(229f) An Integrated Methodology for the Design of Optimal Solvent-Based Adhesive Products with Low Toxicity | AIChE

(229f) An Integrated Methodology for the Design of Optimal Solvent-Based Adhesive Products with Low Toxicity

Authors 

Jonuzaj, S. - Presenter, Imperial College London
Adjiman, C. S., Imperial College London
Cui, J., Imperial College London
Adhesive products are widely used in consumer goods, dental composite restoration, wood processing, and in the paper and packaging, construction, and transportation industries (Ebnesajjad & Landrock, 2015). Nearly 14 million tonnes of adhesives are used worldwide to meet the market demand, which is expected to further increase in the next few years (Ceresana Market Research, 2019). As such, the manufacture of improved adhesive products that meet specified target properties has attracted increasing interest over the last decades. The design of such products, however, remains challenging as it requires (i) the combination of a large number of ingredients and different types of chemicals to obtain product formulations with desired functionalities and qualities and (ii) consideration of economic, environmental and health/safety aspects. Nevertheless, in current industrial practice, methods for identifying suitable chemical blends (number of ingredients, identity of compounds and their proportions) and corresponding processing technologies are mainly based on trial-and-error approaches. In this context, the development of systematic methodologies and tools to design adhesive formulations can be an important advantage in the field.

In this work, we present a comprehensive approach for the design of optimal adhesive products with low environmental impact (Cui et al., 2018; Jonuzaj et al., 2019). The proposed methodology integrates computer-aided design tools (Gani, 2004) and Generalised Disjunctive Programming (Raman and Grossmann, 1994) to formulate and solve the product design problem. Within this integrated approach, the number of product constituents, the identities of the components (i.e., active ingredients and solvents) and their compositions are determined simultaneously. This makes it possible to identify the best combination of active ingredient and the solvent mixture, alleviating the need to decompose the problem in sequential steps in order to specify the identity of each type of chemical. The design methodology is applied to identifying optimal acrylic adhesive formulations with low toxicity. The results show that better performance can be achieved with an integrated product design approach rather than using simplified hierarchical methods. Furthermore, significant trade-offs between competing performance objectives are highlighted through a set of Pareto optimal solutions, where different blends are evaluated based on product toxicity and concentration of the active ingredient. Finally, a ranked list of promising designs, which can serve as a guide to experiments, is generated by adding integer cuts to the integrated formulation, showing that the top-ranked products are diverse in terms of the number of mixture ingredients, the identity of the solvents and their composition.

Ceresana Market Research. Accessed 2019. Market Study: Adhesives - World (3rd edition). Available at: https://www.ceresana.com/en/market-studies/industry/adhesives-world/ceresana-market-study-adhesives-world.html.

Cui, J., Jonuzaj, S. & Adjiman, C.S., 2018. A Comprehensive Approach for the Design of Solvent-based Adhesive Products using Generalized Disjunctive Programming. Computer Aided Chemical Engineering, 44, pp.427-432.

Ebnesajjad, S. & Landrock, A.H., 2015. Adhesives Technology Handbook (3rd Edition), San Diego, CA, USA: Elsevier Inc.

Gani, R., 2004. Computer-aided methods and tools for chemical product design. Chemical Engineering Research and Design, 82, pp.1494-1504.

Jonuzaj, S., Cui, J. & Adjiman, C.S., 2018. Computer-aided design of optimal environmentally benign solvent-based adhesive products. Computers and Chemical Engineering. Accepted for publication.

Raman, R. & Grossmann, I.E., 1994. Modelling and computational techniques for logic based integer programming. Computers & Chemical Engineering, 18, pp.563-578.