Particle laden polymers are one of the most prominent thermal interface materials (TIM) used in electronics cooling. Most of the research has primarily dealt with the understanding of the thermal conductivity of these types of TIMs. For thermal design, reduction of the thermal resistance is the end goal. Thermal resistance is not only dependent on the thermal conductivity, but also on the bond line thickness (BLT) of these TIMs. It is not clear which material property(s) of these particle laden TIMs affects the BLT and eventually the thermal resistance. This paper introduces a rheology based semiempirical model for the prediction of the BLT of these TIMs. BLT depends on the yield stress of the particle laden polymer and the applied pressure. The BLT model combined with the thermal conductivity model can be used for modeling the thermal resistance of these TIMs for factors such as particle volume faction, particle shape, base polymer viscosity, etc. This paper shows that there exists an optimal filler volume fraction at which thermal resistance is minimum. Finally this paper develops design rules for the optimization of thermal resistance for particle laden TIMs.
The performance of seven expert, seven intermediate, and 15 novice snooker players was compared on a range of general visual tests and sport-specific perceptual and cognitive tests in an attempt to determine the locus of the expert advantage. No significant expert-novice differences were apparent on standard optometric tests of acuity, ocular muscle balance, colour vision, and depth perception, nor on the relative frequency of unilateral and cross-lateral eye-hand dominances. Experts, however, were found to be superior in their ability to both recall and recognize rapidly-presented slides depicting normal game situations, but were no better than novices in recalling information from slides in which the balls were arranged randomly on the table. The expert group's superiority on the perceptual recall and recognition tasks was consistent with a deeper level of encoding for structured (meaningful) material. Experts were also shown, through the use of thinking-aloud and evaluation paradigms, to use a greater depth of forward planning in choosing appropriate shot options and to evaluate existing situations with greater accuracy, discriminability, and prospective planning than did novices. The cognitive advantage is shown to be a potential contributor but not a total explanation of the superior performance of the experts on the perceptual tasks. The findings of this study are consistent with existing works on expertise in board games and 'open' skill sports in indicating that the expert's advantage is not a general but a specific one, arising not from physical capacities but from acquired processing strategies.The past decade has seen a growing interest in the study of expert-novice differences in sports tasks as a window for understanding the acquisition of skill. Knowing what essential attributes distinguish the expert from the lesser skilled performer in natural activities provides a principled basis for determining what types of practice are most likely to be beneficial for enhancing the development of expertise.To date, the majority of studies of sport expertise have implicitly adopted an information-processing model of human performance, measuring elements of
This paper reports the measurement of the thermal conductivity of particle-laden polymeric thermal interface materials for three different particle volume fractions. The experimental data are further compared with the percolation model and effective medium theory. We then introduce a method of obtaining the contact resistance between the particles and the polymeric matrix by a combination of percolation modeling and experimental data. We also discuss the dependence of the mechanical response of these particle-laden polymers for different filler or particle loading. A novel mechanical length scale is defined to understand the mechanical response of these materials, and is correlated to the viscosity of these materials.
Particle laden polymers are one of the most prominent thermal interface materials (TIM) used in electronics cooling. Most of the research has primarily dealt with the understanding of the thermal conductivity of these types of TIMs. For thermal design, reduction of the thermal resistance is the end goal. Thermal resistance is not only dependent on the thermal conductivity, but also on the bond line thickness (BLT) of these TIMs. It is not clear which material property(s) of these particle laden TIMs affects the BLT and eventually the thermal resistance. This paper introduces a rheology based semi-empirical model for the prediction of the BLT of these TIMs. BLT depends on the yield stress of the particle laden polymer and the applied pressure. The BLT model combined with the thermal conductivity model can be used for modeling the thermal resistance of these TIMs for factors such as particle volume faction, particle shape, base polymer viscosity, etc. This paper shows that there exists an optimal filler volume fraction at which thermal resistance is minimum. Finally this paper develops design rules for the optimization of thermal resistance for particle laden TIMs.
Currently there are no models to predict the thickness or the bondline thickness (BLT) of particle laden polymeric thermal interface materials (TIM) for parameters such as particle volume fraction and pressure. TIMs are used to reduce the thermal resistance. Typically this is achieved by increasing the thermal conductivity of these TIMs by increasing the particle volume fraction, however increasing the particle volume fraction also increases the BLT. Therefore, increasing the particle volume fraction may lead to an increase in the thermal resistance after certain volume fraction. This paper introduces a model for the prediction of the BLT of these particle laden TIMs. Currently thermal conductivity is the only metric for differentiating one TIM formulation from another. The model developed in this paper introduces another metric: the yield stress of these TIMs. Thermal conductivity and the yield stress together constitute the complete set of material parameters needed to define the thermal performance of particle laden TIMs.
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