NDLI: Random network percolation models for particulate thermal interface materials

Content Provider	IEEE Xplore Digital Library
Author	Kanuparthi, S. Zhang, X. Subbarayan, G. Sammakia, B.G. Siegmund, T. Gowda, A. Tonapi, S.
Copyright Year	2006
Description	Author affiliation: Purdue Univ., West Lafayette, IN (Kanuparthi, S.; Zhang, X.; Subbarayan, G.)
Abstract	Thermal interface materials (TIMs) are widely used in the microelectronics industry to adequately expel the waste heat generated in the chips, by reducing the contact resistance between the chip and the heat sink. 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 models enables 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 50% - 60%. Another crucial drawback in the existing analytical as well as the network models is the inability to model random size distributions of the filler material particles, which is what one obtains when particulates are produced. While mil-field simulations (using the finite element method) are possible for such systems, they are computationally expensive. In the present paper, we develop efficient network models that capture the inter-particle interactions and also allow random size distributions. Fifteen microstructural arrangements of alumina as well as aluminum particles in silicone matrix were first experimentally characterized. Microstructures that are representative of the experimentally tested systems were simulated using a drop-fall-shake algorithm implemented in Java. Thirty such microstructural arrangements were evaluated through both full field simulations as well as the network models. In all cases, it is shown that the full-field simulations of effective behavior are accurate to within 10% of the experimentally measured values and the random network models are accurate to within 10% of the full field simulations. The random network models were efficient since they required a few minutes to run, while the full field simulations required 4-5 hours on an average to complete
Starting Page	7
Ending Page	1198
File Size	453893
Page Count	1192
File Format	PDF
ISBN	0780395247
ISSN	10879870
DOI	10.1109/ITHERM.2006.1645480
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-05-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Atmospheric modeling Thermal conductivity Heat sinks Waste heat Predictive models Computational modeling Thermal resistance Waste materials Microelectronics Contact resistance
Content Type	Text
Resource Type	Article

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