Thermal conductivity of carbon nanotubes

As the sizes of electronic and mechanical devices are decreased to the micron and nanometre level, it becomes particularly important to predict the thermal transport properties of the components. Using molecular level theories, such predictions are particularly important for modelling nano-electronic devices where scaling laws may change substantially but it is most difficult to accurately measure the properties. Hence, using the empirical bond order dependent force field, we have studied here the thermal conductivity of nanotubes' dependence on structure, defects and vacancies. The anisotropic character of the thermal conductivity of the graphite crystal is naturally reflected in the carbon nanotubes. We found that the carbon nanotubes have very high thermal conductivity comparable to diamond crystal and in-plane graphite sheet. In addition, nanotube bundles show very similar properties as graphite crystal in which dramatic difference in thermal conductivities along different crystal axis

Studies of fullerenes and carbon nanotubes by an extended bond order potential

We present a novel approach to combine bond order potentials with long-range nonbond interactions. This extended bond order potential consistently takes into account bond terms and nonbond terms. It not only captures the advantages of the bond order potentials (i.e. simulating bond forming and breaking), but also systematically includes the nonbond contributions to energy and forces in studying the structure and dynamics of covalently bonded systems such as graphite, diamond, nanotubes, fullerenes and hydrocarbons, in their crystal and melt forms. Using this modified bond order potential, we studied the structure and thermal properties (including thermal conductivity) of C60 crystal, and the elastic properties and plastic deformation processes of the single-walled and double-walled nanotubes. This extended bond order potential enables us to simulate large deformations of a nanotube under tensile and compressive loads. The basic formulation in this paper is transferable to other bond order potentials and traditional valence force fields

QM(DFT) and MD studies on formation mechanisms of C_(60) fullerenes

One of the most puzzling aspects of fullerenes is how such complicated symmetric molecules are formed from a gas of atomic carbons, namely, the atomistic or chemical mechanisms. Are the atoms added one by one or as molecules (C2, C3)? Is there a critical nucleus beyond which formation proceeds at gas kinetic rates? What determines the balance between forming buckyballs, buckytubes, graphite and soot? The answer to these questions is extremely important in manipulating the systems to achieve particular products. A difficulty in current experiments is that the products can only be detected on time scales of microseconds long after many of the important formation steps have been completed. Consequently, it is necessary to use simulations, quantum mechanics and molecular dynamics, to determine these initial states. Experiments serve to provide the boundary conditions that severely limit the possibilities. Using quantum mechanical methods (density functional theory (DFT)) we derived a force field (MSXX FF) to describe one-dimensional (rings) and two-dimensional (fullerene) carbon molecules. Combining DFT with the MSXX FF, we calculated the energetics for the ring fusion spiral zipper (RFSZ) mechanism for formation of C60 fullerenes. Our results shows that the RFSZ mechanism is consistent with the quantum mechanics (with a slight modification for some of the intermediates)

Incremental clustering method based on Gaussian mixture model to identify malware family

Aiming at the logical similarity of the behavioral characteristics of malware belonging to the same family,the characteristics of malware were extracted by tracking the logic rules of API function call from the perspective of behavior detection,and the static analysis and dynamic analysis methods were combined to analyze malicious behavior characteristics.In addition,according to the purpose,inheritance and diversity of the malware family,the transitive closure relationship of the malware family was constructed,and then the incremental clustering method based on Gaussian mixture model was improved to identify the malware family.Experiments show that the proposed method can not only save the storage space of malware detection,but also significantly improve the detection accuracy and recognition efficiency

The 3D Printing of Dielectric Elastomer Films Assisted by Electrostatic Force

ompared with traditional methods for preparing dielectric elastomer (DE) films, electrohydrodynamic (EHD) 3D printing displays many advantages, notably full automation, computer control and flexible design. It also confers high printing resolution, high preparation efficiency with minimal probability of nozzle clogging. In this article, EHD 3D printing was employed to fabricate silicone rubber (SR) based DE films. In order to increase their dielectric constant, high dielectric copper phthalocyanine (CuPc) particles were added into the SR ink. Optimal printing conditions were determined by analyzing the effects of printing voltage and ink properties on the formation of liquid cone and the printed line width. The SR/CuPc composite film with 3 wt% CuPc particles (SR/CuPc-3) exhibits a high dielectric constant of 5.52, with a large actuated area strain of 23.7% under an electric field of 39.4 V μm−1. Furthermore, under 100 cycles of electric field loading, SR/CuPc-3 demonstrate excellent electromechanical stability, indicating that EHD 3D printing holds a considerable potential for fabricating high-performance DE films in an efficacious manner

Simulation and experiments on friction and wear of diamond: a material for MEMS and NEMS application

To date most of the microelectromechanical system (MEMS) devices have been based on silicon. This is due to the technological know-how accumulated on the manipulation, machining and manufacturing of silicon. However, only very few devices involve moving parts. This is because of the rapid wear arising from high friction in these silicon-based systems. Recent tribometric experiments carried out by Gardos on silicon and polycrystalline diamond (PCD) show that this rapid wear is caused by a variety of factors, related both to surface chemistry and cohesive energy density of these likely MEMS bearing materials. In particular, the 1.8-times stronger C-C bond in diamond as opposed to the Si-Si bond in the bulk translates into a more than 104-times difference in wear rates, even though the difference in flexural strength is only 20-times, in hardness 10-times and in fracture toughness 5-times. It also has been shown that the wear rates of silicon and PCD are controlled by high-friction-induced surface cracking, and the friction is controlled by the number of dangling, reconstructed or adsorbate-passivated surface bonds. Therefore, theoretical and tribological characterization of Si and PCD surfaces is essential prior to device fabrication to assure reliable MEMS operation under various atmospheric environments, especially at elevated temperatures. As a part of the rational design and manufacturing of MEMS devices containing moving mechanical assemblies (MEMS-MMA) and especially nanoelectromechanical devices (NEMS), theory and simulation can play an important role. Predicting system properties such as friction and wear, and materials properties such as thermal conductivity is of critical importance for materials and components to be used in MEMS-MMAs. In this paper, we present theoretical studies of friction and wear processes on diamond surfaces using a steady state molecular dynamics method. We studied the atomic friction of the diamond-(100) surface using an extended bond-order-dependent potential for hydrocarbon systems. Unlike traditional empirical potentials, bond order potentials can simulate bond breaking and formation processes. Therefore, it is a natural choice to study surface dynamics under friction and wear. In order to calculate the material properties correctly, we have established a consistent approach to incorporate non-bond interactions into the bond order potentials. We have also developed an easy-to-use software to evaluate the atomic-level friction coefficient for an arbitrary system, and interfaced it into a third-party graphical software