The Materials Today ‘Rising Star Awards’ recognize researchers in materials science and engineering who have demonstrated themselves to be exceptionally capable researchers with the potential to become future leaders in the field.
Open to candidates within 15 years of completing their PhD who have demonstrated themselves to be leading the way through the impact of the research the candidate has conducted and the contributions the candidate has made to the materials community.
The 2019 Materials Today ‘Rising Star Awards’ were open to nominations in the fields of: Energy Storage Materials, Materials for Sustainability, Quantum, Soft and Intelligent Materials, and Energy Conversion. We are now delighted to announce the winners of this year’s awards:
- Yan Yu (University of Science and Technology of China)
- Shuangyin Wang (Hunan University)
- Yanguang Li (Soochow University)
- Yongji Gong (Beihang University)
The winners were presented during the “Materials Today – The Future of Materials Science” session at ChinaNANO 2019.
For information on the 2018 Award winners, visit https://www.materialstoday.com/rising-stars-2018/
For more information on the winners, please see below.
Yan Yu is a Professor of material science in University of Science and Technology of China (USTC). She received her Ph.D. in material science at USTC in 2006. From 2007 to 2008, she worked as a postdoctoral at Florida International University. After that she received Humboldt Research Fellow from the Alexander von Humboldt Foundation and worked at the Max Planck Institute for Solid State Research in Stuttgart, Germany. Her current research interests mainly include design of novel nanomaterials for clean energy, especially for batteries and the fundamental science of energy storage system.
Yan Yu’s work shows how crucial and beneficial the construction of intelligent electrochemical networks can be.
Shuangyin Wang is a Professor at Hunan University. His work has included work on the defect chemistry of electrocatalysts to study the effect of defects on electronic properties, surface properties, adsorption properties and electrocatalytic activities at the atomic defect level to uncover fundamental issues of surface-interface science of electrocatalysts. This includes uncovering the activity of intrinsic defects of carbon electrocatalysts; controlling the generation of defects in transition metal oxide (TMO) electrocatalystsl; and the surface functionalization of defect sites in electrocatalysts.
Yanguang Li from Soochow University received his BS degree in Chemistry from Fudan University, China in 2005, and obtained his Ph.D. in Chemistry from Ohio State University in 2010 before moving to Stanford University to complete post-doctoral training. During his postdoctoral research, Dr. Li pioneered the development of several important electrocatalyst materials that generated significant interest within the community – including being the first to pursue the nanostructural engineering of MoS2, and achieve the uniform growth of edge-abundant MoS2 nanocrystals on the graphene support. He went on to publsih exceptional work of Co3O4 nanocrystals on graphene nanosheets and the great potential of spinel oxides. He and his collaborators were the first to introduce the now extremely popular Ni-Fe layered double hydroxide (LDH) for oxygen evelotion reaction in neutral and alkaline solutions. And far more besides.
Yongji Gong is currently a professor of Materials Science and Engineering at Beihang University, Beijing, China. Yongji’s research area is mainly focused on the synthesis of 2D materials, their properties and applications. One particularly significant contribution to the community from Prof. Gong is the development of several reliable methods to build up 2D heterostructures. He was the first to develop a growth strategy for the creation of high-quality vertically stacked as well as in-plane interconnected heterostructures of 2D semiconductors, via the control of the growth temperature. His work has opened the gate to building complicated 2D integrated circuits in a scalable way.