Interaction of common cocatalysts in Ziegler–Natta‐catalyzed olefin polymerization

%VBur index and steric maps: from predictive catalysis to machine learning

Steric indices are parameters used in chemistry to describe the spatial arrangement of atoms or groups of atoms in molecules. They are important in determining the reactivity, stability, and physical properties of chemical compounds. One commonly used steric index is the steric hindrance, which refers to the obstruction or hindrance of movement in a molecule caused by bulky substituents or functional groups. Steric hindrance can affect the reactivity of a molecule by altering the accessibility of its reactive sites and influencing the geometry of its transition states. Notably, the Tolman cone angle and %VBur are prominent among these indices. Actually, steric effects can also be described using the concept of steric bulk, which refers to the space occupied by a molecule or functional group. Steric bulk can affect the solubility, melting point, boiling point, and viscosity of a substance. Even though electronic indices are more widely used, they have certain drawbacks that might shift preferences towards others. They present a higher computational cost, and often, the weight of electronics in correlation with chemical properties, e.g. binding energies, falls short in comparison to %VBur. However, it is worth noting that this may be because the steric index inherently captures part of the electronic content. Overall, steric indices play an important role in understanding the behaviour of chemical compounds and can be used to predict their reactivity, stability, and physical properties. Predictive chemistry is an approach to chemical research that uses computational methods to anticipate the properties and behaviour of these compounds and reactions, facilitating the design of new compounds and reactivities. Within this domain, predictive catalysis specifically targets the prediction of the performance and behaviour of catalysts. Ultimately, the goal is to identify new catalysts with optimal properties, leading to chemical processes that are both more efficient and sustainable. In this framework, %VBur can be a key metric for deepening our understanding of catalysis, emphasizing predictive catalysis and sustainability. Those latter concepts are needed to direct our efforts toward identifying the optimal catalyst for any reaction, minimizing waste, and reducing experimental efforts while maximizing the efficacy of the computational methods.

Chain Walking in the AlCl3 Catalyzed Cationic Polymerization of α-Olefins

Continuing efforts aimed at performing the 1-decene polymerization to low viscosity polyalphaolefins (PAO)s using a less hazardous AlCl₃ catalyst than boron-based analogs, the basic mechanisms of this system were revealed in this research. In this aspect, neat AlCl₃ and AlCl₃ /toluene were carried out to perform 1-decene polymerizations. Microstructure analyses of the as-synthesized oils revealed low molecular weight (708 vs. 1529 g/mol), kinematic viscosity (KV¹⁰⁰ =6.4 vs. 22.2 cSt), and long chain branching (82.1 vs. 84.7) of PAO from the system containing toluene solvent. Furthermore, NMR analysis confirmed various types of short chain branch (SCB) with the inclusion of toluene ring in the structure of final PAO chains. Then, to shed light on the basic mechanisms of cationic polymerization of 1-decene including: i) chain initiation, ii) chain transfer to the monomer, iii) isomerization of the carbocation via a chain walking mechanism (causes different SCB length), and iv) binding of toluene ring to the propagating PAO chain (to yield aromatic containing oligomers), molecular modeling at the DFT level was employed. The energies obtained confirmed the ease of carbocation isomerization and chain transfer mechanisms in toluene medium, which well confirms the highly branched structure experimentally obtained for related PAO.

A Novel Method for Dynamic Molecular Weight Distribution Determination in Organometallic Catalyzed Olefin Polymerizations

In this study, a mathematical model for the time evolution of molecular weight distribution (MWD) was developed. This temporal model is based on the well-known Ziegler–Natta polymerization mechanism and reaction kinetics by the parametric solving of related differential equations. However, due to the generality of the reactions involved, the model can be extended to the other type of catalysts, such as metallocenes, Phillips, etc. The superiority of this model lies in providing the possibility of a more precise prediction over the active sites and kinetic parameters using a simple mathematical equation, which leads to improved reactor design in large-scale production. The model uses a function to develop a methodology for MWD calculations. In this way, the transient response is limited to the first few minutes of the reaction; however, it is important as it demonstrates the establishment of the final MWD. According to the results, almost for practical conditions with negligible transfer resistances, the time dependency of the MWD has a transient interval, depending on the kinetic constants of polymerization reactions. Increasing the time to infinity results in an increase in MW and a widening in MWD, which confirms the experimental plots well. In short, the main advantage of our proposed model over the previous ones is its ability to predict the MWD even before the completion of the polymerization reaction. The results of the present model match well with those of the well-known Schulz–Flory distribution, which only predicts the final molecular weight distribution, thus confirming that the model is reliable and generalizable.

Exploring cocatalyst type effect on the Ziegler–Natta catalyzed ethylene polymerizations: experimental and DFT studies

Due to the important role of cocatalyst in the polymerization process employing industrially favored Ziegler–Natta catalysts, its effect on kinetic behavior, catalyst activity, and polymer properties is discussed. In this paper, triethyl aluminum (TEA) and triisobutyl aluminum (TIBA) have been used as the main cocatalyst ingredient with 10–20 mol percent of diethyl aluminum chloride (DEAC) and ethyl aluminum dichloride (EADC) cocatalysts, being neat TEA the cocatalysts with the highest activity. Moreover, TEA-DEAC and TEA-EADC cocatalysts revealed a built-up kinetic profile, while TIBA-DEAC and TIBA-EADC show a decay-type kinetic curve. According to melt flow index results, no considerable change in flowability was detected in the synthesized polyethylenes (PE). On the other hand, the ethylene insertion and chain termination mechanisms were investigated by means of density functional calculations using Ti active center located in (110) and (104) facets of the MgCl2 surface. To shed light on the bulkiness level of employed cocatalysts, buried volume (VBur) together with the two-dimensional map of cocatalyst systems were considered. Higher VBur of TIBA complex can explain its lower activity and decay type kinetic profile obtained by experimental studies.

The atomic defects on the (104) and (110) surfaces of the MgCl2-supported Ziegler–Natta catalyst: a periodic DFT study

This work presents a DFT study on the effects of atomic defects in the MgCl2-supported Ziegler–Natta catalyst. The adsorption behaviours of TiCl4 and internal donors on the ideal and defective MgCl2(104) and (110) surfaces were investigated.

Fundamental aspects of heterogeneous Ziegler–Natta olefin polymerization catalysis: an experimental and computational overview

Using an internal/external donor containing MgCl₂-supported Ziegler–Natta catalyst is one of the important processes for polyolefin production.