Predicting Thermal Characteristics of Particle Laden Thermal Interface Materials

Author(s):  
Reza H. Khiabani ◽  
Yogendra Joshi ◽  
Cyrus Aidun

Particle laden Thermal Interface Materials (TIMs) are used extensively in thermal packaging of electronic components to enhance the heat transfer between heat dissipating components and the thermal management layers. In this paper, the thermal performance of particle laden TIMs is studied numerically, using the Lattice Boltzmann method. The effect of particle volume fraction, particle size and the thermal conductivity ratio on the thermal performance of particle laden TIMs are examined. The results for the effective thermal conductivity of particle laden greases are in agreement with the existing analytical and experimental results reported in the literature.

Author(s):  
Ravi S. Prasher ◽  
Jim Shipley ◽  
Suzana Prstic ◽  
Paul Koning ◽  
Jin-Lin Wang

Particle laden polymers are one of the most prominent thermal interface materials (TIM) used in electronics cooling. Most of the research groups have primarily dealt with the understanding of the thermal conductivity of these types of TIMs. 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 that which material property(s) of these particle laden TIMs affects the BLT. This paper discusses the experimental measurement of rheological parameters such as non-Newtonian strain rate dependent viscosity and yield stress for 3 different particle volume fraction and 3 different base polymer viscosity materials. These rheological and BLT measurements vs. pressure will be used to model the BLT of particle-laden systems for factors such as volume fraction.


Author(s):  
Ravi S. Prasher ◽  
Jim Shipley ◽  
Suzana Prstic ◽  
Paul Koning ◽  
Jin-Lin Wang

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.


Author(s):  
X. Zhang ◽  
S. Kanuparthi ◽  
G. Subbarayan ◽  
B. Sammakia ◽  
S. Tonapi

Particle laden polymer composites are widely used as thermal interface materials in the electronics cooling industry. The projected small chip-sizes and high power applications in the near future demand higher values of effective thermal conductivity of the thermal interface materials (TIMs) used between the chip and the heat-spreader and the heat-spreader and heat-sink. However, over two decades of research has not yielded materials with significantly improved effective thermal conductivities. A critical need in developing these TIMs is apriori modeling using fundamental physical principles to predict the effect of particle volume fraction and arrangements on effective behavior. Such a model will enable one to optimize the structure and arrangement of the material. The existing analytical descriptions of thermal transport in particulate systems under predict (as compared to the experimentally observed values) the effective thermal conductivity since these models do not accurately account for the effect of inter-particle interactions, especially when particle volume fractions approach the percolation limits of approximately 60%. Most existing theories are observed to be accurate when filler material volume fractions are less than 30–35%. In this paper, we present a hierarchical, meshless, computational procedure for creating complex microstructures, explicitly analyzing their effective thermal behavior, and mathematically optimizing particle sizes and arrangements. A newly developed object-oriented symbolic, java language framework termed jNURBS implementing the developed procedure is used to generate and analyze representative random microstructures of the TIMs.


Author(s):  
Ravi S. Prasher ◽  
Jim Shipley ◽  
Suzana Prstic ◽  
Paul Koning ◽  
Jin-Lin Wang

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.


Author(s):  
Vadim Gektin ◽  
Sai Ankireddi ◽  
Jim Jones ◽  
Stan Pecavar ◽  
Paul Hundt

Thermal Interface Materials (TIMs) are used as thermally conducting media to carry away the heat dissipated by an energy source (e.g. active circuitry on a silicon die). Thermal properties of these interface materials, specified on vendor datasheets, are obtained under conditions that rarely, if at all, represent real life environment. As such, they do not accurately portray the material thermal performance during a field operation. Furthermore, a thermal engineer has no a priori knowledge of how large, in addition to the bulk thermal resistance, the interface contact resistances are, and, hence, how much each influences the cooling strategy. In view of these issues, there exists a need for these materials/interfaces to be characterized experimentally through a series of controlled tests before starting on a thermal design. In this study we present one such characterization for a candidate thermal interface material used in an electronic cooling application. In a controlled test environment, package junction-to-case, Rjc, resistance measurements were obtained for various bondline thicknesses (BLTs) of an interface material over a range of die sizes. These measurements were then curve-fitted to obtain numerical models for the measured thermal resistance for a given die size. Based on the BLT and the associated thermal resistance, the bulk thermal conductivity of the TIM and the interface contact resistance were determined, using the approach described in the paper. The results of this study permit sensitivity analyses of BLT and its effect on thermal performance for future applications, and provide the ability to extrapolate the results obtained for the given die size to a different die size. The suggested methodology presents a readily adaptable approach for the characterization of TIMs and interface/contact resistances in the industry.


