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Development of a Resilience Parameter for 3D-Printable Shape Memory Polymer Blends
Summary
Not relevant to microplastics — this paper develops a resilience parameter metric for evaluating shape memory polymer blends (PLA/SEBS, ABS/SEBS, PLA/TPU) fabricated via fused filament 3D printing for engineering applications.
The goal of this paper was to establish a metric, which we refer to as the resilience parameter, to evaluate the ability of a material to retain tensile strength after damage recovery for shape memory polymer (SMP) systems. In this work, three SMP blends created for the additive manufacturing process of fused filament fabrication (FFF) were characterized. The three polymer systems examined in this study were 50/50 by weight binary blends of the following constituents: (1) polylactic acid (PLA) and maleated styrene-ethylene-butylene-styrene (SEBS-g-MA); (2) acrylonitrile butadiene styrene (ABS) and SEBS-g-MA); and (3) PLA and thermoplastic polyurethane (TPU). The blends were melt compounded and specimens were fabricated by way of FFF and injection molding (IM). The effect of shape memory recovery from varying amounts of initial tensile deformation on the mechanical properties of each blend, in both additively manufactured and injection molded forms, was characterized in terms of the change in tensile strength vs. the amount of deformation the specimens recovered from. The findings of this research indicated a sensitivity to manufacturing method for the PLA/TPU blend, which showed an increase in strength with increasing deformation recovery for the injection molded samples, which indicates this blend had excellent resilience. The ABS/SEBS blend showed no change in strength with the amount of deformation recovery, indicating that this blend had good resilience. The PLA/SEBS showed a decrease in strength with an increasing amount of initial deformation, indicating that this blend had poor resilience. The premise behind the development of this parameter is to promote and aid the notion that increased use of shape memory and self-healing polymers could be a strategy for mitigating plastic waste in the environment.
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