Structure-property reduced order model for viscosity prediction in single-component CO2-binding organic liquidsElectronic supplementary information (ESI) available. See DOI: 10.1039/c6gc02203k
CO 2 capture from power generation with aqueous solvents remains energy intensive due to the high water content of the current technology, or the high viscosity of non-aqueous alternatives. Quantitative reduced models, connecting molecular structure to bulk properties, are key for developing structu...
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Main Authors | , , , , , , , |
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Format | Journal Article |
Language | English |
Published |
07.11.2016
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Online Access | Get full text |
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Summary: | CO
2
capture from power generation with aqueous solvents remains energy intensive due to the high water content of the current technology, or the high viscosity of non-aqueous alternatives. Quantitative reduced models, connecting molecular structure to bulk properties, are key for developing structure-property relationships that enable molecular design. In this work, we describe such a model that quantitatively predicts viscosities of CO
2
binding organic liquids (CO
2
BOLs) based solely on molecular structure and the amount of bound CO
2
. The functional form of the model correlates the viscosity with the CO
2
loading and an electrostatic term describing the charge distribution between the CO
2
-bearing functional group and the proton-receiving amine. Molecular simulations identify the proton shuttle between these groups within the same molecule to be the critical indicator of low viscosity. The model, developed to allow for quick screening of solvent libraries, paves the way towards the rational design of low viscosity water-lean solvent systems for post-combustion CO
2
capture. Following these theoretical recommendations, synthetic efforts of promising candidates and viscosity measurement provide experimental validation and verification.
A reduced model connecting molecular structure to viscosity for single-component carbon capture solvents is presented. |
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Bibliography: | 10.1039/c6gc02203k Electronic supplementary information (ESI) available. See DOI |
ISSN: | 1463-9262 1463-9270 |
DOI: | 10.1039/c6gc02203k |