Author(s):  
Jing Fan ◽  
Liqiu Wang

The recent first-principle model shows a dual-phase-lagging heat conduction in nanofluids at the macroscale. The macroscopic heat-conduction behavior and the thermal conductivity of nanofluids are determined by their molecular physics and microscale physics. We examine numerically effects of particle-fluid thermal conductivity ratio, particle volume fraction, shape, aggregation, and size distribution on macroscale thermal properties for nine types of nanofluids, without considering the interfacial thermal resistance and dynamic processes on particle-fluid interfaces and particle-particle contacting surfaces. The particle radius of gyration and non-dimensional particle-fluid interfacial area in the unit cell are two very important parameters in characterizing the effect of particles’ geometrical structures on thermal conductivity of nanofluids. Nanofluids containing cross-particle networks have conductivity which practically reaches the Hashin-Shtrikman bounds. Moreover, particle aggregation influences the effective thermal conductivity only when the distance between particles is less than the particle dimension. Uniformly-sized particles are desirable for the conductivity enhancement, although to a limited extent.


Author(s):  
Piyas Chowdhury ◽  
Kamal Sikka ◽  
Anuja De Silva ◽  
Indira Seshadri

Thermal interface materials (TIMs), which transmit heat from semiconductor chips, are indispensable in today’s microelectronic devices. Designing superior TIMs for increasingly demanding integration requirements, especially for server-level hardware with high power density chips, remains a particularly coveted yet challenging objective. This is because achieving desired degrees of thermal-mechanical attributes (e.g. high thermal conductivity, low elastic modulus, low viscosity) poses contradictory challenges. For instance, embedding thermally conductive fillers (e.g. metallic particles) into a compliant yet considerably less conductive matrix (e.g. polymer) enhances heat transmission, however at the expense of overall compliance. This leads to extensive trial-and-error based empirical approaches for optimal material design. Specifically, high volume fraction filler loading, role of filler size distribution, mixing of various filler types are some outstanding issues that need further clarification. To that end, we first forward a generic packing algorithm with ability to simulate a variety of filler types and distributions. Secondly, by modeling the physics of heat/force flux, we predict effective thermal conductivity, elastic modulus and viscosity for various packing cases.


Author(s):  
Sukshitha Achar P. L. ◽  
Huanyu Liao ◽  
Ganesh Subbarayan

Abstract As device power density increases, there is a need to dissipate generated heat by increasing particle volume loading in thermal interface materials. In this work, we develop and evaluate algorithms for generating ultrapacked microstructures of particles. Simulated microstructures reported in the literature rarely contain particle volume fractions greater than 60%. However, commercially available thermal greases claim to achieve volume fractions in the range of 60–80%. Therefore, to analyze effectiveness of commercially available particle-filled thermal interface materials, there is a need to develop algorithms capable of generating ultrapacked microstructures. The particle packing problem is initially posed as a nonlinear programming problem (NLP), and formal optimization algorithms are applied to generate microstructures that are maximally packed. Since accuracy of the simulated behavior is dependent on the number of particles in the simulation cell, efficiently simulating large number of particles is imperative. However, the packing simulation is computationally expensive. Therefore, various optimization algorithms are systematically evaluated to assess the computational efficiency as measured by the time to generate the microstructures for a system containing a large number of particles. The evaluated algorithms include the penalty function methods, best-in-class sequential programming method, matrix-less conjugate gradient method as well as the augmented Lagrangian method. In addition, heuristic algorithms are also evaluated to achieve computationally efficient packing. The evaluated heuristic algorithms are mainly based on the Drop-Fall-Shake method, but modified to more effectively simulate the mixing process in commercial planetary mixers. With the developed procedures, Representative Volume Elements (RVE) with volume fraction as high as 74% are demonstrated. The simulated microstructures are analyzed using our previously developed random network model to estimate the effective thermal and mechanical behavior given a particle arrangement.


2011 ◽  
Vol 133 (2) ◽  
Author(s):  
Lin Hu ◽  
William Evans ◽  
Pawel Keblinski

We present a concept for development of high thermal conductivity thermal interface materials (TIMs) via a rapid formation of conductive network. In particular we use molecular dynamics simulations to demonstrate the possibility of a formation of a network of solid nanoparticles in liquid solution and establish wetting and volume fraction conditions required for a rapid formation of such network. Then, we use Monte-Carlo simulations to determine effective thermal conductivity of the solid/liquid composite material. The presence of a percolating network dramatically increases the effective thermal conductivity, as compared to values characterizing dispersed particle structures.


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