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The effective thermal conductivity of Cu-Fe and Sn-Al miscibility gap alloys over a range of temperatures and volume fractions was determined using the Lattice Monte Carlo Method. The Cu-Fe system was found to have an effective conductivity predictable by the Maxwell-Eucken Model. The Sn-Al system was not consistent with any empirical model analysed. The microstructures of physical samples were approximated using a random growth algorithm calibrated to electron or optical microscope images. Charts of effective conductivity against temperature for a number of volume fractions are presented for the two alloys. It was determined that the Cu-Fe alloy would benefit from an interstice type microstructure and the Sn-Al would be more efficient with a hard spheres type microstructure. More general conclusions are drawn about the efficiency of the two observed microstructures. to the variance observed between real images. Typical microstructures of both real and generated microstructures are shown along with their generation properties and correlation function variances in Table 1.

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Abstract. Miscibility gap alloys (MGAs) are an emerging thermal energy storage material with unique thermal properties that may be of particular interest to the renewable energy industry. In this study, they are compared to state of the art thermal storage technologies on an economic basis, with consideration given to material prices, manufacturing costs, specific deployment infrastructure costs, maintenance schedule cost and the potential for material salvage. Cost estimates are provided for seven different MGAs deployed in three different thermal storage implementations.