Single Particle Microscopy
Understanding the atomic structures of colloidal inorganic nanoparticles and their changes over time is of great importance, as it allows us to predict the physical and chemical properties of the nanoparticle. However, owing to the intrinsic heterogeneity among nanoparticles and the practical difficulty of analyzing nanoparticles in their native liquid phase, the static and dynamic structures of colloidal nanoparticles are hardly accessed. To tackle these obstacles, we are developing experimental and computational methods to study the full 3D structures of single nanoparticles in liquid and their transformations over time.
Based on our original method, named 3D SINGLE (3D Structure Identification of Nanoparticles by GLC EM) or Brownian one-particle reconstruction, we study the 3D structures and dynamics of various metal and semiconductor nanoparticles. We also develop computational methods such as neural-network-based image data processing, and computational chemistry for nanoparticles in realistic environment, as complementary methods to overcome finite spatial and temporal resolutions in 3D SINGLE and to understand nanoparticle dynamics in detail.