Thermal conductivity of carbon nanotubes and their polymer nanocomposites: A review

Critical factors that determine the percolation threshold of carbon nanotube (CNT)-reinforced polymer nanocomposites are studied. An improved analytical model is developed based on an interparticle distance concept. Two dispersion parameters are introduced in the model to correctly reflect the different dispersion states of CNTs in the matrix—entangled bundles and well-dispersed individual CNTs. CNT–epoxy nanocomposites with different dispersion states are fabricated from the same constituent materials by employing different processing conditions. The corresponding percolation thresholds of the nanocomposites vary over a wide range, from 0.1 to greater than 1.0 wt %, and these variations are explained in terms of dispersion parameters and aspect ratios of CNTs. Important factors that control the percolation threshold of nanocomposites are identified based on the comparison between modeling data and experimental results.

Correlations between Percolation Threshold, Dispersion State, and Aspect Ratio of Carbon Nanotubes

This article reports on the International Nanofluid Property Benchmark Exercise, or INPBE, in which the thermal conductivity of identical samples of colloidally stable dispersions of nanoparticles or “nanofluids,” was measured by over 30 organizations worldwide, using a variety of experimental approaches, including the transient hot wire method, steady-state methods, and optical methods. The nanofluids tested in the exercise were comprised of aqueous and nonaqueous basefluids, metal and metal oxide particles, near-spherical and elongated particles, at low and high particle concentrations. The data analysis reveals that the data from most organizations lie within a relatively narrow band (±10% or less) about the sample average with only few outliers. The thermal conductivity of the nanofluids was found to increase with particle concentration and aspect ratio, as expected from classical theory. There are (small) systematic differences in the absolute values of the nanofluid thermal conductivity among the various experimental approaches; however, such differences tend to disappear when the data are normalized to the measured thermal conductivity of the basefluid. The effective medium theory developed for dispersed particles by Maxwell in 1881 and recently generalized by Nan et al. [J. Appl. Phys. 81, 6692 (1997)], was found to be in good agreement with the experimental data, suggesting that no anomalous enhancement of thermal conductivity was achieved in the nanofluids tested in this exercise.

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A benchmark study on the thermal conductivity of nanofluids

Sensors and actuators based on carbon nanotubes and their composites: A review

A Benchmark Study on the Thermal Conductivity of Nanofluids

Monte Carlo simulations have been performed, aimed at finding a critical fractional volume (CFV) associated with the onset of percolation for randomly oriented nanotubes (or, indeed, any conductive particles with large aspect ratios) that are randomly dispersed in a low thermo- or electroconductive medium. The nanotubes were treated as capped interpenetrating conductive cylinders (``sticks'') with high (up to 2000) aspect ratio $a$. It has been found that for these aspect ratios the CFV is inversely proportional to $a$ resulting in surprisingly low filler volume loadings, of the order of 0.01%, required to achieve percolation in such systems. By studying fluctuations of the CFV and the density of the percolation clusters, various critical indices of the percolation theory have been calculated including the critical index of conductivity, $t$. For three-dimensional systems it has been found that $t$ decreases substantially with an increase in the aspect ratio. The calculated thermal and electrical conductivity of the nanotube suspensions and composites as functions of the nanotube loading is in good agreement with recent experimental data.

Theoretical and computational studies of carbon nanotube composites and suspensions : Electrical and thermal conductivity

Dopant segregation in a ${\mathrm{Mn}}_{\mathrm{x}}{\mathrm{Ge}}_{1\ensuremath{-}x}$ dilute magnetic semiconductor leads to a remarkable self-assembly of Mn-rich nanocolumns, embedded in a fully compensated Ge matrix. Samples grown at $80\phantom{\rule{0.2em}{0ex}}\ifmmode^\circ\else\textdegree\fi{}\mathrm{C}$ display a giant positive magnetoresistance that correlates directly with the distribution of magnetic impurities. Annealing at $200\phantom{\rule{0.2em}{0ex}}\ifmmode^\circ\else\textdegree\fi{}\mathrm{C}$ increases Mn substitution in the host matrix above the threshold for the insulator-metal transition, while maintaining the columnar morphology, and results in global ferromagnetism with conventional negative magnetoresistance. The qualitative features of magnetism and transport in this nanophase material are thus extremely sensitive to the precise location and distribution of the magnetic dopants.

Dopant segregation and giant magnetoresistance in manganese-doped germanium

Fluctuation Controlled Hopping of Bound Magnetic Polarons in ErAs:GaAs Nanocomposites

A theory of bound magnetic polaron (BMP) hopping, driven by thermodynamic fluctuations of the local magnetization, has been developed. It is based on a two-site model of the BMP. The BMP hopping probability rate was calculated in the framework of the ``golden rule'' approach by using the Ginzburg-Landau effective Hamiltonian method. The theory explains the main features of the hopping resistivity observed in a variety of experiments in dilute magnetic semiconductors and magnetic nanocomposites, namely, (a) the negative giant magnetoresistance, the scale of which is governed by a magnetic polaron localization volume, and (b) the low-magnetic-field positive magnetoresistance which usually precedes the negative magnetoresistance. It is shown that the positive magnetoresistance is a signature of the fluctuation-driven bound magnetic polaron hopping. This effect is related to the vector nature of the magnetic order parameter affected by the presence of the localized-electron spin.

Bound magnetic polaron hopping and giant magnetoresistance in magnetic semiconductors and nanostructures

A reduced dynamical model describing temperature stratification effects driven by natural convection in a liquid hydrogen cryogenic fuel tank has been developed. It accounts for cryogenic propellant loading, storage, and unloading in the conditions of normal, increased, and micro- gravity. The model involves multiple horizontal control volumes in both liquid and ullage spaces. Temperature and velocity boundary layers at the tank walls are taken into account by using correlation relations. Heat exchange involving the tank wall is considered by means of the lumped-parameter method. By employing basic conservation laws, the model takes into consideration the major multi-phase mass and energy exchange processes involved, such as condensation-evaporation of the hydrogen, as well as flows of hydrogen liquid and vapor in the presence of pressurizing helium gas. The model involves a liquid hydrogen feed line and a tank ullage vent valve for pressure control. The temperature stratification effects are investigated, including in the presence of vent valve oscillations. A simulation of temperature stratification effects in a generic cryogenic tank has been implemented in Matlab and results are presented for various tank conditions.

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M. Foygel

Papers

Theoretical and computational studies of carbon nanotube composites and suspensions : Electrical and thermal conductivity

Dopant segregation and giant magnetoresistance in manganese-doped germanium

Fluctuation Controlled Hopping of Bound Magnetic Polarons in ErAs:GaAs Nanocomposites

Bound magnetic polaron hopping and giant magnetoresistance in magnetic semiconductors and nanostructures

Temperature Stratification in a Cryogenic Fuel Tank