Automated mapping method of crystalline structure and orientation of polycrystalline material with deep learning

An apparatus for two-dimensional mapping of crystal information of a polycrystalline material, the apparatus comprising:

• an image acquisition unit configured to detect a captured image of a sample having the polycrystalline material by scanning an electron beam on the polycrystalline material;
• and
• an image processing unit configured to
• acquire a diffraction pattern acquired by the scanning of the electron beam on the polycrystalline material,
• generate a plurality of clusters by clustering the diffraction pattern acquired based on unsupervised learning,
• acquire the crystal information of the polycrystalline material by distributing and processing the crystal information in a parallel deep convolutional neural network (DCNN) for each of the plurality of generated clusters based on supervised learning, wherein the crystal information includes a crystal symmetry, a crystal tilt and a crystal thickness, each acquired using the parallel DCNN, and
• generate a two-dimensional image in which the acquired crystal information is mapped.