Single-layer behavior and slow carrier density dynamic of twisted graphene bilayer

We report scanning tunneling microscopy (STM) and spectroscopy (STS) of twisted graphene bilayer on SiC substrate. For twist angle ~ 4.5o the Dirac point ED is located about 0.40 eV below the Fermi level EF due to the electron doping at the graphene/SiC interface. We observed an unexpected result that the local Dirac point around a nanoscaled defect shifts towards the Fermi energy during the STS measurements (with a time scale about 100 seconds). This behavior was attributed to the decoupling between the twisted graphene and the substrate during the measurements, which lowers the carrier density of graphene simultaneously

How Volatile is ENSO for Global Greenhouse Gas Emissions and the Global Economy?

Abstract: This paper analyzes two indexes in order to capture the volatility inherent in El Niños Southern Oscillations (ENSO), develops the relationship between the strength of ENSO and greenhouse gas emissions, which increase as the economy grows, with carbon dioxide being the major greenhouse gas, and examines how these gases affect the frequency and strength of El Niño on the global economy. The empirical results show that both the ARMA(1,1)-GARCH(1,1) and ARMA(3,2)-GJR(1,1) models are suitable for modelling ENSO volatility accurately, and that 1998 is a turning point, which indicates that the ENSO strength has increased since 1998. Moreover, the increasing ENSO strength is due to the increase in greenhouse gas emissions. The ENSO strengths for Sea Surface Temperature (SST) are predicted for the year 2030 to increase from 29.62% to 81.5% if global CO2 emissions increase by 40% to 110%, respectively. This indicates that we will be faced with even stronger El Niño or La Niña effects in the future if global greenhouse gas emissions continue to increase unabated

Building Identification to Co-Create Supply Chain Innovation

Supply chain identification is a process of self-categorization which can encourage firms to make more efforts to achieve supply chain goals. It is important for firms to co-create value with customers/suppliers while pursuing supply chain innovation. However, few studies have investigated identification issues from the business-to-business aspects. Therefore, the purpose of this study is to investigate the identification generation among supply chain members, especially focus on the exchange mechanisms of identification. Based on these mechanisms, we develop a research model to explain the influences of the exchange mechanisms on information sharing and supply chain innovation. This empirical study investigates the top 1000 Taiwanese manufacturers issued by Commonwealth magazine of Taiwan in 2012. The results show: (1) The exchange mechanisms, including trust, commitment, communication, and reciprocal relationship have significant effects on information sharing. (2) Information sharing in the value co-creating process has a significant effect on supply chain innovation. Implications are provided based on the results

Compensation of blue phase I by blue phase II in optoeletronic device

Compensation effect of blue phase I (BP I) with blue phase II (BP II) liquid crystal was demonstrated. BP I and BP II were co-exist in the optoeletronic device by polymer stabilization. Consequently, disadvantages of BP I and BP II were greatly improved by compensation effect and resulted in high contrast ratio, low hysteresis and fast falling time. Mechanism of compensation effect was explained by relaxation ability of lattice structure under electrical field and compensation structure was well confirmed by Bragg\u27s reflectance spectrum and Commission International de l\u27Eclairage chromaticity diagram

Vertices with the Second Neighborhood Property in Eulerian Digraphs

The Second Neighborhood Conjecture states that every simple digraph has a vertex whose second out-neighborhood is at least as large as its first out-neighborhood, i.e. a vertex with the Second Neighborhood Property. A cycle intersection graph of an even graph is a new graph whose vertices are the cycles in a cycle decomposition of the original graph and whose edges represent vertex intersections of the cycles. By using a digraph variant of this concept, we prove that Eulerian digraphs which admit a simple dicycle intersection graph have not only adhere to the Second Neighborhood Conjecture, but have a vertex of minimum outdegree that has the Second Neighborhood Property.Comment: fixed an error in an earlier version and made structural change

3,5-Dibromo-2-hydroxy­benzaldehyde

The title compound, C7H4Br2O2, exhibits a layer packing structure via weak π–π stacking inter­actions [centroid–centroid distances between adjacent aromatic rings are 4.040 (8) and 3.776 (7) Å]. Mol­ecules in each layer are linked by inter­molecular O—H⋯O hydrogen bonding and Br⋯Br inter­actions [3.772 (4) Å]. There are two mol­ecules in the asymmetric unit

catena-Poly[copper(II)-bis(μ-2,4-dichloro-6-formyl­phenolato)-κ3 O,O′:Cl 4;κ3 Cl 4:O,O′]

In the title compound, [Cu(C7H3Cl2O2)2]n, the CuII atom lies on a centre of inversion and adopts a [4+2] coordination mode, with two long axial Cu—Cl coordinative bonds complementing four Cu—O bonds from two 2,4-dichloro-6-formyl­phenolate ligands in a distorted square plane. π–π stacking inter­actions are also formed between neighbouring aromatic rings, with a centroid–centroid separation of 3.624 (2) Å

How Volatile is ENSO for Global Greenhouse Gas Emissions and the Global Economy?

This paper analyzes two indexes in order to capture the volatility inherent in El Niños Southern Oscillations (ENSO), develops the relationship between the strength of ENSO and greenhouse gas emissions, which increase as the economy grows, with carbon dioxide being the major greenhouse gas, and examines how these gases affect the frequency and strength of El Niño on the global economy. The empirical results show that both the ARMA(1,1)-GARCH(1,1) and ARMA(3,2)-GJR(1,1) models are suitable for modelling ENSO volatility accurately, and that 1998 is a turning point, which indicates that the ENSO strength has increased since 1998. Moreover, the increasing ENSO strength is due to the increase in greenhouse gas emissions. The ENSO strengths for Sea Surface Temperature (SST) are predicted for the year 2030 to increase from 29.62% to 81.5% if global CO2 emissions increase by 40% to 110%, respectively. This indicates that we will be faced with even stronger El Nino or La Nina effects in the future if global greenhouse gas emissions continue to increase unabated