On the determination of the ratios of the propagation rate constants on the basis of the MWD of copolymer chains: A new Monte Carlo algorithm

In this article we provide a brief summary of computational techniques applied to investigate polymerization reactions in general, with a focus on systems under confinement and initiated from surfaces. We concentrate on two major classes of techniques, i.e., stochastic methods and molecular modeling. We describe the major principles of the two classes of methodologies and point out their strengths and weaknesses. We review a variety of studies from the literature and conclude with an outlook of these two classes of computer simulation approaches as they are applied to “grafting from” polymerizations.

Section: Computer Simulation Approaches For Polymerization In Bulkmentioning

confidence: 99%

Progress in Computer Simulation of Bulk, Confined, and Surface‐initiated Polymerizations

Bain

Turgman‐Cohen

Genzer

2012

“…In 1998, Szymanski applied another Monte Carlo algorithm for modeling chain transfer in living polymerization, which was later extended to radical copolymerization. [3,4] In SSA, each step of simulation consists of three stages: first a reaction m is selected randomly from a set of n possible reactions with probability proportional to their stochastic reaction rate R i using a random number 0 < r 1 < 1, as described by Equation (1):…”

Section: Introductionmentioning

confidence: 99%

“…[9] Versions with random selection of reacting chain from a population are not consistent with Gillespie's idea and, as shown by Szymanski, could lead to erroneous results. [4] Proper modeling of some details of polymerization needs simulations with a large population of chains, thus SSA is perceived as a time-consuming method. [9,10] In the Szymanski algorithm, chains are selected sequentially and subject to reaction within an arbitrary chosen time interval DT, within which the concentration of reagents are assumed to be approximately constant.…”

Section: Introductionmentioning

confidence: 99%

“…When the sum of Dt for the given chain exceeds DT then the concentrations of reagents are corrected accordingly and the next chain selected. [3,4] The Szymanski algorithm scales linearly with n, but the value of n is reduced to a very small number. In 1998, Morton-Firth developed a new algorithm for stochastic simulation of chemical reactions in living cells (StochSim).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Implementation of a Modified Morton‐Firth Algorithm for the Simulation of Polymerization Processes

Sosnowski

2010

The first implementation of the Morton‐Firth algorithm for the simulation of living/controlled polymerization processes is presented. Modifications were introduced to the native algorithm, improving its simplicity. The validity of the new algorithm was confirmed by comparison of results with analytical solutions or numerical integrations of appropriate differential equations. The kinetics of polymerization, molecular weights, and molecular weight distributions were precisely reproduced. The efficiency of the proposed algorithm is close to the stochastic simulation algorithm developed by Gillespie.

“…Theory Simul. 2018, 27,1700106 Scheme 1. Ethylene/1octene chain shuttling polymerization leading to olefinic block copolymers (OBCs).…”

mentioning

confidence: 99%

Intelligent Monte Carlo: A New Paradigm for Inverse Polymerization Engineering

Mohammadi¹,

Saeb

Penlidis

et al. 2018

Traditional computational methods simulate the microstructure of polymer chains from input reaction conditions, but a need exists for predicting optimum reaction conditions in a computationally demanding multivariable space leading to the synthesis of predesigned microstructures and architectures. Herein, the intelligent Monte Carlo (IMC) approach, able to predict optimum reaction conditions for synthesizing copolymers with predefined, complex microstructures as input is introduced. This is rendered possible by a combination of kinetic Monte Carlo (KMC) simulation with artificial intelligence concepts, which enables a reasonably enhanced convergence to optimum reactions conditions. Chain shuttling polymerization is chosen as a first test case due to its complexity and the intricate multiblock microstructures that are formed; whose tailoring requires multiple parameters. The IMC approach locates optimum reaction conditions for the synthesis of olefinic multiblock copolymers with specific microstructures. This approach provides a new platform for identifying complex reaction conditions to “produce” and “tailor‐make” materials with precisely predefined microstructures and facilitates the development of meaningful structure‐property relationships.