With its exceptional charge mobility, graphene holds great promise for applications in next-generation electronics. In an effort to tailor its properties and interfacial characteristics, the chemical functionalization of graphene is being actively pursued. The oxidation of graphene via the Hummers method is most widely used in current studies, although the chemical inhomogeneity and irreversibility of the resulting graphene oxide compromises its use in high-performance devices. Here, we present an alternative approach for oxidizing epitaxial graphene using atomic oxygen in ultrahigh vacuum. Atomic-resolution characterization with scanning tunnelling microscopy is quantitatively compared to density functional theory, showing that ultrahigh-vacuum oxidization results in uniform epoxy functionalization. Furthermore, this oxidation is shown to be fully reversible at temperatures as low as 260 °C using scanning tunnelling microscopy and spectroscopic techniques. In this manner, ultrahigh-vacuum oxidation overcomes the limitations of Hummers-method graphene oxide, thus creating new opportunities for the study and application of chemically functionalized graphene.
Generating a description of an image is called image captioning. Image captioning requires to recognize the important objects, their attributes and their relationships in an image. It also needs to generate syntactically and semantically correct sentences. Deep learning-based techniques are capable of handling the complexities and challenges of image captioning. In this survey paper, we aim to present a comprehensive review of existing deep learning-based image captioning techniques. We discuss the foundation of the techniques to analyze their performances, strengths and limitations. We also discuss the datasets and the evaluation metrics popularly used in deep learning based automatic image captioning.
Current interest in the fabrication of organic nanostructures on silicon surface is focused on the self-directed growth of 1D molecular lines with predefined position, structure, composition, and the length on the H-terminated Si(100)-(2 x 1) surface. To date, no studies have succeeded in growing the molecular line across the dimer rows on Si(100)-(2 x 1)-H, which is highly desirable. Using scanning tunneling microscopy (STM), we studied a new molecular system (allyl mercaptan, CH2=CH-CH2-SH) that undergoes chain reaction across the dimer row on the Si(100)-(2 x 1)-H surface at 300 K and produces covalently bonded 1D molecular lines. In combination with the previous findings of chain reaction along the rows, the present observations of self-directed growth of 1D molecular lines across the dimer rows on the Si(100)-(2 x 1)-H surface provide a means to connect any two points (through molecular lines) on a 2D surface.
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