Considering the SU(2) Yang-Mills theory in a 4-dimensional Einstein Gravity, we find a black brane solution in the AdS space. For this setup, by using the AdS/CFT holography, we find non-Abelian color CONDUCTIVITY of the gauge theory on the boundary of the AdS space. Color CONDUCTIVITY is defined by the generalized Ohm’ s law and computed by applying holography to the linear response theory.

Surface properties of cellulosic fibers can be modified by Layer-by-Layer (LbL) technique. Different factors influence the performance of LbL technique. The properties of pulp fiber suspension i.e., CONDUCTIVITY of the fiber suspension are of such factors, affect the results of the LbL process. In this study, the physical and mechanical properties of handsheet with basis weight of 60g/m2, made from LbL-treated recycled OCC fibers at various salt concentrations with biopolymers cationic and anionic starches evaluated. The results showed that apparent density and formation quality of handsheets made of LbL-treated recycled fibers were improved significantly, while there was no obvious change for paper roughness. Bonding ability indexes including tensile index and Scott bond were also increased significantly. Moreover, the variation of CONDUCTIVITY showed a dual effect on the electrochemical properties of OCC fiber surface and starch absorption. The salt concentration of 0.001M NaCl with 140mS/cm CONDUCTIVITY was the optimum condition for layering.

Most of the energy loss in a building is through the walls. For this reason, insulating materials are used to reduce the loss of energy in buildings. Common insulations are high thickness thermally resistant material while thin coatings are usually used less. The purpose of this research was to introduce nanocomposite thin polymer coatings and their effects on thermal CONDUCTIVITY. In order to prepare the insulating layers with nanocomposite coatings, chemically modified nano zirconium and aluminum oxides in three different weight percentages (1, 3, and 5%) were used in polyurethane matrix. To study thermal CONDUCTIVITY, the metallic plates were coated with the prepared nanocomposites, and the thermal CONDUCTIVITY of the samples was measured. The results showed that adding zirconium oxide and aluminum oxide nanoparticles in the polyurethane matrix increases the thermal resistance of the plates in all three weight percentages, compared to the coating with no nanoparticles. The lowest thermal CONDUCTIVITY was found for 5% nano aluminum oxide composition, which compared to the CONDUCTIVITY of the pure polyurethane resin decreases about 40%.

The purpose of this study was to investigate the effect of silver and copper nanoclouids on the thermal CONDUCTIVITY of particleboard. For this purpose, nanoclouids with concentration of 4000 (ppm) in four levels of 0, 5, 10 and 15% were applied to the particleboards with the consumed resin, then thermal CONDUCTIVITY of the boards were measured at four temperature profiles (45, 50, 55 and 60 oC). The results showed that with increasing nanoclouids content, the thermal CONDUCTIVITY increased, and the samples containing silver nanoclouids indicate higher thermal CONDUCTIVITY than the samples containing copper nanoclouids at the same conditions. With increasing temperature, thermal CONDUCTIVITY of the boards increased. The increased of thermal CONDUCTIVITY of compact wooden plates was as a positive factor in production process in terms of cost reducing and increase efficiency of the products.

A Polyaniline/Manganese dioxide (PANI/MnO2) nanocomposite contains five weight percentages of MnO2. It has been successfully prepared by in situ polymerization. The structural, optical, and CONDUCTIVITY of nanocomposites remain relative to changes with respect to the weight percentage of MnO2. The structural, morphological, optical, and electrical CONDUCTIVITY investigation of pure MnO2, pure PANI, and nanocomposites were done with powder XRD, HRTEM, SEM, FT-IR, UV and Impedance spectra. XRD results of the PANI/ MnO2 nanocomposites say that the crystalline structure is converted into a very less crystalline structure due to the incorporation of MnO2 which is inside PANI chain. The HRTEM and SEM images are confirmed to the nanocomposite formation, morphology studies and also supported to the XRD results. From the optical spectra, MnO2 nanoparticles have been impressed in the surface of PANI. It works as the compensator in the formation of nanocomposites. UV spectral analysis reveals that the absorption of MnO2 modifies the absorption wavelength of under visible light in whole range. The absorption wavelength of nanocomposites is 288 nm and 337 nm. AC electrical CONDUCTIVITY of the prepared nanocomposites from impedance spectroscopy was carried out and compared with pure materials. The AC CONDUCTIVITY of as-prepared nanocomposites has been analyzed in the range of 298 K to 423 K. The AC CONDUCTIVITY of nanocomposites varies depending upon a change of logarithmic frequency.

