Prof. Jung-Ting TsaiTaiwan
National Taiwan University of Science and Technology
| 2023 to present | | Assistant Professor at National Taiwan University of Science and Technology |
| 2022 - 2023 | | Post doc fellow at Argonne National Lab |
| 2022 - 2023 | | Post doc fellow at Argonne National Lab |
| 2025 | | Young Investigator Award at the Taiwan Ceramic Society |
| 2024 | | Young Investigator Award at the Taiwan Society for Metal Heat Treatment |
Additively manufactured structural ceramics, cold spray repair and coating technologies, and materials structural monitoring
Dr. Jung-Ting Tsai is an Assistant Professor in the Department of Mechanical Engineering at the National Taiwan University of Science and Technology (NTUST). He served as a postdoctoral researcher in the Applied Materials Division at Argonne National Laboratory until 2023. He received his Ph.D. in Materials Engineering from Purdue University, USA, in 2021.
His research focuses on three main areas: additively manufactured structural ceramics, cold spray repair and coating technologies, and materials structural monitoring. Over the past three years, he has published multiple first-author papers in high-impact journals, including Nano Energy (Impact Factor 16.8), Materials & Design (Impact Factor 9.42), Ceramics International (Impact Factor 5.3), as well as three conference papers. During his time at Argonne National Laboratory, he successfully secured a $200,000 research grant from the U.S. Department of Energy (DOE) focusing on additive manufacturing of structural ceramics.
He was nominated as a Fellow of the Chang Cheng Solid-State Hydrogen Energy Research Center and has also been recognized as an outstanding young scholar in heat treatment and ceramics.
Bridging the Gap in Cold Spray Manufacturing:Quantifying Particle Dynamics and Deposition Probabilities on Polymers
TBA TBA
Surface Modification and Anti-Corrosion/TBA
Cold spray (CS) particle deposition on polymer substrates offers a high-throughput method for functional metallization. Yet, the cost-intensive, trial-and-error nature of the experimental process often limits its use. This research addresses this gap by integrating powder flowability characterization, cost-effective diagnostic tools, and high-fidelity numerical modeling. Powder flowability and mass flow rates were quantified for various metallic and ceramic particles, revealing that spherical morphology and higher density significantly enhance flow consistency. To accurately capture impact dynamics, a double-disk rotary system was developed to measure in-situ particle velocities, providing critical inputs for modeling. A predictive framework utilizing the three-network polymer model (TNM) was implemented in finite element analysis to capture the nonlinear, high-strain-rate response of polymer deformation. Validated by experimental results, a derived kinetic energy fraction (η) serves as a predictive tool, establishing a dimensional window for successful particle embedding. This comprehensive approach enables CS metallization optimization while minimizing experimental overhead.