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

• Tipo: Artigo em Revista Científica Internacional
• Data: 2021

Autores

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

Revista

A Revista está pendente de validação pelos Serviços Administrativos.

Título: PROCESSES

Vol. 169

Página Final: 1939

ISSN: 2227-9717

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Projetos Associados

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

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 15