Monte Carlo methods are heuristic algorithms that use probabilities to select an outcome
among several possible events in a given process. Monte Carlo methods are useful in …

This introductory textbook covers all aspects of catalysis. It also bridges computational
methods, industrial applications and green chemistry, with over 600 references. The book is …

The molecular weight distribution (MWD) is possibly the most important characteristic of a
polymer. Polymers derive many of their physical properties from their MWD. Therefore, since …

Bulk and solution radical polymerization is important in daily live. A challenge is still to
maximize polymerization rate and control over molecular characteristics such as the molar …

Monte Carlo modeling has emerged as a powerful tool to describe system state variations in
many engineering systems. If distributed species are involved, the so-called Gillespie-based …

Monte Carlo (MC) is a term quite common in the research community but, quite surprisingly,
it may possess a different meaning among researchers in different areas. This paradox is …

Kinetic Monte Carlo (KMC) has become a well-established technique for simulating the
kinetics of free radical polymerization, both to generate polymer molecular weight …

The modeling of the molecular weight distribution of polymers is critical in polymerization
modeling. Moment-based models and kinetic Monte Carlo are two methods used to …

Mean‐square radius of gyration Rg2 and the graph diameter D, which describe the
dimensions of polymers, are investigated for the network polymers. Both for the random and …

A novel stochastic algorithm is described for the accurate prediction of the detailed
molecular topology of highly branched polymer chains. Stochastic topological polymer chain …