Device design based on the covalent homocouplingof porphine molecules

Porphine has a great potential application in molecular electronic devices.In this work,based on the density functional theory(DFT)and combining with nonequilibrium Green's function(NEGF),we study the transport properties of the molecular devices constructed by the covalent homocoupling of porphine molecules conjunction with zigzag graphene nanoribbons electrodes.We find that different couple phases bring remarkable differences in the transport properties.Different coupling phases have different application prospects.We analyze and discuss the differences in transport properties through the molecular energy spectrum,electrostatic difference potential,local density of states(LDOS),and transmission pathway.The results are of great significance for the design of porphine molecular devices in the future.

Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models

Scale is the basic attribute for expressing anddescribing spatial entity and phenomena. It offerstheoretical significance in the study of gully structureinformation, variable characteristics of watershed mor-phology, and development evolution at different scales.This research selected five different areas in China＇s LoessPlateau as the experimental region and used DEM data atdifferent scales as the experimental data. First, the changerule of the characteristic parameters of the data at differentscales was analyzed. The watershed structure informationdid not change along with a change in the data scale. Thiscondition was proven by selecting indices of gullybifurcation ratio and fractal dimension as characteristicparameters of watershed structure information. Then, thechange rule of the characteristic parameters of gullystructure with different analysis scales was analyzed bysetting the scale sequence of analysis at the extractiongully. The gully structure of the watershed changed withvariations in the analysis scale, and the change rule wasobvious when the gully level changed. Finally, the changerule of the characteristic parameters of the gully structure atdifferent areas was analyzed. The gully fractal dimensionshowed a significant numerical difference in differentareas, whereas the variation of the gully branch ratio wassmall. The change rule indicated that the developmentdegree of the gully obviously varied in different regions,but the morphological structure was basically similar.

Landform classification based on optimal texture feature extraction from DEM data in Shandong Hilly Area, China

Texture and its analysis methods are crucial for image feature extraction and classification. Digital elevation model (DEM) is the most important data source of digital terrain analysis and landform classification, and considerable research values are gained from texture feature extraction and analysis from DEM data. In this research, on the basis of optimal texture feature extraction, the hilly area in Shandong, China, was selected as the study area, and DEM data with a resolution of 500 m were used as the experimental data for landform classification. First, second-order texture measures and texture image were extracted from DEM data by using a gray level cooccurrence matrix (GLCM). Second, the variation characteristics of each texture measure were analyzed, and the optimal feature parameters, such as direction, gray level, and texture window, were determined. Meanwhile, the texture feature value, combined with maximum information, was calculated, and the multiband texture image was obtained by resolving three optimal texture measure images. Finally, a support vector machine (SVM) method was adopted to classify landforms on the basis of the multiband texture image. Results indicated that the texture features of DEM data can be sufficiently represented and measured via the quantitative GLCM method. However, the feature parameters during the texture feature value calculation required further optimization. Based on the image texture from DEM data, efficient classification accuracy and ideal classification effect were achieved.