Monte Carlo (MC) methods were applied to the complex kinetic model of butyl acrylate polymerizations. The MC simulator mcPolymer developed in house allows for handling chain‐length‐dependent termination kinetics. The simulations provide detailed information on the microstructure of each individual polymer chain. For example, the number of short chain branches (SCBs) on each polymer chain and the length of the monomer sequence between two short chain branches are captured. It is shown that the maximum of the branching density distribution is shifted to shorter chain lengths with reaction time. Variation of initiator concentration does not lead to significant changes in the sequence length distributions and branching distributions as long as the same monomer conversion is reached.

Block copolymers of 1H,1H,2H,2H‐perfluorodecyl acrylate (AC8) were obtained from ARGET ATRP. To obtain block copolymers of low dispersity the PAC8 block was synthesized in anisole with a CuBr2/PMDETA catalyst in the presence of tin(II) 2‐ethylhexanoate as a reducing agent. The PAC8 block was subsequently used as macroinitiator for copolymerization with butyl and tert‐butyl acrylate carried out in scCO2. To achieve catalyst solubility in CO2 two fluorinated ligands were employed. The formation of block copolymers was confirmed by size exclusion chromatography and DSC. magnified image

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Summary The approach used for fitting kinetic coefficients to experimental polymerization data is of minor importance as long as the simulation of the quantities to be compared is sufficiently fast. Whenever the simulation is slowed down, for example due to transfer to polymer reactions involved, the fit has to be performed using as few iteration steps as possible. In this work, the simulation aims for the relation between branching and radius of gyration, therefore the kinetic simulation is coupled with a random walk approach, enlarging the computational demands further. A Markov Chain fit is used, enabling an optimal usage of the resources.

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