CEEM Seminar | Xiang Zhang | University of Wyoming
Toward a Digital Twin for Frontal Polymerization-based Manufacturing: From Multiphysics Modeling to Real-Time Monitoring and Control
Frontal polymerization (FP) is an energy-efficient manufacturing approach in which a localized initiation triggers a self-propagating exothermic reaction front that rapidly cures thermoset polymers and composites. This unique mechanism enables fast curing and free-standing fabrication, but it also creates challenges for process design because the thermal, chemical, and mechanical fields are strongly coupled, process outcomes are sensitive to boundary conditions and operating parameters, and key internal states such as cure degree are difficult to observe directly during manufacturing. In this talk, Zhang will present recent efforts toward a digital twin for FP-based manufacturing, emphasizing the progression from physics-based understanding to real-time process monitoring and control. He will begin with an introduction to FP and early experimental and modeling studies from his postdoctoral work at the University of Illinois Urbana- Champaign, which helped establish the foundation for FP-enabled manufacturing and direct ink writing. Developments at the University of Wyoming will be discussed, including thermo-chemical modeling of layer-by-layer FP printing and thermo-chemo- mechanical modeling of process-induced residual deformation, which together clarify how front behavior, cure evolution, and thermal history influence manufacturing quality. Building on this foundation, Zhang will present recent work on digital-twin-guided closed-loop print-speed control and on real-time cure-state estimation from infrared thermography using cascaded inverse-forward deep learning with uncertainty quantification. Finally, he will highlight emerging manufacturing demonstrations, including lattice structures and lunar regolith-reinforced composites, and outline a path toward digital twins that support real-time monitoring, adaptive control, and ultimately process optimization in FP-based polymer and composite manufacturing.
Xiang Zhang
Dr. Xiang Zhang is an Associate Professor in the Mechanical Engineering Department at the University of Wyoming, leading the Computations for Advanced Materials and Manufacturing Laboratory. He is currently an Adjunct Associate Research Scientist in the Department of Civil Engineering and Engineering Mechanics at Columbia. Zhang’s engineering education started at Northeastern University in Shenyang, China, where he received his bachelor’s degree in Engineering Mechanics. His interest in computational modeling was developed during his master’s study at Beihang University, China. He earned his Ph.D. in Civil Engineering at Vanderbilt University, followed by a postdoctoral research experience in Aerospace Engineering at the University of Illinois at Urbana-Champaign. Zhang’s research interest is computational mechanics, with a particular focus on developing sophisticated multiscale/multiphysics methods in conjunction with machine learning techniques for the modeling, design, and manufacturing of high-performance materials and advanced manufacturing processes. His work has been recognized by multiple awards, including being a Finalist of the 28th Robert J. Melosh Medal Competition for the Best Student Paper on Finite Element Analysis when he was a graduate student, and the American Society of Mechanical Engineers Materials Division ORR Early Career Award and an NSF Early CAREER Award in 2024.