Heterogeneous materials are becoming more common in a wide range of functional devices, particularly those involving energy transport, conversion, and storage. Often, heterogeneous materials are crucial to the performance and economic scalability of such devices. Heterogeneous materials with inherently random structures exhibit a strong sensitivity of energy transport properties to processing and operating conditions. Therefore, improved predictive modeling capabilities are needed that quantify the detailed microstructure of such materials based on various manufacturing processes and correlate them with transport properties. In this work, we integrate high fidelity microstructural and transport models, which can aid in the development of high performance energy materials. Heterogeneous materials are generally comprised of nanometric or larger length scale domains of different materials or different phases of the same material. State-of-the-art structural optimization models demonstrate the predictability of the microstructure for heterogeneous materials manufactured via powder compaction of variously shaped and sized particles. The ability of existing diffusion models to incorporate the essential multiscale features in random microstructures is assessed. Lastly, a comprehensive approach is presented for the combined modeling of a high fidelity microstructure and heat transport therein. Exemplary results are given that reinforce the importance of developing predictive models with rich stochastic output that connect microstructural information with physical transport properties.

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