Abstract
In recent decades, quantum chemical calculations (QCC) have increased in accuracy, not only providing the ranking of chemical reactivities and energy barriers (e.g., for optimal selectivities) but also delivering more reliable equilibrium and (intrinsic/chemical) rate coefficients. This increased reliability of kinetic parameters is relevant to support the predictive character of kinetic modeling studies that are addressing actual concentration changes during chemical processes, taking into account competitive reactions and mixing heterogeneities. In the present contribution, guidelines are formulated on how to bridge the fields of computational chemistry and chemical kinetics. It is explained how condensed phase systems can be described based on conventional gas phase computational chemistry calculations. Case studies are included on polymerization kinetics, considering free and controlled radical polymerization, ionic polymerization, and polymer degradation. It is also illustrated how QCC can be directly linked to material properties.
Highlights
Polymers are typically produced in large-scale industrial reactors, yielding (i) low-cost bulk commodity materials for e.g., household goods, including packaging, construction materials, and heat insulation, as well as (ii) high-added value polymers, which are typically fine chemicals and pharmaceuticals for high-tech niche applications e.g., biomedical devices, medicines, and electronics [1,2,3,4,5,6,7,8,9,10,11]
The efficiency of molecular dynamics (MD) simulations of large solute–solvent systems can be greatly improved with a “multiscale” approach in which the solvent molecules in the first solvation shell are obtained using a quantum mechanical (QM) description, while the long-range effects are approximated by implicit solvation [135]
The influence of the solvent was accounted for via an Evans–Polanyi–Semenov correction upon linking the calculated enthalpies with the experimental activation energies. Another example of the application of quantum chemical calculations (QCC) is the study of the self-initiation process performed by Srinivasan et al [185,186,187], who developed the methodology for the theoretical investigation of 2-2, 2 -4, and 4-4 cycloaddition reactions of monomers that are involved in the self-initiation mechanism
Summary
Polymers are typically produced in large-scale industrial reactors, yielding (i) low-cost bulk commodity materials for e.g., household goods, including packaging, construction materials, and heat insulation, as well as (ii) high-added value polymers, which are typically fine chemicals and pharmaceuticals for high-tech niche applications e.g., biomedical devices, medicines, and electronics [1,2,3,4,5,6,7,8,9,10,11]. Specific focus is on QCC for (molecular scale) rate coefficients and the additional conceptual treatments needed to address polymerization reactions, aiming at a reader that is less familiar with GCC but is active in the field of polymer (reaction) engineering or chemistry. It is explained how the QCC-based rate coefficients need to be combined with actual polymerization kinetic models that are dealing with larger length scales. This is further exemplified by including four case studies from the field of polymerization kinetics and one in a broader frame of material property prediction
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