Commercial and industrial detergents, formulated liquid blends, have recently become extremely sophisticated, in order to address a broad range of cleaning tasks and to deliver superior performances with a minimum of effort and time. These products, by definition, consist of different chemicals, each with a specific function related to the needs of the product: surfactants, builders, bleaching agents, enzymes and minors, usually mixed together with a carrier, necessary to keep the blend as a homogeneous liquid formulation. A system approach and associated tools can help to virtually generate and test different candidates in order to identify the most promising formulations before a detailed experimental stage for final selection and product development is applied. In this way, the whole design procedure speeds up, saving time and money, and the optimum formulation is identified, since a broad range of alternatives are investigated. The approach adopted for the design of emulsion-based chemical products consists in a systematic model-based methodology employing seven hierarchical steps: starting with the identification of the product needs and their translation into appropriate target properties, then building the formulation by adding, one-by-one, the different classes of chemicals needed for each function: from the active ingredients, to the solvents, the emulsifiers and the additives, and finally determining the optimal composition of the formulated product. The design of the ingredients, driven by selection criteria based on the functional properties of each category of chemicals as well as by consideration of effectiveness, safety, toxicity and cost, is done through a data-model based computer aided molecular design technique. When a model-based design is not applicable since the functional properties needed to perform a rigorous choice are not readily available for consideration in a product design methodology, rule-based selection criteria are applied. These are centered on structured databases, where some relevant properties (e.g. safety or toxicity-related), if not available,are predicted through dedicated pure component property models. Once all the most advantageous ingredients have been chosen, the recipe candidates are identified through a knowledge-based mixture design method, where economic considerations are included together with appropriate boundaries related to solubility, stability, toxicity and safety issues. A special database of chemicals, classified according to their function and associated properties, has been developed. Also, a model library consisting of pure component and mixture property models has been developed so that the needed functional properties can be reliably predicted when their data cannot be found in the database. The abovementioned methodology and related tools are generic, in the sense that many different emulsified products can be designed through this framework once the needs-property relations are established, and they are here highlighted through a case-study dealing with the design of a tank cleaning blend. The main focus of this contribution is on the design of surfactants,primary responsible for the cleaning activity, thanks to a comprehensive framework based on newly developed both pure component and mixture property models. The work-flow methodology with associated models, tools, databases and algorithms will be implemented into a computer-aided framework for emulsion-based formulation design.
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9th European Congress of Chemical Engineering, 2013