(659e) Modeling the Heat-Sealing Process for Multilayer Films Using the Slip-Link Model

Multilayer polymer films are ubiquitous in the packaging industry, with each layer being chemically different and serving different functions. The heat-sealing process is commonly used to seal packages made of these films. The typical heat-sealing operation involves hot bars that bring two multilayer polymer films together and apply pressure and heat to form the seal. Optimization of the resins in each layer and the process conditions for heat-sealing to achieve a hermetic seal is a time-consuming process of trial and error that can be facilitated with the help of an appropriate model. This model must account for the different rheologies of the resins, their sensitivity to the effects of melting, flow and recrystallization during heat-sealing, and changes in process parameters.

In this work, we use the discrete slip-link (DSM) model of Schieber and co-workers to simulate the rheology of crystallizable polyethylene resins in the heat-sealing process. The DSM is a molecular model that is known to capture rheology of broadly polydisperse polymers under non-linear flows. The Rutledge group has extended this model to capture the rheological behavior of crystallizable polyolefins. In combination with equations for heat transfer and crystallization kinetics, the crystallizable DSM model is used to simulate the heat-seal process under various process conditions, and the results are compared with heat-sealing experiments for a multilayer film of industrial LLDPE and HDPE resins. The model predicts relevant quantities of engineering importance like flow volume, layer flow rates and evolution of crystallinity. We find that the trends in these quantities, in particular flow volume, agree well with experimental data for hermeticity. The crystallizable DSM is used to evaluate the response of different resins as layers in the heat-seal process. Differences in the performance of these resins can be attributed to differences in molecular features like molecular weight distributions and comonomer content, which are inputs to the model. The molecular insights enabled by the crystallizable DSM are valuable in designing better resins for the heat-seal process.