Product Design is essential for the prosperity of the chemical industry. But how do we design new chemical products? How do we optimize existing products? We are interested in papers discussing computational, experimental or methodological tools that can help design new products and improving existing products from performance and economic perspectives. Topics of interest include methods for design, development, and optimization of chemical products as pure compounds or mixtures. We are especially interested in novel design and formulation approaches that combine first-principle understanding and novel statistical learning methods, including, but not limited to, experiment design, machine learning, and neural networks. Papers on the measurement, correlation, and modeling of physicochemical properties of pure compounds and mixtures, simple fluids and colloidal dispersions, toward application in chemical process and product design are also welcome. This session includes papers on machine learning approaches for product design, and the design of products such as cosmetic emulsions, fabric enhancers for clothes drying, safer solvents for chemical separations, and electrodes and electrolytes for electrochemical processes.

Product Design