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Modelling electrical transport in nano-particle composites using 3D network analysis

University of British Columbia

Conductive composites consist of a conductive filler dispersed within an insulating matrix. These composite materials have been known for many years and are regularly produced experimentally and commercially for a variety of applications. Novel techniques are now being found for creating composites that exhibit conductivity with less conductive filler material than classical physics suggests is sufficient if the particles are uniformly distributed. Several parties have offered physical explanations for the characteristics of their composites by incorporating a blend of classical and quantum physics but few attempts have been made to compare explanations or develop any mechanism to simulate the physics. The model presented in the present work incorporates first principles physics and semi-empirical theory to account for the distribution of particles within a composite and calculate resultant conductivity using three dimensional network analysis. Results from several model iterations are presented and they are compared with published experimental results. The model demonstrates that a random distribution of spherical particles smaller than 200 nm at 3% loading, given realistic wave function decay rates and reasonable tunnelling barrier heights, cannot explain experimentally observed conductivities in these composite materials. The final model, using a Voronoi tessellation approach, duplicates the behaviour trend of the composites being simulated and illustrates some gaps in the present material science knowledge of conductive composites.

Text

2014-02-28

CC0 1.0 Universal

http://hdl.handle.net/2429/46120

Electrical and Computer Engineering

University of British Columbia

UBCV

http://creativecommons.org/publicdomain/zero/1.0/