Comparison of Bulk- vs Layer-by-Layer-Cured Stimuli-Responsive PNIPAM–Alginate Hydrogel Dynamic Viscoelastic Property Response via Embedded Sensors
Yang Liu, Keturah Bethel, Manjot Singh, Junru Zhang, Rana Ashkar, Eric M. Davis, Blake N. Johnson*
Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, Virginia 24061, United States
Macromolecules Innovation Institute, Virginia Tech, Blacksburg, Virginia 24061, United States
Department of Chemical and Biomolecular Engineering, Clemson University, Clemson, South Carolina 29634, United States
Department of Physics and Center for Soft Matter and Biological Physics, Virginia Tech, Blacksburg, Virginia 24061, United States
Department of Materials Science and Engineering, Virginia Tech, Blacksburg, Virginia 24061, United States
While stimuli-responsive hydrogels are now being widely investigated, such as for additive manufacturing applications, it remains a challenge to continuously monitor the dynamic response of their material properties to stimuli using traditional characterization methods. Here, we report that dynamic-mode piezoelectric milli-cantilever sensors enable real-time monitoring of the viscoelastic response of bulk- and layer-by-layer (LBL)-cured composite poly(N-isopropylacrylamide) (PNIPAM)–alginate hydrogel constructs to thermal changes across the 25–37 °C temperature range. Scanning electron microscopy and sensing studies revealed that the network structure and viscoelastic response of ionic–covalent entanglement composite PNIPAM–alginate hydrogel constructs are dependent on the hydrogel processing method. Composite PNIPAM–alginate constructs fabricated using LBL curing exhibited relatively increased responsiveness compared to bulk-cured constructs in terms of the magnitude of thermal stimulus-driven shear storage modulus change, suggesting opportunities for additive manufacturing applications. In summary, we show that sensors, in combination with traditional characterization methods, enable the study of dynamic process–structure–rheological property relations of stimuli-responsive soft materials and real-time monitoring of material rheological properties using a low-sample volume measurement format.