Modeling Heat Conduction Across Thermal Interface Materials With Micro-Particles

2008 ◽  
Author(s):  
C. Channy Wong
Keyword(s):  
Thermal Conductivity ◽  
Heat Conduction ◽  
Composite Materials ◽  
Effective Thermal Conductivity ◽  
Thermal Interface Materials ◽  
Conduction Path ◽  
Micro Particles ◽  
Mechanical And Electrical Properties ◽  
Interface Materials ◽  
Composite Polymeric Material

Different types of fillers with high electrical and thermal conductivities, e.g. graphite and alumina, have been added to adhesive polymers to create composite materials with improved mechanical and electrical properties. Previous modeling efforts have found that it is relatively difficult to predict the effective thermal conductivity of a composite polymeric material when incorporated with large volume content of fillers. We have performed comprehensive computational analysis that models the thermal contacts between fillers. This unique setup can capture the critical heat conduction path to obtain the effective thermal conductivity of the composite materials. Results of these predictions and its comparison with experimental data will be presented in this paper.

Thermal Transport in Self-Assembled Conductive Networks for Thermal Interface Materials

2011 ◽  
Vol 133 (2) ◽  
Author(s):  
Lin Hu ◽  
William Evans ◽  
Pawel Keblinski
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Volume Fraction ◽  
Liquid Solution ◽  
Thermal Interface Materials ◽  
Thermal Interface ◽  
Rapid Formation ◽  
Dynamics Simulations ◽  
Solid Liquid ◽  
Interface Materials

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.

An Improved Efficient Network Model for Determining the Effective Thermal Conductivity of Particulate Thermal Interface Materials

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
B. Dan ◽  
B. G. Sammakia ◽  
G. Subbarayan ◽  
S. Kanuparthi
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Network Model ◽  
Thermal Transport ◽  
Volume Fraction ◽  
Spherical Particles ◽  
Thermal Interface Materials ◽  
Interparticle Interactions ◽  
Cylindrical Region ◽  
Interface Materials

Thermal interface materials (TIMs) are particulate composite materials widely used in the microelectronics industry to reduce the thermal resistance between the device and heat sink. Predictive modeling using fundamental physical principles is critical to developing new TIMs since it can be used to quantify the effect of particle volume fraction and arrangements on the effective thermal conductivity. The existing analytical descriptions of thermal transport in particulate systems do not accurately account for the effect of interparticle interactions, especially in the intermediate volume fractions of 30–80%. An efficient random network model (RNM) that captures the near-percolation transport in these particle-filled systems, taking into account the interparticle interactions and random size distributions, was previously developed by Kanuparthi et al. The RNM approach uses a cylindrical region to approximate the thermal transport within the filler particles and to capture the interparticle interactions. However, this approximation is less accurate when the polydispersivity of the particulate system increases. In addition, the accuracy of the RNM is dependent on the parameters inherent in an analytical description of thermal transport between two spherical particles and their numerical approximation into the network model. In the current paper, a novel semispherical approximation to the conductance of the fillers is presented as an alternative to the cylindrical region approximation used earlier. Compared with the cylindrical model, the thermal conductivities of the semispherical model are more closely to the finite element (FE) results. Based on the FE analysis, the network model is improved by developing an approximation of the critical cylindrical region between two spherical particles over which energy is transported. Comparing the RNM results with FE results and experimental data, a linear relationship of the critical parameter with the thermal conductivity ratio and the volume fraction was found that provides a more accurate prediction of the effective thermal conductivity of the particulate TIMs.

Estimation of Effective Thermal and Mechanical Properties of Particulate Thermal Interface Materials by a Random Network Model

2018 ◽  
Vol 140 (2) ◽  
Author(s):  
Pavan Kumar Vaitheeswaran ◽  
Ganesh Subbarayan
Keyword(s):  
Mechanical Properties ◽  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Network Model ◽  
Random Network ◽  
Thermal Interface Materials ◽  
Thermal And Mechanical Properties ◽  
Thermal Interface ◽  
Classical Models ◽  
Interface Materials

Particulate thermal interface materials (TIMs) are commonly used to transport heat from chip to heat sink. While high thermal conductance is achieved by large volume loadings of highly conducting particles in a compliant matrix, small volume loadings of stiff particles will ensure reduced thermal stresses in the brittle silicon device. Developing numerical models to estimate effective thermal and mechanical properties of TIM systems would help optimize TIM performance with respect to these conflicting requirements. Classical models, often based on single particle solutions or regular arrangement of particles, are insufficient as real-life TIM systems contain a distribution of particles at high volume fractions, where classical models are invalid. In our earlier work, a computationally efficient random network model (RNM) was developed to estimate the effective thermal conductivity of TIM systems (Kanuparthi et al., 2008, “An Efficient Network Model for Determining the Effective Thermal Conductivity of Particulate Thermal Interface Materials,” IEEE Trans. Compon. Packag. Technol., 31(3), pp. 611–621; Dan et al., 2009, “An Improved Network Model for Determining the Effective Thermal Conductivity of Particulate Thermal Interface Materials,” ASME Paper No. InterPACK2009-89116.) . This model is extended in this paper to estimate the effective elastic modulus of TIMs. Realistic microstructures are simulated and analyzed using the proposed method. Factors affecting the modulus (volume fraction and particle size distribution (PSD)) are also studied.

Hierarchical Modeling and Trade-Off Studies in Design of Thermal Interface Materials

2005 ◽  
Author(s):  
X. Zhang ◽  
S. Kanuparthi ◽  
G. Subbarayan ◽  
B. Sammakia ◽  
S. Tonapi
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Volume Fraction ◽  
Particle Volume Fraction ◽  
Thermal Interface Materials ◽  
Particle Volume ◽  
Heat Spreader ◽  
Thermal Interface ◽  
Volume Fractions ◽  
Interface Materials

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.

Enhanced Effective Thermal Conductivity of Composite Materials by Incorporating Constructal Fillers

2021 ◽  
Vol 42 (7) ◽  
Author(s):  
Xiaojian Wang ◽  
Xiaohu Niu ◽  
Wensheng Kang ◽  
Xiaoxue Wang ◽  
Liangbi Wang
Keyword(s):  
Thermal Conductivity ◽  
Composite Materials ◽  
Effective Thermal Conductivity

Characterizing Bulk Thermal Conductivity and Interface Contact Resistance Effects of Thermal Interface Materials in Electronic Cooling Applications

2003 ◽  
Author(s):  
Vadim Gektin ◽  
Sai Ankireddi ◽  
Jim Jones ◽  
Stan Pecavar ◽  
Paul Hundt
Keyword(s):  
Thermal Conductivity ◽  
Thermal Resistance ◽  
Contact Resistance ◽  
Thermal Performance ◽  
Electronic Cooling ◽  
Thermal Interface Materials ◽  
Thermal Interface ◽  
Interface Contact ◽  
Interface Materials ◽  
Bulk Thermal Conductivity

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.

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