Stimuli-Responsive Material-Based Fabrication of Soft Material Actuators and a Cell Sorting Device

Abstract

Stimuli-responsive materials, known for their ability to change properties in response to environmental variations, hold tremendous potential. The responsive nature of these materials necessitates a high level of control during manufacturing and utilization processes. The aim of this thesis is to effectively leverage stimulus- responsive materials through the integration of technologies from various fields to fabricate novel soft actuators and a cell sorter. In the first part of the thesis, soft actuators were fabricated using a 3D printing technology based on jammed microgel-based inks. Bulk hydrogels were synthesized by a standard UV photopolymerization, fragmented using a blender to produce microgels, and jammed. The jammed microgels exhibited shear-thinning and self- healing properties that are essential for extrusion-based 3D printing. Three different types of the microgels were fabricated: non-responsive poly(acrylamide) (PAAm), temperature-responsive poly(N-isopropyllacrylamide) (PNIPAm), and pH-responsive poly(acrylic acid) (PAA) microgels. Using these jammed microgel-based inks, composite hydrogels made of different materials were fabricated by extrusion-based 3D printing and subsequent UV crosslinking. The composite hydrogels exhibited temperature- and pH-responsive behaviors. The 3D printing processes were fine tuned to generate various structures ranging from simple chain shapes to complex dumbbell and gripper forms. Finally, 3D soft actuators were fabricated by printing various stimuli-responsive jammed hydrogels. In the second part of the thesis, a cell sorter that allow separation of specific cell types by selectively detaching them was developed by using a light-responsive polymer. A cell-friendly photoresist, poly(2,2-dimethoxy nitrobenzyl methacrylate- r-methyl methacrylate-r-poly(ethylene glycol) methacrylate) (PDMP) was spincoated on glass substrates. PDMP thin films immersed in cell culture media spontaneously dissolved upon light illumination, thus induce detachment of cells adhering on the films. A microscope integrated with a digital micromirror device (DMD) was setup to illuminate light on determined regions of the PDMP films so that cells on those regions could be selectively detached. Various cells found in tumor tissues such as cancer cells, fibroblasts, and macrophages were adhered on the plasma-treated PDMP thin films, and differential interference contrast (DIC) images of each cell type were collected. Using these images, a deep learning model segmenting and classifying three different cell types were developed. By combining the DMD-integrated microscope and deep learning, a specific type of cells was isolated from the cell mixtures attached on the PDMP films. First, DIC images of the cells were acquired, and each cell attached on the PDMP thin film was segmented and classified using the deep learning model. Then, the classification and segmented area information was transferred to the computer controlling DMD to determine the areas for light illumination. Finally, by illuminating spatially modulated light using the DMD, target cells were selectively detached from the substrates by dissolving the PDMP thin films underlying the cells. A motorized stage would allow a large area image acquisition and subsequent detachment. In sum, this research not only demonstrates the practical utility of stimulus- responsive materials in state-of-the-art technological applications but also paves the way for future breakthroughs in material science, soft robotics, and biomedical devices. The experiments conducted reveal the effectiveness of an interdisciplinary approach, combining material science, mechanical engineering, and cellular biology to address complex challenges, thereby laying a robust foundation for ongoing research and development in these dynamic fields.