Publications by authors named "Kangshu Li"
Article Synopsis
- Defect engineering enhances the functionality of materials, but traditional defect analysis methods suffer from issues like random noise and human bias.
- The study introduces a new approach using CycleGAN and U-Nets to analyze a single STEM image for defect detection, reducing the need for extensive labeled training data.
- This method successfully visualizes atomic defects and oxygen dopants in monolayer MoS, and can be applied to other two-dimensional materials, showing potential for advancing deep learning applications in materials science.
Chiral materials possess broken inversion and mirror symmetry and show great potential in the application of next-generation optic, electronic, and spintronic devices. Two-dimensional (2D) chiral crystals have planar chirality, which is nonsuperimposable on their 2D enantiomers by any rotation about the axis perpendicular to the substrate. The degree of freedom to construct vertical stacking of 2D monolayer enantiomers offers the possibility of chiral manipulation for designed properties by creating multilayers with either a racemic or enantiomerically pure stacking order.
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