Abstract: A method for autonomously applying a dangling bond pattern to a substrate for atom scale device fabrication includes inputting the pattern, initiating a patterning process, scanning the substrate using a scanning probe microscope (SPM) to generate an SPM image of the substrate, feeding the SPM image into a trained convolution neural network (CNN), analyzing the SPM image using the CNN to identify substrate defects, determining a defect free substrate area for pattern application; and applying the pattern to the substrate in that area. An atom scale electronic component includes functional patches on a substrate and wires electrically connecting the functional patches. Training a CNN includes recording a Scanning Tunneling Microscope (STM) image of the substrate, extracting images of defects from the STM image, labeling pixel-wise the defect images, and feeding the extracted and labeled images of defects into a CNN to train the CNN for semantic segmentation.

Abstract: A method for autonomously applying a dangling bond pattern to a substrate for atom scale device fabrication includes inputting the pattern, initiating a patterning process, scanning the substrate using a scanning probe microscope (SPM) to generate an SPM image of the substrate, feeding the SPM image into a trained convolution neural network (CNN), analyzing the SPM image using the CNN to identify substrate defects, determining a defect free substrate area for pattern application; and applying the pattern to the substrate in that area. An atom scale electronic component includes functional patches on a substrate and wires electrically connecting the functional patches. Training a CNN includes recording a Scanning Tunneling Microscope (STM) image of the substrate, extracting images of defects from the STM image, labeling pixel-wise the defect images, and feeding the extracted and labeled images of defects into a CNN to train the CNN for semantic segmentation.