Screening of ionic liquids and deep eutectic solvents for physical CO2 absorption by soft-SAFT using key performance indicators

The efficient screening of solvents for CO2 capture requires a reliable and robust equation of state to characterize and compare their thermophysical behavior for the desired application. In this work, the potentiality of 14 ionic liquids (ILs) and 7 deep eutectic solvents (DESs) for CO2 capture was...

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Detalhes bibliográficos
Autores: Llovell Ferret, Félix Lluís, Alkhatib, Ismail I.I., Ferreira, Margarida L., Albà, Carlos G., Bahamon, Daniel, Pereiro, Ana B., Araújo, João M.M., Abu-Zahra, Mohammad R.M., Vega, Lourdes F.
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:20.500.14342/1025
Acesso em linha:http://hdl.handle.net/20.500.14342/1025
https://doi.org/10.1021/acs.jced.0c00750
Access Level:acceso abierto
Palavra-chave:Sals
Dissolvents
Absorció
Viscositat
Salts
Molecular modeling
Absorption
Solvents
Viscosity
54
Descrição
Resumo:The efficient screening of solvents for CO2 capture requires a reliable and robust equation of state to characterize and compare their thermophysical behavior for the desired application. In this work, the potentiality of 14 ionic liquids (ILs) and 7 deep eutectic solvents (DESs) for CO2 capture was examined using soft-SAFT as a modeling tool for the screening of these solvents based on key process indicators, namely, cyclic working capacity, enthalpy of desorption, and CO2 diffusion coefficient. Once the models were assessed versus experimental data, soft-SAFT was used as a predictive tool to calculate the thermophysical properties needed for evaluating their performance. Results demonstrate that under the same operating conditions, ILs have a far superior performance than DESs primarily in terms of amount of CO2 captured, being at least two-folds more than that captured using DESs. The screening tool revealed that among all the examined solvents and conditions, [C4 py][NTf2] is the most promising solvent for physical CO2 capture. The collection of the acquired results confirms the reliability of the soft-SAFT EoS as an attractive and valuable screening tool for CO2 capture and process modeling.