Hydrogenation of Graphene and Hydrogen Diffusion Behavior on Graphene/Graphane Interface

Hydrogenation of carbon materials has been attracting a wide range of interests as an application of hydrogen storage materials in hydrogen-powered automobile as well as a methodology to manipulate the electric properties of carbon materials. Graphene with unique electronic, thermal and mechanical properties has been investigated as one of the most promising candidates for the next generation of electronic materials (Geim, 2009). However, several major challenges have to be tackled before the widespread application of graphene. For example, the absence of a band gap in the electronic spectrum of intrinsic graphene and the Klein paradox as a consequence of the Dirac-type nature of the charge carriers (Novoselov et al., 2004; Rao et al., 2009). The most efficient way to overcome these problems is hydrogenation of graphene (Luo et al., 2009). The graphane (Sofo et al., 2007), a fully hydrogenated single layer of graphene, was suggested to possess the promising semiconductor properties with a band gap of around 3.5 eV theoretically. Very recently, Elias et al. (Elias et al, 2009) experimentally demonstrated the formation of graphane through the exposure of a graphene membrane to hydrogen plasma. Subsequently, the rate of hydrogenation process of multilayer graphene was found to strongly depend on the number of layers (Luo et al., 2009; Ryu et al., 2008). These discoveries open important perspectives for the application of graphene-based devices because the electronic gap in those graphanes could be controlled by the degree of hydrogenation (Elias et al., 2009; Zhou et al., 2009)

Applications of Al Modified Graphene on Gas Sensors and Hydrogen Storage

The Stone Age, the Bronze Age, the Iron Age... Every global epoch in the history of the mankind is characterized by materials used in it. In 2004 a new era in material science was opened: the era of graphene or, more generally, of two-dimensional materials. Graphene is the strongest and the most stretchable known material, it has the record thermal conductivity and the very high mobility of charge carriers. It demonstrates many interesting fundamental physical effects and promises a lot of applications, among which are conductive ink, terahertz transistors, ultrafast photodetectors and bendable touch screens. In 2010 Andre Geim and Konstantin Novoselov were awarded the Nobel Prize in Physics "for groundbreaking experiments regarding the two-dimensional material graphene". The two volumes Physics and Applications of Graphene - Experiments and Physics and Applications of Graphene - Theory contain a collection of research articles reporting on different aspects of experimental and theoretical studies of this new material

Editorial: Environmental Catalysis and the Corresponding Catalytic Mechanism

Editorial on the Research Topic Environmental Catalysis and the Corresponding Catalytic MechanismZA was supported by National Natural Science Foundation of China (21777033 and 21607029), Science and Technology Program of Guangdong Province (2017B020216003), and Science and Technology Program of Guangzhou City (201707010359)

Deep Domain Adaptation for Pavement Crack Detection

Deep learning-based pavement cracks detection methods often require large-scale labels with detailed crack location information to learn accurate predictions. In practice, however, crack locations are very difficult to be manually annotated due to various visual patterns of pavement crack. In this paper, we propose a Deep Domain Adaptation-based Crack Detection Network (DDACDN), which learns to take advantage of the source domain knowledge to predict the multi-category crack location information in the target domain, where only image-level labels are available. Specifically, DDACDN first extracts crack features from both the source and target domain by a two-branch weights-shared backbone network. And in an effort to achieve the cross-domain adaptation, an intermediate domain is constructed by aggregating the three-scale features from the feature space of each domain to adapt the crack features from the source domain to the target domain. Finally, the network involves the knowledge of both domains and is trained to recognize and localize pavement cracks. To facilitate accurate training and validation for domain adaptation, we use two challenging pavement crack datasets CQU-BPDD and RDD2020. Furthermore, we construct a new large-scale Bituminous Pavement Multi-label Disease Dataset named CQU-BPMDD, which contains 38994 high-resolution pavement disease images to further evaluate the robustness of our model. Extensive experiments demonstrate that DDACDN outperforms state-of-the-art pavement crack detection methods in predicting the crack location on the target domain.Comment: 12 pages, 10 figure

