An artificial neural networks (ANNs) approach is presented for the prediction of effective thermal conductivity of porous systems filled with different liquids. ANN models are based on feedforward backpropagation network with training functions: LevenbergeMarquardt (LM), conjugate gradient with FletchereReeves updates (CGF), one-step secant (OSS), conjugates gradient with PowelleBeale restarts ...

This paper presents a comprehensive thermal scaling analysis of multilevel interconnects in deep nanometer scale CMOS technologies based on technological, structural, and material data from ITRS ’03 [1]. Numerical simulations have been performed using three-dimensional (3-D) electrothermal finite element methods (FEM), combined with accurate calculations of temperatureand size-dependent Cu resi...

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Composite materials by definition are a combination of two or more materials. Although the idea of combining two or more components to produce materials with controlled properties has been known and used from time immemorial, modern composites were developed only several decades ago and have found by now intensive application in different fields of engineering (Vasiliev&Morozov, 2001). These ma...

In the region of minimum porosity of particulate binary mixtures, heat exchange and permeability were found to be higher than the ones obtained with a mono-size packing built with the same small size particles used in the binary packing. This effect was noticed in the range of the particles size ratio 0.1–1.0. The obtained improvement on thermal performance is related to the increase of effecti...

Theoretical model for predicting effective thermal conductivity (ETC) of metal filled polymer composites has been developed. The concept of averaging the temperature field within different phases has been used. Resistor model has been applied to determine ETC of polymer composites. A parameter estimation technique has been applied to determine the inclination angle θ. An effort has been made to...

Authors reported an effective path to decrease the thermal conductivity while to increase the coefficient of thermal expansion, thus enhancing the thermo-physical properties of the LnMeA11O19-type magnetoplumbite LaMgAl11O19 by simultaneously substituting La(3+), Mg(2+) and Al(3+) ions with large ionic radius Ba(2+), Zn(2+) and Ti(4+), respectively. The mechanism behind the lowered thermal cond...

Mussel-inspired approach was attempted to non-covalently functionalize the surfaces of boron nitride (BN) with self-polymerized dopamine coatings in order to reduce the interfacial thermal barrier and enhance the thermal conductivity of BN-containing composites. Compared to the polypropylene (PP) composites filled with pristine BN at the same filler content, thermal conductivity was much higher...

The gadolinium calcium silicates having the apatite crystal structure can accommodate a wide range of point defects, including oxygen and cation vacancies, as well as anti-site defects, depending on the Gd/Ca ratio. Compositions having only cation or oxygen vacancies were identified and the thermal diffusivity and conductivity were measured up to 1000C. All the compositions, including the stoic...

Introduction: The thermal conductivity of powdered media is characteristically very low in vacuum, and is effectively dependent on many parameters of their constituent particles and packing structure. Understanding of the heat transfer mechanism within powder layers in vacuum and theoretical modeling of their thermal conductivity are of great importance for several scientific and engineering pr...