In this paper, we study the thermal rectification in asymmetric U-shaped graphene flakes by using nonequilibrium molecular dynamics simulations. The graphene flakes are composed by a beam and two arms. It is found that the heat flux runs preferentially from the wide arm to the narrow arm which indicates a strong rectification effect. The dependence of the rectification ratio upon the heat flux, the length and the width of the beam, the length and width of the two arms are studied. The result suggests a possible route to manage heat dissipation in U-shaped graphene based nanoelectronic devices. PACS numbers: 44.10.+i, 65.80.Ck, 62.23.Kn Graphene, a single layer of carbon atoms arranged in a honeycomb lattice, has attracted much interest due to its extraordinary properties [1,2]. Since graphene exhibits much greater electron mobility than silicon as a zero band gap semiconductor, it has been considered as a promising candidate for the post-CMOS (complementary metal-oxide-semiconductor) material to replace silicon which is approaching its fundamental limit [3]. As electronic devices would undergo dramatic miniaturization, thus heat dissipation has become one of the most important barriers of breaking through. To achieve better functionality and longer lifetime for nanoelectronic devices, it is desirable to have in-depth understanding of the thermal properties of graphene which stimulates intense efforts both experimentally [4][5][6] and theoretically [7,8]. To design a nanoelectronic device with better heat dissipation capacity, one of the most challenging issues is to design thermal rectifiers. Thermal rectification is a phenomenon that the heat flux runs preferentially in one direction and inferiorly in the opposite direction [9,10]. Thus realization thermal rectification in graphene has deep implication for graphene based devices. Through molecular dynamics simulations, researchers have proposed several different thermal rectifiers from the asymmetric graphene nanoribbons [11][12][13][14]. In nanoelectronic designs, U-shaped devices are very common and widely used as electronic transistors and logic gates. Very recently it is found that the U-shaped graphene flakes reveal extremely high Ion/Ioff ratio as channel transistors in experiments and they can easily realize and control the resonant tunneling without any external gates [15,16]. The U-shaped graphene flakes can be fabricated by using lithography or gallium focused ion beam to cut from continuous graphene sheets [15,16]. Therefore it arouses great interest to design thermal rectifiers by U-shaped graphene flakes.Here we study the thermal rectification in asymmetric Ushaped graphene flakes by NEMD (nonequilibrium molecular dynamics) simulations. The graphene flakes are composed by a beam and two arms. We report that higher thermal conductivity is obtained when the heat flux runs from the wide arm to the narrow arm. We also discuss the impacts of the heat flux, the length and the width of the beam, the length and width of the two arms on the rectification...

Adsorbed water molecules on an ionic surface may exhibit an ordered monolayer on the surface. The ordered structure gives it many unique properties that are distinct from either liquid water or ice. We use molecular dynamics simulations to investigate the thermal properties of monolayer water, and find that its thermal conductivity is more similar to ice than to liquid water. The dependence of the thermal conductivity on the charge on the substrate and the temperature are studied. This study explores the density distribution of the water molecules to explain the dependence relations, and examines the effect of bulk water on the structure and thermal properties of monolayer water. Furthermore, kinetic energy transportation in monolayer water is studied.

In this paper we demonstrate the direct evidence of solitons in graphene by means of molecular dynamics simulations and mathematical analysis. It shows various solitons emerge in the graphene flakes with two different chiralities by cooling procedures. They are in-plane longitudinal and transverse solitons. Their propagations and collisions are studied in details. A soliton solution is derived by making several valid simplifications. We hope it shed light on understanding the unusual thermal properties of graphene.

Using nonequilibrium molecular dynamics simulations, we study the heat conduction in graphene flakes composed by two regions. One region is mass-loaded and the other one is intact. It is found that the mass interface between the two regions greatly decreases the thermal conductivity, but it would not bring thermal rectification effect. The dependence of thermal conductivity upon the heat flux and the mass difference ratio are studied to confirm the generality of the result. The interfacial scattering of solitons is studied to explain the absence of rectification effect.PACS numbers: 65.80. Ck, 44.10.+i, 05.45.Yv Thermal rectification is a phenomenon that the heat flux runs preferentially along one direction and inferiorly along the opposite direction [1][2][3][4][5][6][7][8][9][10][11][12][13][14]. It has attracted a great deal of attention in the last decade since it reveals the possibility to control the heat transportation process. With an improved understanding of thermal rectification, various devices like thermal transistors, thermal logic circuits and thermal diodes could be fabricated. Two methods are commonly used to design thermal rectifiers. The first method is to couple two or more anharmonic chains with different nonlinear potentials together [3][4][5]. The explanation for the observed rectification effect is that the phonon bands of different regions of the chain will change from overlap to separation when the heat flux is reversed. The asymmetry of interaction potential controls the phonon band shift and it plays the central role here. The second method is to implement asymmetric geometric shape in quasi-1D and 2D systems. For example, it is applied in deformed carbon nanotubes [6], carbon nanohorns [7], triangle shaped, trapezoid shaped and U-shaped graphene flakes [8][9][10]. Thermal conductivity is higher when the heat flux runs from the narrow to the wide region. The explanation for the observed rectification is that the asymmetric geometric shape introduces asymmetric boundary scattering of phonons. The asymmetry of geometric shape controls the phonon scattering and it plays the central role in this case.

In this paper we introduce a weighted complex networks model to investigate and recognize structures of patterns. The regular treating in pattern recognition models is to describe each pattern as a high-dimensional vector which however is insufficient to express the structural information. Thus, a number of methods are developed to extract the structural information, such as different feature extraction algorithms used in preprocessing steps, or the local receptive fields in convolutional networks. In our model, each pattern is attributed to a weighted complex network, whose topology represents the structure of that pattern. Based upon the training samples, we get several prototypal complex networks which could stand for the general structural characteristics of patterns in different categories. We use these prototypal networks to recognize the unknown patterns. It is an attempt to use complex networks in pattern recognition, and our result shows the potential for real-world pattern recognition. A spatial parameter is introduced to get the optimal recognition accuracy, and it remains constant insensitive to the amount of training samples. We have discussed the interesting properties of the prototypal networks. An approximate linear relation is found between the strength and color of vertexes, in which we could compare the structural difference between each category. We have visualized these prototypal networks to show that their topology indeed represents the common characteristics of patterns. We have also shown that the asymmetric strength distribution in these prototypal networks brings high robustness for recognition. Our study may cast a light on understanding the mechanism of the biologic neuronal systems in object recognition as well. In spatial cognition of biologic neuronal systems, an object possesses many properties, such as color, size, brightness, and structures, etc. The main characteristic of an object is represented by its structures which is the primary reason to classify one object from other objects. The structure of an object is expressed as the description of the spatial arrangements and correlations among its individual parts ͓1-3͔. It has been hypothesized that the aim of cortical information processing is to transform the highly redundant inputs into a higher-order representation which reveals the structure ͓4,5͔.In the usual pattern recognition models, such as artificial neural networks ͓6-8͔, each pattern is attributed to a high dimensional vector which is often constructed by a row-byrow scan in the pixel box. Such expression is insufficient in expressing the structural information of each pattern, since the arrangements and correlations between the pixel points is not manifested in the vector. The synaptic matrix treats the computation of each dimension separately, and the spatial arrangements take no effect in computation. Thus, in order to overcome such shortcoming, a number of different methods are developed to extract the structural information within the raw inputs, such as featu...