Session: Rising Stars of Mechanical Engineering Celebration & Showcase

Paper Number: 148048

148048 - Toward Ripest Photopolymer Additive Manufacturing (Pam): Cyber-Physical Dual-Wavelength Photoinhibition Aided Pam 

Photopolymer additive manufacturing (PAM) uses light to cure photosensitive materials and is one of the most versatile technologies to fabricate components with higher resolution compared to existing polymer manufacturing technologies. However, the state-of-the-art photopolymer additive manufacturing technologies still suffer an intractable issue of overcuring, which is detrimental to the structural integrity of printed parts. This Faculty Early Career Development (CAREER) grant supports research to elucidate the fundamental science of light propagation, photochemistry reactions, and material mechanics as well as enable effective process dynamics control for establishing a smart dual-wavelength photoinhibition aided PAM process. This new process allows to manipulate cure and curb exposures of the PAM processing so that the part properties - geometrical fidelity and functional integrity can be enhanced. If successful, this project will impact numerous applications including biochips, electrodes, soft robots, metamaterials, and others that demand precision manufacturing of parts with complex shapes and strengthened performance. This project will provide educational activities aimed to train future leaders to pursue manufacturing-related careers and improve the diversity of the STEM workforce by reaching out to historically underrepresented communities.

The overarching goal of this CAREER project is to realize Rapid, Intelligent, Precise, Extensive, Sustainable, and Transformative (RIPEST) PAM. The primary research objective is to establish a novel digital light processing method - DLP_2Curb that capitalizes on photoinhibition induced by a second wavelength light to curb curing parts, via a holistic cyber-physical approach that combines physics-guided surrogate modeling with real-time sensing and control. Thrust 1 elaborates the DLP_2Curb process dynamics and materials behavior through multiple physical regimes, temporal stages, and spatial scales to unravel the causes of overcuring and the curb reaction paths by constructing a digital twin.  Thrust 2 aims to achieve non-contact, full-field operando characterization of PAM in real time. In-process part properties will be measured by deploying in-situ interferometric and ultrasonic monitoring systems along with physical sensor models and data analytics methods.  Thrust 3 develops a real-time control method via deep reinforcement learning of model predictions and in-situ measurements feedback to achieve closed-loop control of part properties. With representative cases such as micropillars and lattices relevant to the above-mentioned applications, this project will demonstrate the potential ability of DLP_2Curb to unlock efficient precision manufacturing of sophisticated parts with exact geometry and exquisite detail that can sustain the structural underpinning to functionalities.

Presenting Author: Xiayun Zhao University of Pittsburgh

Presenting Author Biography: Dr. Xiayun Zhao joined the University of Pittsburgh (Pitt) as an assistant professor in the Department of Mechanical Engineering and Materials Science in August 2018. She received a B.S. from the Department of Precision Instruments in Tsinghua University (Beijing), and M.S. and Ph.D. in Mechanical Engineering from Georgia Institute of Technology (Atlanta). She worked as a full-time instrumentation and control system engineer in Houston for the Oil & Gas industry for a couple of years. Her interdisciplinary background cultivates her research interest in integrating precision engineering and additive manufacturing to realize the vision of advanced manufacturing. Her research lab, the ZIP-AM (ZXY Intelligent Precision – Advanced Manufacturing) Laboratory, aims to lead the important area of “Measurement Science and Control Technologies for Additive Manufacturing”. Zhao received a Faculty Early Career Development (CAREER) award from the National Science Foundation in 2023 for her integrated research and education in cyber-physical additive manufacturing. As a lead PI, Zhao has been working with interdisciplinary collaborators and research teams on several projects related to improving metal 3D printing as well as innovating photopolymerization-based 3D printing. These projects are sponsored by the US Department of Energy, National Science Foundation (CAREER, Future Manufacturing program, and Industry–University Cooperative Research Centers), as well the Manufacturing Pennsylvania Innovation Program. More details about Zhao’s research are available at her lab website: https://www.zipam.pitt.edu/.

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