In Situ Scanning Transmission Electron Microscopy Study of MoS2 Formation on Graphene with a Deep-Learning Framework.

Atomic-scale information is essential for understanding and designing unique structures and properties of two-dimensional (2D) materials. Recent developments in in situ transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) enable research to provide abundant insights into the growth of nanomaterials. In this study, 2D MoS2 is synthesized on a suspended graphene substrate inside a TEM column through thermolysis of the ammonium tetrathiomolybdate (NH4)2MoS4 precursor at 500 °C. To avoid misinterpretation of the in situ STEM images, a deep-learning framework, DeepSTEM, is developed. The DeepSTEM framework successfully reconstructs an object function in atomic-resolution STEM imaging for accurate determination of the atomic structure and dynamic analysis. In situ STEM imaging with DeepSTEM enables observation of the edge configuration, formation, and reknitting progress of MoS2 clusters with the formation of a mirror twin boundary. The synthesized MoS2/graphene heterostructure shows various twist angles, as revealed by atomic-resolution TEM. This deep-learning framework-assisted in situ STEM imaging provides atomic information for in-depth studies on the growth and structure of 2D materials and shows the potential use of deep-learning techniques in 2D material research.

Spontaneous Formation of a ZnO Monolayer by the Redox Reaction of Zn on Graphene Oxide.

Graphene-based two-dimensional heterostructures are of substantial interest both for fundamental studies and their various potential applications. Particularly interesting are atomically thin semiconducting oxides on graphene, which uniquely combine a wide band gap and optical transparency. Here, we report the atomic-scale investigation of a novel self-formation of a ZnO monolayer from the Zn metal on a graphene oxide substrate. The spontaneous oxidation of the ultrathin Zn metal occurs by a reaction with oxygen supplied from the graphene oxide substrate, and graphene oxide is deoxygenated by a transfer of oxygen from O-containing functional groups to the zinc metal. The ZnO monolayer formed by this spontaneous redox reaction shows a graphene-like structure and a band gap of about 4 eV. This study demonstrates a unique and straightforward synthetic route to atomically thin two-dimensional heterostructures made from a two-dimensional metal oxide and graphene, formed by the spontaneous redox reaction of a very thin metal layer directly deposited on graphene oxide.

Contrast Transfer Function-Based Exit-Wave Reconstruction and Denoising of Atomic-Resolution Transmission Electron Microscopy Images of Graphene and Cu Single Atom Substitutions by Deep Learning Framework.

The exit wave is the state of a uniform plane incident electron wave exiting immediately after passing through a specimen and before the atomic-resolution transmission electron microscopy (ARTEM) image is modified by the aberration of the optical system and the incoherence effect of the electron. Although exit-wave reconstruction has been developed to prevent the misinterpretation of ARTEM images, there have been limitations in the use of conventional exit-wave reconstruction in ARTEM studies of the structure and dynamics of two-dimensional materials. In this study, we propose a framework that consists of the convolutional dual-decoder autoencoder to reconstruct the exit wave and denoise ARTEM images. We calculated the contrast transfer function (CTF) for real ARTEM and assigned the output of each decoder to the CTF as the amplitude and phase of the exit wave. We present exit-wave reconstruction experiments with ARTEM images of monolayer graphene and compare the findings with those of a simulated exit wave. Cu single atom substitution in monolayer graphene was, for the first time, directly identified through exit-wave reconstruction experiments. Our exit-wave reconstruction experiments show that the performance of the denoising task is improved when compared to the Wiener filter in terms of the signal-to-noise ratio, peak signal-to-noise ratio, and structural similarity index map metrics.

Atomic Scale Study on Growth and Heteroepitaxy of ZnO Monolayer on Graphene.

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 in situ 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.

Atomic-scale dynamics of triangular hole growth in monolayer hexagonal boron nitride under electron irradiation.

The production of holes by electron beam irradiation in hexagonal boron nitride (hBN), which has a lattice similar to that of graphene, is monitored over time using atomic resolution transmission electron microscopy. The holes appear to be initiated by the formation of a vacancy of boron and grow in a manner that retains an overall triangular shape. The hole growth process involves the formation of single chains of B and N atoms and is accompanied by the ejection of atoms and bundles of atoms along the hole edges, as well as atom migration. These observations are compared to density functional theory calculations and molecular dynamics simulations.