A gradient copolymer has a gradient in the repeat units comprising the backbone of the polymer arranged from predominantly monomer A to predominantly monomer B along the copolymer chain. Because of the gradual change of the composition along the copolymer chains, gradient copolymers exhibit distinct physical properties compared to those of random or block copolymers of the same composition. Furthermore, different sequence distributions along gradient copolymer chains may lead to markedly different physical properties, suggesting that gradient polymers can be tailored for specific applications by tuning the sequence distribution. Thus, it would be valuable to be able to predict the specific sequence distribution of gradient copolymers given different monomer pairs and synthesis conditions.

To address this challenge, we developed kinetic Monte Carlo (KMC) models, which track molecules instead of concentration, in order to track the explicit sequence distribution for each copolymer chain. In addition, KMC models permit the explicit molecular weight distribution (MWD) and chemical composition distribution (CCD) of gradient copolymers to be tracked, which is not possible with moment-based continuum models. We developed these KMC models in the context of the nitroxide-mediated controlled radical polymerization (NM-CRP) of two different monomer systems: styrene/4-acetoxystyrene and methyl methacrylate/t-butyl methacrylate. The simulated MWD and CCD were compared to experimental data from matrix-assisted laser desorption/ionization-time of flight mass spectroscopy (MALDI-TOF-MS). The effects of different synthesis conditions on the MWD, CCD and formation of the compositional gradient along the copolymer chains were studied. Finally, experimental methods for obtaining information about the sequence distribution to compare to the detailed KMC output were explored.