Designing sensorial behaviour of Fabrics.

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&G detergent research constantly yields new and improved chemical variations on existing detergent components that meet consumer habits and regional needs. The performance of these variations can be experimentally evaluated, which involves placing artificially soiled fabrics into commercial washing machines, followed by determining the amount of soil removed and the degree of fabric whiteness by visual means. Such evaluation could take up to 3 days for a given formulation. Fabric care is another additional vector that is delivered traditionally using polymers and softener products to drive the desired performance; consumer test panels and physical testing are often conducted to assess fabric appearance (shape, wrinkles), softness (feel) and fabric longevity. Additionally, feel actives have important interactions with other cleaning vectors such as stain removal, whiteness and perfume. As modern day economic and environmental constraints tighten, there is a need to quickly and cheaply determine the optimally performing formulation and innovate with new products in the market. Such demands result in an extra layer of difficulty in efficiently optimising the performance of a formulation due to the considerable number of components in a detergent and softener formulation. Predictive tools based on first principles understanding of the physic-chemical process of washing have shown immense potential in assessing fabric care performance. The aim of this proposal is to establish the fundamental understanding of the effect of detergent chemistry on the deposition kinetics of cationic actives on fabrics (natural and synthetic fibers), which determines the consumer perception. Ability to correlate the characteristics of fabric at multiple length scales will be a key enabler to develop disruptive technologies in meeting the challenges aforementioned.