Journal
ACS APPLIED MATERIALS & INTERFACES
Volume 15, Issue 28, Pages 34097-34107Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acsami.3c07172
Keywords
semicrystalline polymer; 3D printing; shapememory; multimaterial; photopolymerization
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Multimaterial 3D printing allows for the creation of programmable smart plastics with spatially tunable thermomechanical properties and shape-memory behavior, which can be applied in soft robotics and electronics. Digitallight processing 3D printing has shown high precision and resolution, but there is a lack of research on using this method for semicrystalline polymers. By adjusting the ratio of two long-chain acrylates, it is possible to obtain different thermomechanical properties and shape-memory behavior in the printed objects. This approach shows promise for the development of customizable actuators for biomedical applications.
Multimaterial three-dimensional (3D) printing of objectswith spatiallytunable thermomechanical properties and shape-memory behavior providesan attractive approach toward programmable smart plasticswith applications in soft robotics and electronics. To date, digitallight processing 3D printing has emerged as one of the fastest manufacturingmethods that maintains high precision and resolution. Despite thecommon utility of semicrystalline polymers in stimuli-responsive materials,few reports exist whereby such polymers have been produced via digitallight processing (DLP) 3D printing. Herein, two commodity long-alkylchain acrylates (C-18, stearyl and C-12, lauryl)and mixtures therefrom are systematically examined as neat resin componentsfor DLP 3D printing of semicrystalline polymer networks. Tailoringthe stearyl/lauryl acrylate ratio results in a wide breadth of thermomechanicalproperties, including tensile stiffness spanning three orders of magnitudeand temperatures from below room temperature (2 & DEG;C) to abovebody temperature (50 & DEG;C). This breadth is attributed primarilyto changes in the degree of crystallinity. Favorably, the relationshipbetween resin composition and the degree of crystallinity is quadratic,making the thermomechanical properties reproducible and easily programmable.Furthermore, the shape-memory behavior of 3D-printed objects uponthermal cycling is characterized, showing good fatigue resistanceand work output. Finally, multimaterial 3D-printed structures withvertical gradation in composition are demonstrated where concomitantlocalization of thermomechanical properties enables multistage shape-memoryand strain-selective behavior. The present platform represents a promisingroute toward customizable actuators for biomedical applications.
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