. a) The 100 ml + weight's water level; b) the foam glass and the weight in 100 ml of water 2.3.2 Thermal conductivity The thermal conductivity of each specimen was measured at room temperature by using a C-Therm TCi laboratory instrument. Each
]. J. Chiu P. G. Fair 1979 Determination of thermal conductivity by differential scanning calorimetry Thermochimica Acta
Since the late 1990’s, research has been reported where intercalated, expanded, and/or exfoliated graphite nanoflakes could also be used as reinforcements in polymer systems. The key point to utilizing graphite as a platelet nanoreinforcement is in the ability to exfoliate graphite using Graphite Intercalated Compounds (GICs). Natural graphite is still abundant and its cost is quite low compared to the other nano–size carbon materials, the cost of producing graphite nanoplatelets is expected to be ~$5/lb. This is significantly less expensive than single wall nanotubes (SWNT) (>$45000/lb) or vapor grown carbon fiber (VGCF) ($40–50/lb), yet the mechanical, electrical, and thermal properties of crystalline graphite flakes are comparable to those of SWNT and VGCF. The use of exfoliated graphite flakes (xGnP) opens up many new applications where electromagnetic shielding, high thermal conductivity, gas barrier resistance or low flammability are required. A special thermal treatment was developed to exfoliate graphite flakes for the production of nylon and high density polypropylene nanocomposites. X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were used to assess the degree of exfoliation of the graphite platelets and the morphology of the nanocomposites. The thermal conductivity of these composites was investigated by three different methods, namely, by DSC, modified hot wire, and halogen flash lamp methods. The addition of small amounts of exfoliated graphite flakes showed a marked improvement in thermal and electrical conductivity of the composites.
Thermal diffusivity is the speed with which heat propagates through a material. It has a multitude of direct applications, such as determining heat transfer through brake pads at the moment of contact, etc., but more often it is used to derive thermal conductivity from the fundamental relationship tying it with specific heat capacity and density. Using a new multi-sample configuration system, and testing a reference sample adjacent to the unknown, specific heat capacity can be obtained parallel with thermal diffusivity. Thus, a single test yields thermal diffusivity and thermal conductivity with prior knowledge of density. The method is fast and produces results with high accuracy and very good repeatability. The sample size, 12 to 30 mm diameter and 2 to 5 mm thickness, is easy to handle and is well suited for a broad range of materials, even for composites, often a problem for other methods. Typical data on two polymers, Pyrex glass and Pyroceram 9606 are presented.
The thermal conductivity of polyolefins and halogen-substituted polymers was studied in a broad temperature interval spanning both solid and melt states, in the range of pressures from 0.1 up to 100 MPa with the aid of a high-pressureλ-calorimeter in the continuous heating regime. Treatment of data on the pressure dependence of the thermal conductivity of melts in terms of Barker's equation yielded the values of ‘quasilattice’ Grueneisen parameter γB which exhibited the same dependence on molecular structure of a polymer as the parameter 3C/p from the Simha-Somcynsky equation of state (number of external degress of freedom per chain repeat unit). Analysis of the dependence of the thermal conductivity of polyethylene on the degree of crystallinity revealed the inadequacy of the current two-phase model which does not account for the microheterogeneity of the ‘amorphous phase’. It was concluded that interchain heat transfer makes the dominant contribution to the thermal conductivity of polymers both in amorphous and in crystalline states.
One of the benefits of temperature-modulated DSC (TMDSC) is its ability to measure thermal conductivity and thermal diffusivity without DSC cell modifications or additional accessories. Thermal conductivity of solid materials from 0.1 to about 1 W m-1 K-1 measured. Applications of this approach have been discussed in the literature but no description is yet available concerning the derivation of the working equations. This presentation provides a detailed derivation of the working equations used to obtain thermal conductivity and thermal diffusivity from TMDSC data.
Various techniques and methodologies of thermal conductivity measurement have been based on the determination of the rate of directional heat flow through a material having a unit temperature differential between its opposing faces. The constancy of the rate depends on the material density, its thermal resistance and the heat flow path itself. The last of these variables contributes most significantly to the true value of steady-state axial and radial heat dissipation depending on the magnitude of transient thermal diffusivity along these directions. The transient hot-wire technique is broadly used for absolute measurements of the thermal conductivity of fluids. Refinement of this method has resulted in a capability for accurate and simultaneous measurement of both thermal conductivity and thermal diffusivity together with the determination of the specific heat. However, these measurements, especially those for the thermal diffusivity, may be significantly influenced by fluid radiation. Recently developed corrections have been used to examine this assumption and rectify the influence of even weak fluid radiation. A thermal conductivity cell for measurement of the thermal properties of electrically conducting fluids has been developed and discussed.
This paper presents a model for evaluation of effective thermal conductivity for the composites with carbon nanotubes (CNT) having log-normal function of distribution of CNT, with direct effect over depolarization factor. The CNT are considered having cylindrical shape with L/d ratio very high. The model parameters are calculated in function of the data from literature. The influence of volume fraction of reinforced materials, of the aspect ratio of the particles included and of the ratio of the two thermal conductivities is presented.
Thermal conductivity is an important parameter in the field of nanofluid heat transfer. This article presents a novel model for the prediction of the effective thermal conductivity of nanofluids based on dimensionless groups. The model expresses the thermal conductivity of a nanofluid as a function of the thermal conductivity of the solid and liquid, their volume fractions, particle size and interfacial shell properties. According to this model, thermal conductivity changes nonlinearly with nanoparticle loading. The results are in good agreement with the experimental data of alumina-water and alumina-ethylene glycol based nanofluids.
Introduction Thermal conductivity is a property that characterizes the ability of a material to transmit heat and is a macroscopic representation of all the molecular effects that contribute to the conduction of heat through it