Characterization Of Dispersion Of Pcm In Matrix And Its Impact On Thermal Conductivity Of Composite

As a particle filled thermal system, there are many factors that have impact on thermal conductivity of composite, such as the thermal conductivity of filler and matrix material, volume fraction of fillers. Besides, particle size and size distribution of filler in the matrix and the dispersion of filler in matrix are the other two important factors. There is no best method to quantitatively characterize the two factors because the complexity of internal structure in composite and the randomicity of particle distribution in matrix. Therefore, the realization of quantitative characterization on these two factors will be beneficial to further reseach the relationship between particle size distribution, particle dispersion and the thermal property, and also plays some promoting role for the preparation of particulate-filled composites.The particle size distribution of power storage clay and conductivity factor of phase transformafion power storage gypsum were measured respectively by digital camera and image process software and heat test machine. A general mathematical model for calculating the size distribution fractal dimension of inorganic particle based on fractal theory and statistical concept was modeled. The multifractal spectrum and lacunarity were calculated by image analysis, which were achieved with Matlab and Excel, based on box counting algorithm and gliding box algorithm respectively in order to analyze the dispersion of particle in matrix. The relationship between the two parameters and thermal property was investigated. After researching the relative tests, models and new methods, main conclusions in the thesis were as follows:(1) Size distribution of phase-change particulate was fractal structure and could be quantitatively characterized by D psd. The smaller of fractal dimension, the more homogeneous of particle size; as the temperature increased, the impact of fractal dimension on thermal conductivity composite became weaker.(2) The influence of particulate volume content on thermal conductivity composite investigated by GM model showed that particulate with size among 9~10mm, 10~14mm had least impact on thermal conductivity under each test temperature; meanwhile, particulate with size among 0~3mm enhanced thermal conductivity greatest under 28℃. (3) The dispersed distribution in matrix of phase-change particulate was evidently multifractal, could be quantitatively characterized by multifractal spectrum and its parameters: ?α. The smaller of ?α, the more homogeneous of dispersion.(4) The lacunarity calculated by gliding box algorithm could measure the deviation of random distribution of gaps among particulate from perfectly regular distribution. AsΛ(r ) got close to 1, the distribution of gaps was more regular and the congestion became less.