The approach was developed by Daniel Packwood of Kyoto University's Institute for Integrated Cell-Material Sciences (iCeMS) and Taro Hitosugi of the Tokyo Institute of Technology. It involves connecting the chemical properties of molecules with the nanostructures that form as a result of their interaction. A machine learning technique generates data that is then used to develop a diagram that categorizes different molecules according to the nano-sized shapes they form. This approach could help materials scientists identify the appropriate molecules to use in order to synthesize target nanomaterials.
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