In this paper, a new model for estimation of the electrical conductivity of polymer carbon nanotube (CNT) nanocomposites based on the conventional power-law model and Halpin-Tsai formulation has been proposed. Halpin-Tsai model was originally presented to calculate the tensile modulus of composites, which can be modified for estimation of the electrical conductivity by replacing the electrical parameters. The nature of “b” exponent in power-law model is defined according to CNT dimensions, CNT electrical conductivity and the interphase thickness and also the impacts of these parameters on the “b” and the electrical conductivity of nanocomposite are taken into consideration. The developed model interprets that the electrical conductivity of polymer-CNT nanocomposite increases as the concentration, length and electrical conductivity of CNT and the interphase thickness increase. Furthermore, reduction in CNT diameter and waviness results in growth of nanocomposite electrical conductivity. In order to validate the developed model, nanocomposite samples with different volume fractions were produced by solid-state technique of the melt-blending method. The results of calculations and experimental procedure show good agreement.

Dhenedar, Hashtbandi Floodwater Spreading plan of about 450 hectares, is located in the southeast Hormozgan. Measuring the electrical conductivity of the affected wells is one of the most important indicators of the effect of artificial recharge schemes. The maps of the electrical conductivity were prepared using the Surfer software. To determine the effect Floodwater spreading of Aquifer , wells that were near floodwater spreading with potholes farther away than were floodwater spreading (control wells) were compared. Compare the electrical conductivity of the wells showed that the total electrical conductivity increased, but its rate of floodwater spreading area by far less than other locations. Therefore, the electrical conductivity dropped in the well No. 5, which is located near the flood spreading area from 800 to 716 μm/cm, respectively before and after the construction of flood spreading system. But that is well No. 11 at the end of the plain and farther distance than floodwater spreading systems, electrical conductivity increased from 710 to 786 micromhos per centimeter.

There is many ways to assessing the electrical conductivity anisotropy of a tumor. Applying the values of tissue electrical conductivity anisotropy is crucial in numerical modeling of the electric and thermal field distribution in electroporation treatments. This study aims to calculate the tissues electrical conductivity anisotropy in patients with sarcoma tumors using diffusion tensor imaging technique.
A total of 3 subjects were involved in this study. All of patients had clinically apparent sarcoma tumors at the extremities. The T1, T2 and DTI images were performed using a 3-Tesla multi-coil, multi-channel MRI system. The fractional anisotropy (FA) maps were performed using the FSL (FMRI software library) software regarding the DTI images. The 3D matrix of the FA maps of each area (tumor, normal soft tissue and bone/s) was reconstructed and the anisotropy matrix was calculated regarding to the FA values.
The mean FA values in direction of main axis in sarcoma tumors were ranged between 0.475–0.690. With assumption of isotropy of the electrical conductivity, the FA value of electrical conductivity at each X, Y and Z coordinate axes would be equal to 0.577. The gathered results showed that there is a mean error band of 20% in electrical conductivity, if the electrical conductivity anisotropy not concluded at the calculations. The comparison of FA values showed that there is a significant statistical difference between the mean FA value of tumor and normal soft tissues (P DTI is a feasible technique for the assessment of electrical conductivity anisotropy of tissues. It is crucial to quantify the electrical conductivity anisotropy data of tissues for numerical modeling of electroporation treatments.

Bipolar plates are one of the most important components in a PEM fuel cell. In this study, a bipolar plate made of stamping method is developed to increase electrical conductivity and mechanical behavior and manufacturing productivity of the fuel cell and to decrease electrical resistance according to DOE. For fabrication these plates, phenolic resins were used as matrix and expanded graphite to increase electrical conductivity and graphite to filler and carbon fiber to increase flexural strength and optimize electrical conductivity. The electrical conductivity increased up to 40 percent respect to the DOE. The flexural strength and impact strength of the measured specimens were improved respect to the DOE about 11 and 170 percent, respectively. The experimental results are in accordance with DOE. According to SEM images and test curves, electric conductivity increases with expanded graphite filler. Finally, the results showed that expanded graphite weight gain did not affect the mechanical behavior of the composite and increased the electrical conductivity.

