Collaborative Research: Integrated Design Optimization for Multifunctional Hydrogel Synthesis and Additive Manufacturing

Arizona State University, Scottsdale AZ

Investigators

Abstract

Hydrogels have great potential for applications in healthcare, robotics, and more. Additive manufacturing of hydrogel enables building 3D objects with sophisticated structures. However, a key challenge is the lack of cost-efficient methodologies for designing the hydrogel synthesis and printing processes together to achieve desired product performance. This award enables research in creating hydrogels with customized features tailored for distinct applications with lower cost, reducing the cost of additive-manufactured hydrogel products. If successful, the outcomes of this research are expected to shorten the design cycle of new materials and processes and facilitate wide utilization and rapid scale-up to industry. This research aims to develop a unique analytical design framework, consisting of (a) interpretable and efficient uncertainty quantification models that adaptively accommodate the model complexity and (b) a unique decision algorithm for the multistage experiments that simultaneously decides the next experimental operation and the volume of material, in order to make diverse products achieving multiple targeted functionalities. Additionally, the experimental platform, dynamic-fluid-assisted micro-continuous liquid interface printing (DF-μCLIP), offers a dedicated “hardware in the loop” system that synergizes in-situ hydrogel synthesis and printing for implementing the design optimization procedure. The resulting integrated material discovery and manufacturing platform has broad potential impact across material and manufacturing systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.