The emerging of new materials design tools and approaches, such as Materials Genome, machine learning and AI-assisted designs, are bringing new opportunities to materials science and engineering research. These new progresses also call for new experimental methodologies that can quickly verify and complement the computations/modeling. In our recent works, multiple in situ characterization methods were developed and combined with first principles based computations to design and develop new materials for energy storage in a significantly accelerated pace. Some of our recent research projects will be presented. (1) Understanding the formation and phase selectivity of metal and alloy nanoparticles with in situ XRD. (2) Design of phase transition-free cathode for high energy Na-ion batteries. Other ongoing researches such as solid state batteries and Li-ion battery recycling will also be briefly discussed.
Dr. Hailong Chen is currently an Assistant Professor in the Woodruff School of Mechanical Engineering at Georgia Tech. He received his BS degree in Materials Science and Engineering in 1999 and MS degree in Chemistry in 2002, respectively, at Tsinghua University. He earned his PhD degree in Chemistry at the State University of New York-Stony Brook. Before joining the faculty of Georgia Tech in 2013, he conducted postdoctoral research at MIT at the Department of Materials Science and Engineering.
His research interest focuses on understanding the formation mechanism of solid state materials and the structure-property relationship. His research group at Georgia Tech has been working on development of state-of-the-art X-ray based in situ and operando characterization methods, such as synchrotron X-ray based in situ XRD, PDF, SAXS and XAS, and solid state NMR, etc. The ongoing projects include design, synthesis, testing and characterization of new materials for Li-ion, Na-ion and all-solid-state batteries, as well as metals and alloys as functional and structural materials. More information about the group and the publications can be found at the group webpage: https://hlchen.gatech.edu.