3D-QSAR study of ansa-metallocene catalytic behavior in ethylene polymerization

Towards designer polyolefins: highly tuneable olefin copolymerisation using a single permethylindenyl post-metallocene catalyst

Using a highly active permethylindenyl-phenoxy (PHENI*) titanium catalyst, high to ultra-high molecular weight ethylene-linear-α-olefin (E/LAO) copolymers are prepared in high yields under mild conditions (2 bar, 30-90 °C). Controllable, efficient, and predictable comonomer enchainment provides access to a continuum of copolymer compositions and a vast range of material properties using a single monomer-agnostic catalyst. Multivariate statistical tools are employed that combine the tuneability of this system with the analytical and predictive power of data-derived models, this enables the targeting of polyolefins with designer properties directly through predictive alteration of reaction conditions.

Design and prediction of high potent ansa-zirconocene catalyst for olefin polymerizations: combined DFT calculations and QSPR approach

Density functional calculations were carried out to predict activities, regio- and stereoselectivity, and to design new ansa-zirconocene catalysts for olefin polymerizations.

Catalytic performance of bis(imino)pyridine Fe/Co complexes toward ethylene polymerization by 2D-/3D-QSPR modeling

The two-dimensional and three-dimensional quantitative structure-property relationship (2D- and 3D-QSPR) approaches are applied to investigate the catalytic performance for a total data set of 55 bis(imino)pryridine iron and cobalt complexes, including the catalytic activity, molecular weight, and melting temperature of the product. The obtained models for the catalytic performance of interest exhibit good results by both 2D- and 3D-QSPR modeling, meanwhile higher predictive and validation powers observed in the 3D type. The modeling results indicate that the bulky substituents on ortho-position of the singular side phenyl ring and positive charge on para-position of the phenyl ring within the ligand are favorable to catalytic activity, while unfavorable to the molecular weight of product. Based on the obtained QSPR models, four new complexes are designed and predicted with good catalytic activity and very high molecular weight, which are in good agreement with our recent experimental report. © 2019 Wiley Periodicals, Inc.

Straightforward Design for Phenoxy-Imine Catalytic Activity in Ethylene Polymerization: Theoretical Prediction

The quantitative structure-activity relationship (QSAR) of 18 Ti-phenoxy-imine (FI-Ti)-based catalysts was investigated to clarify the role of the structural properties of the catalysts in polyethylene polymerization activity. The electronic properties of the FI-Ti catalysts were analyzed based on density functional theory with the M06L/6-31G** and LANL2DZ basis functions. The analysis results of the QSAR equation with a genetic algorithm showed that the polyethylene catalytic activity mainly depended on the highest occupied molecular orbital energy level and the total charge of the substituent group on phenylimine ring. The QSAR models showed good predictive ability (R2) and R2 cross validation (R2cv) values of greater than 0.927. The design concept is “head-hat”, where the hats are the phenoxy-imine substituents, and the heads are the transition metals. Thus, for the newly designed series, the phenoxy-imine substituents still remained, while the Ti metal was replaced by Zr or Ni transition metals, entitled FI-Zr and FI-Ni, respectively. Consequently, their polyethylene polymerization activities were predicted based on the obtained QSAR of the FI-Ti models, and it is noteworthy that the FI-Ni metallocene catalysts tend to increase the polyethylene catalytic activity more than that of FI-Zr complexes. Therefore, the new designs of the FI-Ni series are proposed as candidate catalysts for polyethylene polymerization, with their predicted activities in the range of 35,000–48,000 kg(PE)/mol(Cat.)·MPa·h. This combined density functional theory and QSAR analysis is useful and straightforward for molecular design or catalyst screening, especially in industrial research.

2D-QSPR/DFT studies of aryl-substituted PNP-Cr-based catalyst systems for highly selective ethylene oligomerization

1-Hexene and 1-octene are important comonomers for the synthesis of high performance polyolefins. Recently, various N-substituted Cr-bis(diphenylphosphino)amine (PNP-Cr) catalysts show the potential as excellent candidates for highly selective ethylene trimerization/tetramerization. In this work, a series of aryl-substituted PNP-Cr catalysts were studied by two-dimensional quantitative structure-property relationship (QSPR) method based on density functional theory (DFT) calculations. The heuristic method (HM) and best multi-linear regression (BMLR) were used to establish the best linear regression models to describe the relationship between selectivities and catalyst structures. Both Cr(I) and Cr(II) active site models for ethylene trimerization/tetramerization were considered. It was found that 1) the relativity and stability of the models were increased by using self-defined descriptors based on DFT calculations; 2) Cr(I)/Cr(III) centers were the most plausible active sites for ethylene trimerization, while Cr(II)/Cr(IV) active sites were most possibly responsible for ethylene tetramerization; and 3) the skeleton structures of the PNP-Cr system with good complanation and symmetry were crucial for achieving excellent catalytic selectivity of 1-octene, while the PNP-Cr backbone with a large steric effect on N atom would benefit ethylene trimerization. Six new PNP ligands with high selectivity toward ethylene trimerization/tetramerization were predicted based on descriptor analysis and the best linear regression models providing a good basis for further development of novel catalyst systems with better performance.

Quantitative structure-property relationship modeling of Grätzel solar cell dyes

With fossil fuel reserves on the decline, there is increasing focus on the design and development of low-cost organic photovoltaic devices, in particular, dye-sensitized solar cells (DSSCs). The power conversion efficiency (PCE) of a DSSC is heavily influenced by the chemical structure of the dye. However, as far as we know, no predictive quantitative structure-property relationship models for DSSCs with PCE as one of the response variables have been reported. Thus, we report for the first time the successful application of comparative molecular field analysis (CoMFA) and vibrational frequency-based eigenvalue (EVA) descriptors to model molecular structure-photovoltaic performance relationships for a set of 40 coumarin derivatives. The results show that the models obtained provide statistically robust predictions of important photovoltaic parameters such as PCE, the open-circuit voltage (V(OC)), short-circuit current (J(SC)) and the peak absorption wavelength λ(max). Some of our findings based on the analysis of the models are in accordance with those reported in the literature. These structure-property relationships can be applied to the rational structural design and evaluation of new photovoltaic materials.

A systematic investigation of quaternary ammonium ions as asymmetric phase-transfer catalysts. Application of quantitative structure activity/selectivity relationships

Although the synthetic utility of asymmetric phase-transfer catalysis continues to expand, the number of proven catalyst types and design criteria remains limited. At the origin of this scarcity is a lack in understanding of how catalyst structural features affect the rate and enantioselectivity of phase transfer catalyzed reactions. Described in this paper is the development of quantitative structure-activity relationships (QSAR) and -selectivity relationships (QSSR) for the alkylation of a protected glycine imine with libraries of quaternary ammonium ion catalysts. Catalyst descriptors including ammonium ion accessibility, interfacial adsorption affinity, and partition coefficient were found to correlate meaningfully with catalyst activity. The physical nature of the descriptors was rationalized through differing contributions of the interfacial and extraction mechanisms to the reaction under study. The variation in the observed enantioselectivity was rationalized employing a comparative molecular field analysis (CoMFA) using both the steric and electrostatic fields of the catalysts. A qualitative analysis of the developed model reveals preferred regions for catalyst binding to afford both configurations of the alkylated product.