The development of novel pressure sensitive adhesives, formed by the drying of a polymer latex emulsion, is hampered by a lack of understanding of the relation between microscopic details and the large-scale rheology. In a previous paper [Soft Matter, 2011, 7, 5036] we introduced a coarse-grained computer simulation model that aims to provide such a link. To reach sufficiently large time and length scales each latex particle is represented by just six degrees of freedom, and transient forces are introduced to capture the effect of slow changes in the degree of chain intermixing and in the number of sticker groups shared between pairs of latex particles. In this paper we show that this model can nearly quantitatively predict the shear and extensional nonlinear rheology by careful tuning of only a few parameters to the linear rheology. We find a complex transient viscosity with multiple inflection points and maxima under shear flow, as well as a strong strain hardening under extensional flow, all in agreement with experimental observations. We investigate the influence of each of the model's parameters on the linear and nonlinear rheology.@en

For optimal application, pressure-sensitive adhesives must have rheological properties in between those of a viscoplastic solid and those of a viscoelastic liquid. Such adhesives can be produced by emulsion polymerisation, resulting in latex particles which are dispersed in water and contain long-chain acrylic polymers. When the emulsion is dried, the latex particles coalesce and an adhesive film is formed. The rheological properties of the dried samples are believed to be dominated by the interface regions between the original latex particles, but the relationship between rheology and latex particle properties is poorly understood. In this paper we show that it is possible to describe the bulk rheology of a pressure-sensitive adhesive by means of a mesoscale simulation model. To reach experimental time and length scales, each latex particle is represented by just one simulated particle. The model is subjected to oscillatory shear flow and extensional flow. Simple order of magnitude estimates of the model parameters already lead to semi-quantitative agreement with experimental results. We show that inclusion of transient forces in the model, i.e. forces with memory of previous configurations, is essential to correctly predict the linear and nonlinear properties.@en