Experimental, modeling and optimisation of adipic acid reactive extraction using ionic liquids

Adipic acid (hexanedioic acid, AA) can be utilised as an essential monomer in the production of nylon-6,6 (75 %), but also for urethane foams, fibers, elastomers, tire reinforcements, and synthetic lubricants. Considerable work has been done to develop sustainable biosynthetic processes for its manufacture, especially for adipic acid efficient separation (one of the main challenges for industrialisation). As for scale-up, process optimisation, and thorough engineering mathematical models that describe the system efficiently are required, this study proposes mathematical models for a reactive extraction using ionic liquids as extractants for adipic acid separation to improve the biosynthetic route's sustainability, efficiency, and environmental performance. Heptane as the solvent and 117.8 g/L [P6,6,6,14][Phos] 6,6,6,14 ][Phos] as the extractant at 2.8 pH of the aqueous phase were the optimum mixture for reactive extraction, resulting in an extraction yield of 97.55 % for adipic acid. The process was modeled using an artificial neural network optimised with a differential evolution algorithm. The optimal model structure had one hidden layer with 20 neurons, and its performance in the testing phase was: explained variance score of 0.974, mean absolute error of 1.917, and coefficient of determination of 0.974.