VR-assisted segmentation of tomography elaborated defects in self-assembled colloidal clusters
In a recent paper published in ACS Nano, researchers from particle technology and theory have worked together with CENEM and it’s research training group members to decrypt the free energy landscape of colloidal clusters in sphere confinement, using the model system of polystyrene (PS) particles. This work sheds light to understand the magics of self-assembling systems. Beside the systematic theoretical investigations and predictions, one particular highlight of this study was the successful development and application of a virtual reality (VR)-assisted segmentation of electron tomography method to visualize the internal structure of more than 3000 self-assembled PS particles.
Congratulations to Junwei Wang and all colleagues for your beautiful work!
Well done, tomo boys!
Demonstration of VR-assisted feature tagging in a tomography dataset, during the open day of high-school students’ visit (photo@M.Wu).
For more details:
Free Energy Landscape of Colloidal Clusters in Spherical Confinement
In: Acs Nano (2019)
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