Akira Otsuki, Speaker at Climate Change Congress
Universidad Adolfo Ibanez, Chile
Title : Non-destructive characterization and selective material recovery for sustainable resource utilization

Abstract:

Within the context of non-destructive characterization and selective material recovery for sustainable resource utilization, big picture including global trend and targets will be first summarized. Then, challenges associated with selective recovery of complex materials for their sustainable utilization will be discussed in three main areas. They are: characterization, selective liberation/dispersion, and selective separation. Not only the importance of each area but also the synergistic combination of three of them will be highlighted. This talk will help the audience select and design appropriate comminution/liberation and separation methods and evaluate liberation and separation results, leading to minimize the carbon footprint and sustainable resource utilization.

Biography:

Dr. Otsuki received his PhD in Geosystem Engineering from The University of Tokyo (JP) in 2007. After postdocs, a lecturer and an associate professor in Japan, Australia and France, he is currently working as a professor in Universidad Adolfo Ibáñez in Chile. Dr. Otsuki also works as a guest professor in non-destructive characterization and selective material recovery at Lulea University of Technology (SE), and a visiting researcher in Neutron Beam Technology Team at RIKEN (JP). He is a member of several academic societies, including Int. Waste Working Group. He has been acting as journal editors and also organizing journal special issues relevant to non-destructive characterization/testing and selective material recovery, including the ones given below. Dr. Otsuki’s research is specialized in the area of characterization and processing of complex materials which include colloids, waste materials, and natural ores. He has extensive exchange programs with different research and academic institutions around the world and is performing world class collaborative research in characterization and processing.

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