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Thermal Conductivity and Microstructure of Copper Coated Graphite Composite by Spark Plasma Sintering Process

Park S. H., Kim D. B., Lee R. G., Son I. J.

Archives of Metallurgy and Materials

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2017

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Vol. 62, iss. 2B

1303--1306

EN

This study focuses on the fabrication of thermal management material for power electronics applications using graphite flake reinforced copper composites. The manufacturing route involved electroless plating of copper in the graphite flake and sintering process are optimized. The microstructures, interface, thermal properties, and relative density of graphite/Cu composites are investigated. The relative density of the composites shows 99.5% after sintering. Thermal conductivities and coefficients of thermal expansion of this composites were 400-480 Wm-1K-1 and 8 to 5 ppm k-1, respectively. Obtained graphite nanoplatelets-reinforced composites exhibit excellent thermo-physical properties to meet the heat dispersion and matching requirements of power electronic devices to the packaging materials.

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A study of the gas specificity of porous silicon sensors for organic vapours

Choi S. H., Cheng H., Park S. H., Kim H. J., Kim Y. Y., Lee K. W.

Materials Science Poland

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2009

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Vol. 27, No. 2

603--610

EN

A porous silicon sensor was investigated as a means to determine the response specificity for organic vapours. Porous silicon layers were fabricated by electrochemical anodization of p-type crystalline silicon in an HF ethanol solution under various conditions. The porous silicon sensors were placed in a gas chamber with various organic vapours, and the changes in electrical resistance under constant voltage of each sensor were used as detection signals. The sensors recorded various changes in resistivity for various organic vapours.

3

Discovering and Matching Elastic Rules from Sequence Databases

Park S.H., Chu W.W.

Fundamenta Informaticae

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2001

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Vol. 47, nr 1,2

75-90

EN

This paper presents techniques for discovering and matching rules with elastic patterns. Elastic patterns are ordered lists of elements that can be stretched along the time axis. Elastic patterns are useful for discovering rules from data sequences with different sampling rates. For fast discovery of rules whose heads (left-hand sides) and bodies (right-hand sides) are elastic patterns, we construct a trimmed suffix tree from succinct forms of data sequences and keep the tree as a compact representation of rules. The trimmed suffix tree is also used as an index structure for finding rules matched to a target head sequence. When matched rules cannot be found, the concept of rule relaxation is introduced. Using a cluster hierarchy and relaxation error as a new distance function, we find the least relaxed rules that provide the most specific information on a target head sequence. Experiments on synthetic data sequences reveal the effectiveness of our proposed approach.