sites have been proposed to be at the edges of the layers toward the [104] and [110] crystallographic directions (Figure 1b).4 However, as any crystalline material, MgCl2 contains defects, which change chemical environment of the surface sites, consequently affecting the binding properties.5 The defects may be even essential for the performance of MgCl2 in Ziegler−Natta catalysts. Electron-donating compounds are typically added to improve the activity of the catalytic system and to gain better control of the product properties, such as stereoregularity and molecular weight distribution.6−8 Still, the mechanism of acting is unclear. It has been recently shown that upon the addition of suitable electron donors, the growth of MgCl2 can be controlled, leading to preferable formation of either (104) or (110) surfaces.9−14 This suggests that the donors may operate through altering the structure of the catalytic system as a whole. © 2012 American Chemical Society

Binding of the donors on the MgCl2 surfaces is difficult to clarify by experimental techniques alone. Parallel to the experiments, computational chemistry has become a widely employed tool to address the problem. The computational studies, dealing with the defect-free MgCl2, have provided useful information on various aspects of the process, such as binding modes of the donors on the surface sites and control of the microstructure of the MgCl2−donor catalyst system.2,13−21 The present Article aims at expanding the previous studies taking the defects into account. We optimize a technique for efficient treatment of MgCl2−donor interactions in the presence of defects and demonstrate its applicability for a model system, where the donor is methanol and the defect is chlorine-to-bromine substitution.



COMPUTATIONAL DETAILS Periodic quantum chemical calculations were employed throughout the study using CRYSTAL0922,23 code. The hybrid density functional PBE024,25 and B3LYP26,27 methods were combined with three basis sets optimized for the periodic treatment of MgCl2. A previously reported basis set was taken from the paper of Barrera et al.,28 namely, 8−5−11G* (Mg) Received: February 24, 2012 Revised: March 15, 2012 Published: March 16, 2012 7957

dx.doi.org/10.1021/jp3018327 | J. Phys. Chem. C 2012, 116, 7957−7961

The Journal of Physical Chemistry C

Article

Figure 2. Unit cells of 1-D surface models employed in the study (Mg in yellow, Cl in green). Five atomic layers are presented.

Figure 1. Structure of the MgCl2: (a) stacking of the layers in different modifications and (b) catalytically relevant crystallographic directions (Mg in yellow, Cl in green). Figure 3. Dependence of the lattice parameter on the model thickness. The black lines represent the corresponding crystallographic data for α- (lower) and β-forms (upper) of the MgCl2.3

and 8−6-311G* (Cl) of Harrison and Saunders29 with further optimized 3sp, 4sp, and 3d functions for Mg and 4sp, 5sp, and 3d functions for Cl, together with added 4d functions for Cl. In conjunction with Barrera’s basis set, the standard 6-31G(d)30 basis set was used for oxygen, carbon, and hydrogen. The two other basis sets were optimized in the work: The split-valence + polarization (SVP) and triple-ζ-valence + polarization (TZVP) basis sets were derived from the molecular def2-SVP31,32 and def-TZVP33 basis sets. (See the Supporting Information for the detailed descriptions of the basis sets.) A shrinking factor (SHRINK) of 4 was used to generate a Monkhorst−Pack type grid of k-points in the reciprocal space. Tightened tolerance factors of 8, 8, 8, 8, and 16 were used for the evaluation of the Coulomb and exchange integrals (TOLINTEG). All structures were fully optimized within the respective symmetry group using default optimization convergence thresholds and extralarge integration grid (XLGRID) for the density functional part. Basis set superposition error (BSSE) was calculated by the counterpoise technique.34

density functional methods and three basis sets. Beyond the thickness of five atomic layers, the change in the lattice parameter becomes