Enhancing Li <sup>+</sup> recovery in brine mining: integrating next-gen emotional AI and explainable ML to predict adsorption energy in crown ether-based hierarchical nanomaterials
Sani I. Abba, Jamilu Usman, Ismail Abdulazeez, Lukka Thuyavan Yogarathinam, A. G. Usman, Dahiru U. Lawal, Billel Salhi, Nadeem Baig, Isam H. Aljundi
Abstract
ions. The extreme gradient boosting algorithm (XGBoost) model demonstrated a RT-2-MAPE = 0.4618% and ENN-2-MAPE = 0.4839% for the feature engineering analysis. This research would be an insight into the AI-driven nanotechnology that presents a viable and sustainable approach for the extraction of natural resources through the application of brine mining.
Topics & Concepts
BrineCrown etherAdsorptionNanomaterialsChemistryNuclear chemistryMaterials scienceNanotechnologyPhysical chemistryOrganic chemistryIonExtraction and Separation ProcessesRadioactive element chemistry and processingAdvancements in Battery Materials