Analytical heat conduction model of particle reinforced tertiary composite materials based on complete spatial randomness of fillers in base matrix and its application in the development of cryosorption pump

•Development of analytical heat conduction model for the prediction of thermal conductivity of tertiary composites.•The model is stochastic in nature and utilizes bivariate Poisson distribution.•The model is applicable at any temperature in range 50 K to 300 K.•Theoretical predictions are validated with experimental data considering the tertiary composite [Epoxy + Aluminium + Zinc].•The results have been used to develop a cryosorption pump of high pumping speed. In this article, we propose an analytical heat conduction model within a stochastic frame work which estimates the thermal conductivity (TC) value of particle reinforced composite materials comprising of three parent elements i.e. a base matrix along with two different filler element particles randomly distributed in it. The spatial distribution of the filler particles in a sample of specific dimension has been estimated by applying bivariate Poisson distribution. This distribution is then used to arrive at the TC value of the composite. This concept has been applied to predict the TC of the tertiary composite comprised of epoxy as the base matrix, aluminium and zinc particles as filler elements. The TC values obtained from this model for different volume fractions of fillers were extensively compared with experimental results. The model is found to predict the results fairly well with less aberrations up to the total filler volume fraction of ∼20%. The developed model for TC prediction has been used in the design of high efficiency cryosorption pump where the adhesive material used is Epoxy-Aluminium -Zinc composite.