Comparative Evaluation of Algorithms for Achieving Ultrapacked Thermal Greases: Microstructural Models and Effective Behavior

2019 ◽  
Author(s):  
Sukshitha Achar P. L. ◽  
Huanyu Liao ◽  
Ganesh Subbarayan
Keyword(s):  
Heuristic Algorithms ◽  
Volume Fraction ◽  
Optimization Algorithms ◽  
Particle Packing ◽  
Thermal Interface Materials ◽  
Particle Volume ◽  
Thermal Interface ◽  
Volume Fractions ◽  
Interface Materials ◽  
Number Of Particles

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.

Comparative Evaluation of Algorithms for Achieving Ultrapacked Thermal Greases: Microstructural Models and Effective Behavior

2020 ◽  
Vol 142 (4) ◽  
Author(s):  
Sukshitha Achar P. L ◽  
Huanyu Liao ◽  
Ganesh Subbarayan
Keyword(s):  
Heuristic Algorithms ◽  
Volume Fraction ◽  
Augmented Lagrangian Method ◽  
Random Network ◽  
Optimization Algorithms ◽  
Particle Packing ◽  
Computational Time ◽  
Particle Volume ◽  
Volume Fractions ◽  
Number Of Particles

Abstract 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 appear to achieve volume fractions in the range of 60–80%. Therefore, to analyze the effectiveness of commercially available particle-filled thermal interface materials (TIM), there is a need to develop algorithms capable of generating ultrapacked microstructures. The particle packing problem is initially posed as a nonlinear programming problem, and formal optimization algorithms are applied to generate microstructures that are maximally packed. The packing efficiency in the simulated microstructure is dependent on the number of particles in the simulation cell; however, as the number of particles increases, the packing simulation is computationally expensive. Here, the computational time to generate microstructures with large number of particles is systematically evaluated first using optimization algorithms. The algorithms include the penalty function methods, best-in-class sequential quadratic programming method, matrix-less conjugate gradient method as well as the augmented Lagrangian method. Heuristic algorithms are next evaluated to achieve computationally efficient packing. The evaluated heuristic algorithms are mainly based on the drop-fall-shake (DFS) 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.

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.

Rheological Study of Micro Particle Laden Polymeric Thermal Interface Materials: Part 1 — Experimental

2002 ◽  
Author(s):  
Ravi S. Prasher ◽  
Jim Shipley ◽  
Suzana Prstic ◽  
Paul Koning ◽  
Jin-Lin Wang
Keyword(s):  
Thermal Conductivity ◽  
Volume Fraction ◽  
Particle Volume Fraction ◽  
Electronics Cooling ◽  
Bond Line ◽  
Rheological Parameters ◽  
Thermal Interface Materials ◽  
Particle Volume ◽  
Thermal Interface ◽  
Interface Materials

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.

Rheological Study of Micro Particle Laden Polymeric Thermal Interface Materials: Part 2 — Modeling

2002 ◽  
Author(s):  
Ravi S. Prasher ◽  
Jim Shipley ◽  
Suzana Prstic ◽  
Paul Koning ◽  
Jin-Lin Wang
Keyword(s):  
Thermal Conductivity ◽  
Thermal Resistance ◽  
Yield Stress ◽  
Volume Fraction ◽  
Particle Volume Fraction ◽  
Thermal Interface Materials ◽  
Particle Volume ◽  
Thermal Interface ◽  
Complete Set ◽  
Interface Materials

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.

Thermal Resistance of Particle Laden Polymeric Thermal Interface Materials

2003 ◽  
Author(s):  
Ravi S. Prasher ◽  
Jim Shipley ◽  
Suzana Prstic ◽  
Paul Koning ◽  
Jin-Lin Wang
Keyword(s):  
Thermal Conductivity ◽  
Thermal Resistance ◽  
Volume Fraction ◽  
Applied Pressure ◽  
Electronics Cooling ◽  
Thermal Design ◽  
Thermal Interface Materials ◽  
Particle Volume ◽  
Thermal Interface ◽  
Interface 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.

Predicting Thermal Characteristics of Particle Laden Thermal Interface Materials

2009 ◽  
Author(s):  
Reza H. Khiabani ◽  
Yogendra Joshi ◽  
Cyrus Aidun
Keyword(s):  
Thermal Conductivity ◽  
Thermal Performance ◽  
Volume Fraction ◽  
Particle Volume Fraction ◽  
Thermal Characteristics ◽  
Thermal Conductivity Ratio ◽  
Thermal Interface Materials ◽  
Particle Volume ◽  
Thermal Interface ◽  
Interface Materials

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.

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

2017 ◽  
Author(s):  
Pavan Kumar Vaitheeswaran ◽  
Ganesh Subbarayan
Keyword(s):  
Mechanical Properties ◽  
Network Model ◽  
Thermal Stresses ◽  
Volume Fraction ◽  
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 distriubtion of particles at high volume fractions, where classical models are invalid. In our earlier work, a computationally efficient random network model was developed to estimate the effective thermal conductivity of TIM systems [1,2]. 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) are also studied.

On Thermal Interface Materials With Polydisperse Fillers: Packing Algorithm and Effective Properties

2018 ◽  
Author(s):  
Piyas Chowdhury ◽  
Kamal Sikka ◽  
Anuja De Silva ◽  
Indira Seshadri
Keyword(s):  
Thermal Conductivity ◽  
Elastic Modulus ◽  
Volume Fraction ◽  
Effective Properties ◽  
Material Design ◽  
High Volume ◽  
Thermal Interface Materials ◽  
Thermal Interface ◽  
Packing Algorithm ◽  
Interface Materials

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.

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.

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