DocumentCode :
170719
Title :
Using a Monte-Carlo model to identify best filler arrangement in thermally conductive materials
Author :
Descamps, Philippe ; Teixeira, Senhorinha ; Beaucame, G.
Author_Institution :
Dow Corning Eur. S.A, Seneffe, Belgium
fYear :
2014
fDate :
24-26 Sept. 2014
Firstpage :
1
Lastpage :
6
Abstract :
A 2D Monte-Carlo model was built to calculate the probability of paths creation between the two interfaces of a TC material via direct contact between filler particles. This model allowed studying the impact of the filler size with respect to the distance between the two interfaces on the probability of direct TC paths creation. Calculation is carried-out considering one single filler size and the mixture of two fillers of different dimensions. We demonstrate that at low degree of filler loading, it is preferable to use large size filler compared to the volume to fill; when increasing filler loading, the trend reverses and it becomes beneficial to use smaller size filler for increasing probability of path creation. In case of two fillers of different dimensions, an optimum fraction of large size filler exists that depends on the filler loading level: at low filling level, the optimum corresponds to a high fraction of large size particles, this optimum displacing towards a lower fraction of large size filler when the filling level increases.
Keywords :
Monte Carlo methods; particle reinforced composites; particle size; thermal conductivity; 2D Monte-Carlo model; direct contact; filler arrangement; filler loading degree; filler mixture; filler particles; filler size; large size particles; optimum displacing; path creation probability; thermally conductive materials; Conferences; Filling; Load modeling; Loading; Monte Carlo methods; Probability; Thermal conductivity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Thermal Investigations of ICs and Systems (THERMINIC), 2014 20th International Workshop on
Conference_Location :
London
Type :
conf
DOI :
10.1109/THERMINIC.2014.6972482
Filename :
6972482
Link To Document :
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