Photocatalytic reforming of lignocellulose: A review

Biomass has been considered as a promising energy resource to combat the exhaustion of fossil fuels, as it is renewable, sustainable, and clean. Photocatalytic reforming is a novel technology to utilize solar energy for upgrading biomass in relatively mild conditions. This process efficiently reforms and recasts biomass into hydrogen and/or valuable chemicals. To date, lignocellulose, including cellulose, hemicellulose and lignin, has attracted extensive studies in facile photocatalytic valorisation. This review summarizes and analyzes the most recent research advances on photoreforming of lignocellulose to provide insights for future research, with a particular emphasis on the reformation of lignin because of its 3D complex and stubborn structure. The structure of lignin contains a dominant linkage, i.e., β-O-4. The breakage of β-O-4 linkage can be proceeded by two steps, e.g., oxidization and reduction, according to the sequence of photoexcited holes and electrons. Thus, this review discusses two-step and integrate step dissociation strategies along with the rationally chosen photocatalysts. The challenges of the photocatalysts, solvent, and post-treatment were identified, and potential solutions to these challenges were provided

Nitrogen-doped carbon nanospheres-modified graphitic carbon nitride with outstanding photocatalytic activity

Metals and metal oxides are widely used as photo/electro-catalysts for environmental remediation. However, there are many issues related to these metal-based catalysts for practical applications, such as high cost and detrimental environmental impact due to metal leaching. Carbon-based catalysts have the potential to overcome these limitations. In this study, monodisperse nitrogen-doped carbon nanospheres (NCs) were synthesized and loaded onto graphitic carbon nitride (g-C3N4, GCN) via a facile hydrothermal method for photocatalytic removal of sulfachloropyridazine (SCP). The prepared metal-free GCN-NC exhibited remarkably enhanced efficiency in SCP degradation. The nitrogen content in NC critically influences the physicochemical properties and performances of the resultant hybrids. The optimum nitrogen doping concentration was identified at 6.0 wt%. The SCP removal rates can be improved by a factor of 4.7 and 3.2, under UV and visible lights, by the GCN-NC composite due to the enhanced charge mobility and visible light harvesting. The mechanism of the improved photocatalytic performance and band structure alternation were further investigated by density functional theory (DFT) calculations. The DFT results confirm the high capability of the GCN-NC hybrids to activate the electron–hole pairs by reducing the band gap energy and efficiently separating electron/hole pairs. Superoxide and hydroxyl radicals are subsequently produced, leading to the efficient SCP removal

Temperature- and thickness-dependent elastic moduli of polymer thin films

The mechanical properties of polymer ultrathin films are usually different from those of their counterparts in bulk. Understanding the effect of thickness on the mechanical properties of these films is crucial for their applications. However, it is a great challenge to measure their elastic modulus experimentally with in situ heating. In this study, a thermodynamic model for temperature- (T) and thickness (h)-dependent elastic moduli of polymer thin films Ef(T,h) is developed with verification by the reported experimental data on polystyrene (PS) thin films. For the PS thin films on a passivated substrate, Ef(T,h) decreases with the decreasing film thickness, when h is less than 60 nm at ambient temperature. However, the onset thickness (h*), at which thickness Ef(T,h) deviates from the bulk value, can be modulated by T. h* becomes larger at higher T because of the depression of the quenching depth, which determines the thickness of the surface layer δ

Insights into N-doping in single-walled carbon nanotubes for enhanced activation of superoxides: A mechanistic study

Emerging characteristics upon nitrogen-doping were differentiated in the activation of superoxides over single-walled carbon nanotubes. Both experimental and theoretical studies revealed that enhanced peroxymonosulfate (PMS) activation is ascribed to a nonradical process while persulfate (PS) activation is accelerated via directly oxidizing water, yet hydrogen peroxide (H2O2) activation is inert to N-doping. This study details the first insights into versatile N-doping in carbocatalysis for organic oxidation in sustainable remediation