In harsh climates, utilizing thermal insulation in the building envelope can substantially reduce the building thermal load and consequently its energy consumption. The performance of the thermal insulation material is mainly determined by its effective thermal CONDUCTIVITY, which is dependent on the material’s density, porosity, moisture content, and mean temperature difference. The effective thermal CONDUCTIVITY of insulation materials increases with increasing temperature and moisture content. Hence, thermal losses may become higher than the design values. The availability of measured data of the thermal CONDUCTIVITY of insulations at higher temperatures and at elevated moisture contents is poor. In this article the Artificial Neural Networks (ANN) is utilized in order to predict the effective thermal CONDUCTIVITY of expanded polystyrene with specific temperature and moisture content. The experimental data was used for training and testing ANN. Obtained results from the ANN method give a good agreement with experimental data.

The study of heat transfer in porous media has many applications in industry. In this work, heat transfer between an inert gas and a semi infinite porous media based on Singular Perturbation method and with using of Laplace Transform, has been studied. To solve this problem with this approach, the thermal CONDUCTIVITY is assumed to be small. Also, the solution is expressed in both inner and outer layer. For matching these two layers a matching method is suggested. This approach shows a good accuracy for small values of parameter, small thermal CONDUCTIVITY. One time the problem is solved by using the third kind boundary condition on the wall and one time this boundary condition is changed into first kind and then has been considered in problem. With comparing between this solution and the solution of using boundary condition of third kind shows the good accuracy of this approach, except near the wall that there occurred small differences between these two solutions. This idea can be used as a useful method in simplifying the analysis of the issues. But in cases that the good accuracy of solution or slop changes with high precision is important, this procedure may be caused approximate results.

Thermal CONDUCTIVITY of rocks for accurate estimation of geothermal heat flux is important. Here we introduce the design and construction of a newly built system based on the principle of steady state heat conduction using divided bars method. The system is computer controlled and has been calibrated using standard quartz samples. Typical error in the system is about one percent which is mainly due to the way the sample is positioned in the system. For proper positioning, one must use a conductive greace to generate good contacts between the sample and the rods. Measurements of a few rock samples from Iran, give thermal conductivities which are within the reported values by others. The geothermal heat flux based on these measurements and the geothermal gradients from different parts of Iran, show that its mean value varies between 45 and 70 mW/m2, for these regions. Variations in geothermal gradient along the depth of same wells may also indicate the variations in rock with different thermal conductivities.

In this paper, thermal CONDUCTIVITY of porous media has been modeled based on mathematical analysis in one dimensional space with micro size. First, porous modeling established on three kinds of porosity (Y = 0.52, 0.68 and 0.74) and then to make analysis and calculation easy, reality assumptions were considered. With omitted radiation and convection mechanisms, we can developed one simple model as kP = kgks / (ks - Y (ks - kg)). After developing the model its results for three materials cotton, fiber and sand obtained and then compared to the experimental data and the results of Maxwell model as a valid model. The results obtained for two modes of material into the holes once air and once again water. The results obtained from the model for gas fluid (air) into the holes with great accuracy. Generally, based on the terms of model, in porous media accuracy of the model was increased when the ratio of (ks / kg) was increased. At the other hand, if the bulk has much CONDUCTIVITY or the fluid into the hole has low CONDUCTIVITY, the prediction of model and its adaptation on heat behavior of the body will be better. So the uses of this model were recommended for dense porous materials.

We report the synthesized and preparation of graphene oxide (GO) nanocomposite functionalized with polyvinyl alcohol (PVA) with different concentration of graphene oxide 0, 1, 1.5, 2, 2.5, 3, 3.5 and 4% weight. This synthesized confirmed by FT-IR. The electrical CONDUCTIVITY of the all nanocomposite was measured at 25oC for all samples and the resulted showed electrical CONDUCTIVITY was increased with increasing % weight graphene in nanocomposite.