Formation of Hydrogenated Graphene Nanoripples by Strain Engineering and Directed Surface Self-assembly

We propose a new class of semiconducting graphene-based nanostructures: hydrogenated graphene nanoripples (HGNRs), based on continuum-mechanics analysis and first principles calculations. They are formed via a two-step combinatorial approach: first by strain engineered pattern formation of graphene nanoripples, followed by a curvature-directed self-assembly of H adsorption. It offers a high level of control of the structure and morphology of the HGNRs, and hence their band gaps which share common features with graphene nanoribbons. A cycle of H adsorption/desorption at/from the same surface locations completes a reversible metal-semiconductor-metal transition with the same band gap.Comment: 11 pages, 5 figure

An Optimal Binding Number Condition for Bipancyclism

published_or_final_versio

Total Dual Integrality in Some Facility Location Problems

published_or_final_versio

Mathematics simulation and experiments of continuous casting with strip feeding in mold

Steel strip feeding technology can reduce the degree of superheat of the molten steel, change the solidification order of the molten steel; raise the equiaxed crystal rate of the slab and improve the continuous casting quality. The paper establishes the mathematical model of heat transfer and temperature field of casting billet of steel strip feeding in continuous casting mold. Results show that if Plate Billet is 1 000 mm × 220 mm and the steel strip is 100 mm × 3 mm, feeding position of parallel is 250 mm from the narrow side. When the feeding speed is 3,6 m/min, the superheat degree can be reduced by 5 °C, and the solidification length can be reduced by 2,9 m. When the feeding speed is 6 m/min, the superheat degree can be reduced by about 9 °C, and the solidification length can be reduced by 3,7 m. The results of the test in a steel plant are in good agreement with the experimental results

Predicting Indoor Temperature Distribution Based on Contribution Ratio of Indoor Climate (CRI) and Mobile Sensors

In practical building control, quickly obtaining detailed indoor temperature distribution is necessary for providing satisfying personal comfort and improving building energy efficiency. The aim of this study is to propose a fast prediction method for indoor temperature distribution without knowing the thermal boundary conditions in practical applications. In this method, the index of contribution ratio of indoor climate (CRI), which represents the independent contribution of each heat source to the temperature distribution, has been combined with the air temperature collected by one mobile sensor at the height of the working area. Based on a typical office model, the effectiveness of using mobile sensors was discussed, and the influence of its acquisition height and acquisition distance on the prediction accuracy was analyzed as well. The results showed that the proposed prediction method was effective. When the sensors fixed on the wall were used to predict the indoor temperature distribution, the maximum average relative error was 27.7%, whereas when the mobile sensor was used to replace the fixed sensors, the maximum average relative error was 4.8%. This indicates that using mobile sensors with flexible acquisition location can help promote both reliability and accuracy of temperature prediction. In the human activity area, data from a set of mobile sensors were used to predict the temperature distribution at four heights. The prediction accuracy was 2.1%, 2.1%, 2.3%, and 2.7%, respectively. However, the influence of acquisition distance of mobile sensors on prediction accuracy cannot be ignored. The distance should be large enough to disperse the distribution of the acquisition points. Due to the influence of airflow, some distance between the acquisition points and the room boundaries should be given