Fig. 1 STEM data: Original and processed by neural networks.

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Fig. 1 STEM data: Original and processed by neural networks. STEM data: Original and processed by neural networks. (A) STEM overview image. Brighter areas typically correspond to amorphous Si-C regions, from which Si atoms can be dispersed into clean graphene lattice, leading to various Si defect structures (in terms of number of Si atoms and their bonding to each other and to nearby lattice atoms). (B) Results of applying a defect sniffer (deep neural network followed by density-based spatial clustering) to data in (A). White markers show regions of interest as identified by a defect sniffer. Notice that it ignores amorphous Si-C regions and returns information on the location of point Si defects, only (C) 2 nm by 2 nm area cropped around one of the identified defects [white box in (B)]. This cropped image serves as an input to atom finder model. (D) The output of an atom finder network for the image in (C), where red blobs correspond to C lattice atoms and a green blob is associated with Si impurity. Maxim Ziatdinov et al. Sci Adv 2019;5:eaaw8989 Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).