A Hybrid Modeling Framework for Membrane Separation Processes: Application to Lithium-Ion Recovery from Batteries

• Type: Article in International Scientific Journal
• Date: 2021

Authors

Regufe, MJ (Author) Other; Santana, VV (Author) Other; Alexandre Ferreira (Author) FEUP; Ana M. Ribeiro (Author) FEUP; Loureiro, JM (Author) Other; Nogueira, IBR (Author) FEUP

Journal

The Journal is awaiting validation by the Administrative Services.

Title: PROCESSES

Vol. 169

Final page: 1939

ISSN: 2227-9717

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Associated Projects

LA LSRE-LCM - Financiamento Plurianual 2020-2023 para a Unidade LA LSRE-LCM Laboratório de Processos de Separação e Reacção - Laboratório de Catálise e Materiais

Other information

Authenticus ID: P-00V-NRG

DOI: 10.3390/pr9111939

Abstract (EN): This study proposed a hybrid modeling framework for membrane separation processes where lithium from batteries is recovered. This is a pertinent problem nowadays as lithium batteries are popularized in hybrid and electric vehicles. The hybrid model is based on an artificial intelligence (AI) structure to model the mass transfer resistance of several experimental separations found in the literature. It is also based on a phenomenological model to represent the transient system regime. An optimization framework was designed to perform the AI model training and simultaneously solve the Ordinary Differential Equation (ODE) system representing the phenomenological model. The results demonstrate that the hybrid model can better represent the experimental validation sets than the phenomenological model alone. This strategy opens doors for further investigations of this system.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 15