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Noise2Atom: unsupervised denoising for scanning transmission electron microscopy images
Feng Wang,Trond R. Henninen,Debora Keller,Rolf Erni 한국현미경학회 2020 Applied microscopy Vol.50 No.1
We propose an effective deep learning model to denoise scanning transmission electron microscopy (STEM) image series, named Noise2Atom, to map images from a source domain S S to a target domain C C , where S S is for our noisy experimental dataset, and C C is for the desired clear atomic images. Noise2Atom uses two external networks to apply additional constraints from the domain knowledge. This model requires no signal prior, no noise model estimation, and no paired training images. The only assumption is that the inputs are acquired with identical experimental configurations. To evaluate the restoration performance of our model, as it is impossible to obtain ground truth for our experimental dataset, we propose consecutive structural similarity (CSS) for image quality assessment, based on the fact that the structures remain much the same as the previous frame(s) within small scan intervals. We demonstrate the superiority of our model by providing evaluation in terms of CSS and visual quality on different experimental datasets.
Atomic Scale Study on Growth and Heteroepitaxy of ZnO Monolayer on Graphene
Hong, Hyo-Ki,Jo, Junhyeon,Hwang, Daeyeon,Lee, Jongyeong,Kim, Na Yeon,Son, Seungwoo,Kim, Jung Hwa,Jin, Mi-Jin,Jun, Young Chul,Erni, Rolf,Kwak, Sang Kyu,Yoo, Jung-Woo,Lee, Zonghoon American Chemical Society 2017 NANO LETTERS Vol.17 No.1
<P/><P>Atomically thin semiconducting oxide on graphene carries a unique combination of wide band gap, high charge carrier mobility, and optical transparency, which can be widely applied for optoelectronics. However, study on the epitaxial formation and properties of oxide monolayer on graphene remains unexplored due to hydrophobic graphene surface and limits of conventional bulk deposition technique. Here, we report atomic scale study of heteroepitaxial growth and relationship of a single-atom-thick ZnO layer on graphene using atomic layer deposition. We demonstrate atom-by-atom growth of zinc and oxygen at the preferential zigzag edge of a ZnO monolayer on graphene through <I>in situ</I> observation. We experimentally determine that the thinnest ZnO monolayer has a wide band gap (up to 4.0 eV), due to quantum confinement and graphene-like structure, and high optical transparency. This study can lead to a new class of atomically thin two-dimensional heterostructures of semiconducting oxides formed by highly controlled epitaxial growth.</P>