Multicycle Characterization of Surface Roughness in Stereolithography-based Additive Manufacturing Using a Methacrylate-based Thermoresponsive Copolymer

Additive manufacturing of stimuli-responsive materials, that is, 4D printing, has recently drawn attention given its unique ability to fabricate smart structures that can change shape over time when triggered by external stimuli. Despite numerous efforts toward understanding the shape memory characteristics of 4D-printed structures, the comprehensive characterization of their critical quality metrics, such as surface quality, remains limited. Existing surface roughness models primarily focus on describing roughness caused by the layer-wise 3D fabrication process, inadequately capturing the variations in the surface quality due to multiple shape programming and recovery processes, particularly under the influence of external stimuli. This study employs a combined approach of mathematical modeling and experimental characterization to investigate the surface roughness changes of 4D-printed thermoresponsive shape memory structures, considering the impacts of both printing parameters and stimulus conditions across consecutive shape-morphing cycles. The findings indicate that the geometry features and the type of deformation applied on the sample have an essential role in the way the roughness responds to the shape-changing processes, while longer holding times resulted in an association with increased roughness after the first cycle with different fluctuations as the structures underwent repeated exposure. Higher temperatures (20°C over the material’s glass transition temperature) induced less change in roughness with respect to the as-printed structures compared with those programmed using lower temperatures. This study indicates that the stimulus-induced variations in surface quality due to 4D printing can be regulated appropriately using adequate tailoring of the process parameters.