In chemical product design, it is desirable to formulate a product with a set of target properties to perform specific functions. Ingredients and internal product structure are two key drivers of product quality with direct impact on the thermal, electrical, and mechanical properties. Thus, there is a keen interest in elucidating the dependence of product performance on ingredients and structure. Design of product structure, particularly microstructure, is an intrinsically complex problem that involves different phases of different physicochemical properties, mass fraction, morphology, size distribution, and interconnectivity. Whilst microstructure plays an essential role in product design, a seamless approach is missing to characterize, generate, and analyze microstructure to predict d...[ Read more ]

In chemical product design, it is desirable to formulate a product with a set of target properties to perform specific functions. Ingredients and internal product structure are two key drivers of product quality with direct impact on the thermal, electrical, and mechanical properties. Thus, there is a keen interest in elucidating the dependence of product performance on ingredients and structure. Design of product structure, particularly microstructure, is an intrinsically complex problem that involves different phases of different physicochemical properties, mass fraction, morphology, size distribution, and interconnectivity. Whilst microstructure plays an essential role in product design, a seamless approach is missing to characterize, generate, and analyze microstructure to predict desired properties that can be effectually utilized as process design target. This thesis proposes an extension to the Grand Product Design (GPD) model to expound the dependence of product performance (in terms of target properties) on its structure for structured chemical products. The influence of different microstructural aspects on performance has been explicated and computational techniques have been developed for the systematic optimization of microstructure.

In Chapter 2, review and critical analysis of various computational methods to design microstructure are provided and a computation-assisted performance, ingredients, structure, and manufacturing process (PRISM) framework is formulated for structured chemical products. An optimization-based approach is presented in Chapter 3 for determining the target of two-phase particulate composite microstructure incorporating filler particles of different size, shape, and orientation. In chapter 4, a multi-criteria extension to the optimization of microstructure is provided for microstructure design targeting and ingredients selection in conductive polymer composite. Finally, Chapter 5 summarizes the major contributions together with the recommendations for future work.