Physisorption-based charge transfer in two-dimensional SnS2 for selective and reversible NO2 gas sensing

Nitrogen dioxide (NO2) is a gas species that plays an important role in certain industrial, farming, and healthcare sectors. However, there are still significant challenges for NO2 sensing at low detection limits, especially in the presence of other interfering gases. The NO2 selectivity of current gas-sensing technologies is significantly traded-off with their sensitivity and reversibility as well as fabrication and operating costs. In this work, we present an important progress for selective and reversible NO2 sensing by demonstrating an economical sensing platform based on the charge transfer between physisorbed NO2 gas molecules and two-dimensional (2D) tin disulfide (SnS2) flakes at low operating temperatures. The device shows high sensitivity and superior selectivity to NO2 at operating temperatures of less than 160 °C, which are well below those of chemisorptive and ion conductive NO2 sensors with much poorer selectivity. At the same time, excellent reversibility of the sensor is demonstrated, which has rarely been observed in other 2D material counterparts. Such impressive features originate from the planar morphology of 2D SnS2 as well as unique physical affinity and favorable electronic band positions of this material that facilitate the NO2 physisorption and charge transfer at parts per billion levels. The 2D SnS2-based sensor provides a real solution for low-cost and selective NO2 gas sensing

Regional metabolic patterns of abnormal postoperative behavioral performance in aged mice assessed by 1H-NMR dynamic mapping method

Abstract Abnormal postoperative neurobehavioral performance (APNP) is a common phenomenon in the early postoperative period. The disturbed homeostatic status of metabolites in the brain after anesthesia and surgery might make a significant contribution to APNP. The dynamic changes of metabolites in different brain regions after anesthesia and surgery, as well as their potential association with APNP are still not well understood. Here, we used a battery of behavioral tests to assess the effects of laparotomy under isoflurane anesthesia in aged mice, and investigated the metabolites in 12 different sub-regions of the brain at different time points using proton nuclear magnetic resonance (1H-NMR) spectroscopy. The abnormal neurobehavioral performance occurred at 6 h and/or 9 h, and recovered at 24 h after anesthesia/surgery. Compared with the control group, the altered metabolite of the model group at 6 h was aspartate (Asp), and the difference was mainly displayed in the cortex; while significant changes at 9 h occurred predominantly in the cortex and hippocampus, and the corresponding metabolites were Asp and glutamate (Glu). All changes returned to baseline at 24 h. The altered metabolic changes could have occurred as a result of the acute APNP, and the metabolites Asp and Glu in the cortex and hippocampus could provide preliminary evidence for understanding the APNP process

Chalcogenide Glass-on-Graphene Photonics

Two-dimensional (2-D) materials are of tremendous interest to integrated photonics given their singular optical characteristics spanning light emission, modulation, saturable absorption, and nonlinear optics. To harness their optical properties, these atomically thin materials are usually attached onto prefabricated devices via a transfer process. In this paper, we present a new route for 2-D material integration with planar photonics. Central to this approach is the use of chalcogenide glass, a multifunctional material which can be directly deposited and patterned on a wide variety of 2-D materials and can simultaneously function as the light guiding medium, a gate dielectric, and a passivation layer for 2-D materials. Besides claiming improved fabrication yield and throughput compared to the traditional transfer process, our technique also enables unconventional multilayer device geometries optimally designed for enhancing light-matter interactions in the 2-D layers. Capitalizing on this facile integration method, we demonstrate a series of high-performance glass-on-graphene devices including ultra-broadband on-chip polarizers, energy-efficient thermo-optic switches, as well as graphene-based mid-infrared (mid-IR) waveguide-integrated photodetectors and modulators

The Design and Verification of Disaster Recovery Strategies in Cloud Disaster Recovery Center

Disaster recovery is an important means to ensure business continuity. However, the disaster recovery investment is so huge that the cloud disaster recovery becomes a best choice for enterprises, especially for SMEs. This paper discusses the necessity and importance of the cloud disaster recovery center and the vital indicators of disaster recovery by analyzing the classification and selecting principle of cloud disaster recovery strategy, developing disaster recovery strategy based on major disaster recovery strategy finally. In the end, this paper verifies the feasibility of the disaster recovery strategy by two specific cases of disaster recovery implementation. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.294

Research on Optimal Path of Data Migration among Multisupercomputer Centers

Data collaboration between supercomputer centers requires a lot of data migration. In order to increase the efficiency of data migration, it is necessary to design optimal path of data transmission among multisupercomputer centers. Based on the situation that the target center which finished receiving data can be regarded as the new source center to migrate data to others, we present a parallel scheme for the data migration among multisupercomputer centers with different interconnection topologies using graph theory analysis and calculations. Finally, we verify that this method is effective via numeric simulation

Research on Optimal Path of Data Migration among Multisupercomputer Centers

Data collaboration between supercomputer centers requires a lot of data migration. In order to increase the efficiency of data migration, it is necessary to design optimal path of data transmission among multisupercomputer centers. Based on the situation that the target center which finished receiving data can be regarded as the new source center to migrate data to others, we present a parallel scheme for the data migration among multisupercomputer centers with different interconnection topologies using graph theory analysis and calculations. Finally, we verify that this method is effective via numeric simulation

Evolution and Influencing Factors of Venture Capital Network Structure among Chinese Cities

Inter-city Venture Capital (VC) exchange is a micro-embodiment of the cross-regional flow of innovative elements such as capital and technology, and also an important driving force for shaping the network of VC cities. Compared with other types of investment activities, VC has more advantages in promoting the development of innovative industries, especially high-tech industries, and then driving urban economy and regional development; hence, it is widely regarded as a "catalyst" for economic growth and technological innovation. The study of VC networks is helpful in understanding the financial activity links between cities across the country and provides key support for further rational allocation of financial resources between cities. The existing research rarely uses the actual investment amount of VC transaction events between cities to construct the city network. The analysis of the continuous dynamic evolution research and the influencing factors of the overall spatial network structure over a long period of time needs to be strengthened. To compensate for the shortcomings in the above research, this study uses the data of China's inter-city VC flow between 2000 and 2018 to construct the Chinese urban VC network. The long-term spatial evolution characteristics and overall network structure influencing factors of the national inter-city VC network are discussed based on complex network analysis, GIS spatial technology analysis, multiple linear regression model, and so on. This study derives the following results: (1) The connection between cities tends to be closer, and the agglomeration degree of the national VC network increases, displaying obvious characteristics of high aggregation and small-world network. However, the cyber spatial structure of investors/start-ups tends to be flattened, there is a trend of decentralization. (2) The VC connection between cities has expanded from the eastern coastal axis to the central and western regions as a whole, exhibiting obvious characteristics of path dependence and distance attenuation. Additionally, the VC connection continues to sink from the three major urban agglomerations to other marginal cities, and the core node cities of the network also display a tendency of quantitative expansion and power transfer. (3) The city's entrepreneurial foundation, VC industry development level, financial environment, and urban accessibility all have differentiated impacts on the spatial structure of the national VC network. Moreover, the aforementioned are affected by various mechanisms such as multi-dimensional proximity, urban economy, and path dependence, which promote the construction of national and regional VC networks and the formation and evolution of regional capital centers