Prof. Yueh-Ting Shih(Tim),
Department of Materials and Mineral Resources Engineering, National Taipei University of Technology (Taipei Tech)
Speech Title: Accelerating the Development of Glass Materials through Computational Methods
Dr. Yueh-Ting (Tim) Shih is a materials scientist specializing in glass and ceramic materials, with expertise in both experimental and computational approaches. His research integrates machine learning, molecular dynamics simulations, and advanced characterization techniques to develop innovative materials for applications in 5G/6G communications, low-temperature co-fired ceramics (LTCC), and high-strength display panels.
He earned his Ph.D. in Materials Science and Engineering from National Tsing Hua University in 2019, focusing on the structure-property relationships of lithium-calcium borosilicate glasses. His research examined how different compositions influence mechanical, electrical, and thermal properties using advanced analytical methods. He also contributed to the development of low-loss dielectric ceramics for copper electrode LTCC.
Following his Ph.D., Dr. Shih conducted postdoctoral research at Rensselaer Polytechnic Institute (RPI) in the United States, where he worked on molecular dynamics simulations and machine learning models to predict glass properties. He collaborated with research teams using Brillouin and Raman spectroscopy to study stress distribution and elasticity in glass and polymers.
Since joining the faculty at National Taipei University of Technology in 2022, Dr. Shih has continued his research on glass and glass-ceramic materials for next-generation telecommunications and electronics. His work includes developing deep learning models for microstructure-dielectric property predictions, creating interpretable machine learning frameworks for glass dielectric properties under varying conditions, and enhancing the strength of glasses through crystallization and ion-exchange processes. He also investigates the thermal conductivity and structural properties of glass substrates for integrated circuit (IC) packaging.
Dr. Shih’s contributions to materials science have earned him multiple accolades, including Outstanding Paper Awards from the Taiwan Ceramic Society and the Taiwan Materials Research Society. He has also secured significant research funding from the National Science and Technology Council (NSTC) for projects applying deep learning and machine learning to material informatics.
As an active member of the scientific community, Dr. Shih serves as a technical reviewer for leading journals such as the Journal of the American Ceramic Society and the Journal of Non-Crystalline Solids. He also holds leadership positions as Vice Secretary of the Taiwan Ceramic Society and Chief Editor of its bulletin. His interdisciplinary expertise continues to advance glass and ceramic materials research, bridging computational modeling with practical engineering applications.
Glass materials are indispensable in applications ranging from traditional uses to high-tech industries, yet their development remains challenging due to their disordered atomic structures. Recent advances in computational materials science, particularly molecular dynamics (MD) simulations, and machine learning (ML) models have significantly accelerated the understanding and design of glass materials.
This talk will explore how computational approaches, including MD simulations and ML techniques, are utilized to analyze the composition-structure-property relationships of multi-component oxide glasses under various thermodynamic conditions. MD simulations provide atomic-scale insights into glass structures, enabling the design of glasses with enhanced mechanical strength. Meanwhile, ML models offer accurate predictions of oxide glasses’ dielectric properties across different temperatures and frequencies, overcoming the limitations of traditional empirical models. By integrating physics-based simulations with data-driven methodologies, this work establishes a robust framework for optimizing glass materials for next-generation telecommunications, microelectronics, and structural applications.
Deputy General Manager. Tomita Hiroo,
International Business Dept., Ohkawara Kakohi Co., Ltd.
Speech Title: Spray Dryer in Advanced Ceramic Powder Manufacturing Process
日本中央大學理工學部工業化學科畢業
經歷：Ohkawarra Kakohki Co., Ltd. 1992-Present
Tomita-san has been worked in the Development Dept., Test Planning, and International Business Dept.
Prof. Wen-Jea. J. Tseng
Distinguished Professor in the Materials Science and Engineering Department of the National Chung Hsing University
Speech Title: Semiconducting Ceramic Nanohybrids for Enhanced Gas-Sensing Applications
Dr. Wenjea J. Tseng is a Distinguished Professor in the Materials Science and Engineering Department of the National Chung Hsing University. He graduated with a diploma in Metallurgy from the National Taipei Institute of Technology, Taiwan, and his M.S. and Ph.D. degrees in Materials Science from the University of Rochester, New York, U.S.A. His research interests include colloidal processing of fine particles, chemical synthesis of functionalized nanostructures, organic-inorganic hybrids, photocatalysis, electrocatalysis, and gas sensing. He has published more than 100 journal papers and holds over 10 patents. He served as a council member and committee commissioner for the Taiwan Ceramic Society.
Gas sensors based on semiconducting ceramics have gained significant attention due to their high sensitivity, stability, and versatility in detecting various gases across different environmental conditions. This keynote presentation will explore recent advancements in semiconducting ceramic nanohybrids, emphasizing their structural and compositional tuning for improved gas-sensing performance. We will discuss a diverse range of semiconducting oxides and sulfides, including In₂O₃, ZnO, SnO₂, NiO-decorated In₂O₃, CuO-decorated V₂O₅, Cu-doped α-Fe₂O₃, and ZnS, synthesized in different morphologies such as nanoparticles and nanofibers. The impact of crystallinity, facet engineering, and hybridization strategies on gas detection capabilities in both dry and humid environments will be highlighted. Furthermore, we will present sensing performance for various target gases, including NO₂, H₂S, CO, and ethanol, and address key challenges such as selectivity, response time, and long-term stability in practical applications. This presentation aims to provide insights into novel material design strategies that enhance gas-sensing efficiency and pave the way for next-generation mobile sensor technologies in real-world applications.