http://s.uconn.edu/meseminar4/23/21

Abstract: After billions of years of evolution, it is no surprise that biological materials are treated as an invaluable source of inspiration in the search for new materials. Additionally, developments in computation spurred the fourth paradigm of materials discovery and design using artificial intelligence. Our research aims to advance design and manufacturing processes to create the next generation of high-performance engineering and biological materials by harnessing techniques integrating artificial intelligence, Multiphysics modeling, and multiscale experimental characterization. This work combines computational methods and algorithms to investigate design principles and mechanisms embedded in materials with superior properties, including bioinspired materials. Additionally, we develop and implement deep learning algorithms to detect and resolve problems in current additive manufacturing technologies, allowing for automated quality assessment and the creation of functional and reliable structural materials. These advances will find applications in robotic devices, energy storage technologies, orthopedic implants, among many others. In the future, this algorithmically driven approach will enable materials-by-design of complex architectures, opening up new avenues of research on advanced materials with specific functions and desired properties.

Biographical Sketch: Grace X. Gu is an Assistant Professor of Mechanical Engineering at the University of California, Berkeley. She received her PhD and MS in Mechanical Engineering from the Massachusetts Institute of Technology and her BS in Mechanical Engineering from the University of Michigan, Ann Arbor. Her current research focuses on creating new materials with superior properties for mechanical, biological, and energy applications using multiphysics modeling, artificial intelligence, and high-throughput computing, as well as developing intelligent additive manufacturing technologies to realize complex material designs previously impossible. Gu is the recipient of several awards, including the 3M Non-Tenured Faculty Award, MIT Technology Review 35 Innovators Under 35, Johnson & Johnson Women in STEM2D Scholars Award, Royal Society of Chemistry Materials Horizons Outstanding Paper Prize, and SME Outstanding Young Manufacturing Engineer Award.

http://s.uconn.edu/meseminar4/9/21

Abstract: Soft machines are transforming the fields of robotics and biomedical devices in that they are capable of sustaining large deformation and interacting safely with human beings. Soft active materials can change their shapes or volumes in response to external stimuli, such as light, heat and electric fields, and are important building blocks of soft machines. The recent advance of 3D printing techniques allows manufacturing of soft materials into complex structures. Designing and fabricating soft structures with predictable actuation and programmable functionalities are the major efforts in the field. In this seminar, I will first talk about our recent progress in controlling and modeling spatiotemporal reconfiguration of soft active materials. By spatially patterning photo-responsive liquid crystal elastomers, we have shown morphing of flat sheets into designed three-dimensional geometry. To predict the spatiotemporal responses of photo-responsive hydrogels, we have developed a nonlinear field theory based on the nonequilibrium thermodynamics to capture the coupled reaction-diffusion kinetics. Further accounting the inertia effect, we have predicted and demonstrated self-excited photo-responsive hydrogel oscillators that can autonomously vibrate under constant light irradiation. Tuning the properties of soft materials through sophisticated chemical synthesis is often challenging. To overcome this limitation, I will demonstrate how we are able to vary the responses of soft materials by designing and fabricating them into mechanical metamaterials, which are materials with microarchitectures. Our efforts in designing phase-transforming metamaterials and energy-absorbing metamaterials will be discussed.

Biographical Sketch: Dr. Lihua Jin is an assistant professor in the Department of Mechanical and Aerospace Engineering at the University of California, Los Angeles (UCLA). Before joining UCLA in 2016, she was a postdoctoral scholar at Stanford University. In 2014, she obtained her PhD degree in Engineering Sciences from Harvard University. Prior to that, she earned her Bachelor’s and Master’s degrees from Fudan University in 2006 and 2009. Jin’s group conducts research on mechanics of soft materials, stimuli-responsive materials, instability and fracture, and soft robotics. Lihua was the winner of Haythornthwaite Research Initiative Grant from American Society of Mechanical Engineers in 2016, Extreme Mechanics Letters Young Investigator Award in 2018, Hellman Fellowship in 2019, and UCLA Faculty Career Development Award in 2020.