Abstract

The diagnosis and treatment of patients suffering from neurological diseases with patient-individualized silicone rubber-based implants is one of the most promising and challenging approaches to improve treatment outcome. Therefore, medical additive manufacturing techniques are developed for fabrication of such implants, but currently do not achieve the required printing resolution. This is caused by intensive droplet spreading of the initially liquid silicone rubber on the printing substrate. While empirical optimization approaches for the droplet spreading are intensive in cost and time, we develop a mathematical optimization approach to calculate the optimal printing parameters for minimal droplet spreading. Since the viscosity profile of thermal curing silicone rubber is the main reason for the droplet spreading, we implemented a rheology model for calculation of the optimal heat curing parameters. A Dual-Arrhenius equation was used to correlate the temperature-time-profile of the curing process with the curing-related viscosity rise and the temperature-related viscosity fall of the liquid silicone rubber. Two commonly used silicone rubbers were characterized with a rheometer at different isothermal and anisothermal curing profiles. High correlation between the calculated and the measured viscosity profiles were observed, giving the ability to optimize the curing process parameters to the rheological behaviour of the used silicone rubber.

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