Microstructure engineering in metal additive manufacturing using experimental and computational methods

Guest Speaker：Assistant Professor Xipeng Tan，National University of Singapore, Singapore

Inviter: Prof. Jinfu Li

Date&Time: Wednesday, 8.Jan., 14:00-16:00

Venue: Meeting Room 308 , Xu Zuyao Building

Biography:

Dr. Xipeng Tan is currently a tenure-track Assistant Professor in the Department of Mechanical Engineering, National University of Singapore. He also holds the courtesy joint appointment in the Department of Materials Science and Engineering. He received his BS in metallurgical engineering from Jilin University in 2007, and PhD in materials science from the Institute of Metal Research (Shenyang), Chinese Academy of Sciences in 2013. After his postdoctoral training on atom probe tomography in France, he joined the Nanyang Technology University as a Senior Research Fellow working on metal additive manufacturing. Dr. Tan’s main research interest lies in design and control strategies for high-performance metal additive manufacturing. He has been a lead author for more than 60 peer-reviewed journal papers in metallurgy and additive manufacturing such as Nature Communications, NPG Asia Materials, Acta Materialia, Additive Manufacturing, Journal of Materials Processing Technology, etc., including 7 Highly Cited Papers in terms of Web of Science. His research work has gained over 8000 citations with a H-index of 35 from Google Scholar. He delivered more than 10 invited talks in the international conferences and workshops in the past 5 years. He serves as an editorial board member of Advanced Powder Materials. More personal details see https://cde.nus.edu.sg/me/staff/tan-xipeng/

Abstract:

Metal additive manufacturing (AM), colloquially known as metal 3D printing enables high-precision digital fabrications of complex near-net-shape metallic parts using raw materials mainly in the form of powder or wire. It exhibits immense promise in achieving real-time, in-process yet site-specific microstructural control and engineering during layer-by-layer deposition of a wide variety of metal alloys. In this talk, I will brief AM and microstructure fundamentals, and then share our recent research work of using experimental and machine learning methods to engineer the AM microstructure for exceptional mechanical properties. Our research efforts pave the way towards high-performance metal AM technology by leveraging the classical materials science and emerging computational power.