This study was designed to experimentally measure the thermal and electrical conductivities of Aluminium Nitride/Ethylene Glycol (AlN/EG) nanofluids. Transmission electron microscopy (TEM) was used to characterize the shape of AlN nanoparticles. Nanofluids with different particle volume concentrations of 0.5%, 1%, 2%, 3%, 4%, and 5% were utilized. The thermal and electrical conductivities of the nanofluids were measured using a KD2-Pro thermal analyser and electrical conductivity meter, respectively. The obtained results revealed that the thermal conductivity of the nanofluids increased at the higher volume concentration of the nanoparticles. Thus, at 5% volume concentration, the maximum thermal conductivity enhancement of 25% was obtained. The addition of AlN nanoparticles to the EG base fluid resulted in a significant increase in the electrical conductivity of the nanofluid. An enhancement in the electrical conductivity of approximately 520 times relative to the base fluid was attained by loading a 0.5% volume concentration of AlN in EG at 28°C.

The nylon and nylon/lycra yarns were coated with electrically conductive polymers such as polyaniline and polypyrrole, via chemical polymerization process. Electrical conductivity of the coated yarns was measured at various strain levels using two-point probe technique and their strain sensitivities were studied. The results showed that, electrical conductivity of the coated yarns decreased with an increase in strain level. A sharp decrease in the electrical conductivity of the nylon/lycra coated yarn with the strain level was recorded whereas, a small drop in the electrical conductivity of the nylon coated yarn was observed. Linear relationships were found between the electrical conductivity and length for the nylon and nylon/lycra coated yarns. The polyaniline coated yarns showed higher strain sensitivity compared to polypyrrole coated yarns. Repeatability of the strain sensitivity of the coated yarns was examined and the coated nylon/lycra yarn showed better repeatability compared to that of coated nylon yarn. The coated yarns were proposed as a flexible strain sensor in the field of intelligent materials.

An empirical electrical conductivity assessment of nanofluids comprising CuO nanoparticles water-based in different concentrations, particles size and various temperatures of nanofluids has been carried out in this paper. These experimentations have been done in deionized water with nanoparticles sizes such as 89, 95, 100 and 112 nm and concentrations of 0.12 g/l, 0.14 g/l, 0.16 g/l and 0.18 g/l so nanofluids obtain in temperatures such as 25oC, 35oC, 45oC and 50oC for investigation of their electrical conductivity. It is observed that, in water-based nanofluids, the electrical conductivity increases with increasing in both nanofluids temperatures and concentration respectively in the range 25–50oC and 0.12-0.18g/l. But in nanoparticles size rising in nanofluids we observe that electrical conductivity has a few increase when nanoparticles have 95nm diameters, so decrease for biggest nanoparticles such as 100 and 112nm. It seems that there is an optimum in electrical conductivity with resize of nanoparticles.

The object of this research is the investigation of carbon nanotube (CNT) distribution effect on electrical conductivity of polymer-CNT composite as dosimetry response of this system. Thus, electrical conductivity of this composite was simulated for aligned, homogenous, and agglomerated distributions in 2D, and 3D situations. The results of simulation were compared and validated by experimental data in the literature. For 3D distribution of CNTs in polymer matrix, Monte Carlo method and excluded volume approach were utilized. The results of 3D simulation showed that electrical conductivity of polymer-CNT composite was depended on dispersion angle of CNTs in polymer matrix. The results of 2D simulation showed that more agglomeration of CNTs in polymer-CNT composite was leading to sever reduction of electrical conductivity. In the other hand, with transition of agglomeration to homogeneous dispersion of CNTs into polymer matrix, increasing of electrical conductivity of the composite was observed.

We address the electronic properties of armchair graphene nanoribbon within tight binding model Hamiltonian. Specially we have investigated the behavior of density of states and electrical conductivity. The possible gap parameter eff ects, ribbon width and chemical potential on electrical conductivity are investigated. Us-
ing Green's function calculate the electrical conductivity and density of states of the system have been calculated. Based on the results, the band gap in density of states increases with gap parameter and decreases with ribbon width. The dependence of the electrical conductivity on temperature for various ribbon widths and chemical potentials has been found. Our results show a peak appears in temperature de-pendence of electrical conductivity for each value of chemical potential and ribbon width.

Electric field intensity at each point is responsible for pore creation in the cell membrane during the electroporation process. These pores can increase the tissue electrical conductivity in the electroporation. Changes in electrical conductivity through the electroporation is a useful factor for imaging and tracking of electroporation inside the body. Electrical conductivity is set to become a vital factor for accurate estimation of the electric field and cell kill probability distribution in the course of electroporation for treatment planning purposes. Therefore, for more accurate treatment, tissue electrical conductivity changes due to electroporation should be considered in the treatment planning system. This paper describes the advantages of tissue electrical conductivity as a useful factor in the clinic.