Predicting the Surface Tension of Deep Eutectic Solvents Using Artificial Neural Networks
Tarek Lemaoui, Abir Boublia, Ahmad S. Darwish, Manawwer Alam, Sung‐Min Park, Byong‐Hun Jeon, Fawzi Banat, Yacine Benguerba, Inas M. AlNashef
Abstract
values of 0.986 and 0.977 were obtained for training and testing, respectively, with an overall average absolute relative deviation of 2.20%. The proposed models represent an initiative to promote the development of robust models capable of predicting the properties of DESs based only on molecular parameters, leading to savings in investigation time and resources.
Topics & Concepts
Surface tensionEutectic systemArtificial neural networkComputer scienceMaterials scienceArtificial intelligenceThermodynamicsComposite materialPhysicsAlloyIonic liquids properties and applicationsElectrochemical Analysis and ApplicationsChemical and Physical Properties in Aqueous Solutions