Erratum to: “Column-by-column compositional mapping by Z-contrast imaging” [Ultramicroscopy 109(2) (2009) 172–176]

Deep Learning-Assisted Quantification of Atomic Dopants and Defects in 2D Materials

Atomic dopants and defects play a crucial role in creating new functionalities in 2D transition metal dichalcogenides (2D TMDs). Therefore, atomic-scale identification and their quantification warrant precise engineering that widens their application to many fields, ranging from development of optoelectronic devices to magnetic semiconductors. Scanning transmission electron microscopy with a sub-Å probe has provided a facile way to observe local dopants and defects in 2D TMDs. However, manual data analytics of experimental images is a time-consuming task, and often requires subjective decisions to interpret observed signals. Therefore, an approach is required to automate the detection and classification of dopants and defects. In this study, based on a deep learning algorithm, fully convolutional neural network that shows a superior ability of image segmentation, an efficient and automated method for reliable quantification of dopants and defects in TMDs is proposed with single-atom precision. The approach demonstrates that atomic dopants and defects are precisely mapped with a detection limit of ≈1 × 1012 cm-2 , and with a measurement accuracy of ≈98% for most atomic sites. Furthermore, this methodology is applicable to large volume of image data to extract atomic site-specific information, thus providing insights into the formation mechanisms of various defects under stimuli.

Influence of the crosstalk on the intensity of HAADF-STEM images of quaternary semiconductor materials

The influence of the neighbouring atomic-columns in determining the composition at atomic column scale of quaternary semiconductor compounds, using simulated HAADF-STEM images is evaluated. The InAlAsSb alloy, a promising material in the photovoltaic field, is considered. We find that the so called 'crosstalk' effect plays an important role for the aimed compositional determination. The intensity transfer is larger from neighbouring atomic columns with higher average Z, and towards atomic columns with smaller Z. Our results show that in order to obtain precise information on the column composition, the HAADF-STEM intensities of both columns need to be taken into account simultaneously.