4.5 Article

A general viscosity model for deep eutectic solvents: The free volume theory coupled with association equations of state

期刊

FLUID PHASE EQUILIBRIA
卷 470, 期 -, 页码 193-202

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.fluid.2017.08.024

关键词

Cubic plus association; CPA; PC-SAFT; DES; Physical property

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Deep eutectic solvents (DESs) make up a most-recent category of 'green' solvents with a potentially promising future. Insignificant vapor pressure, biodegradability, low cost, task-specific engineering, and high absorption for gases such as CO2 are the most important characteristics of most DESs. To apply DESs in various industries, knowledge of their physical properties is vital. Since the viscosity of a DES is a strong function of temperature, as well as the ratio of the hydrogen bond donating and accepting components, to estimate the viscosity behavior, a model based on sound theory is proposed in this study, i.e., the free volume theory. Since DESs are strongly associating components, this theory is enriched by using associating equations of state, namely CPA and PC-SAFT. In this study, a large density and viscosity databank of 27 DESs of different nature, also with varying molar ratios of the hydrogen bond donor and acceptor, were used to propose the model. In this way, a global model is presented for the first time to estimate the viscosities of DESs. The pseudo-component approach, with a 2B association scheme, was considered for the DESs. Both the CPA and the PC-SAFT EoSs, coupled with the free volume theory, showed reliable results, with average AARD% values in viscosity for all of the investigated DESs equal to 2.7% and 2.7%, respectively. Furthermore, both models reliably showed the trend of nearly logarithmic increase in DES viscosity with decreasing temperature. Also, both models accurately estimated the viscosity behavior of the DESs by not only changing the molecular nature of the hydrogen bond donor with a fixed hydrogen bond acceptor, but also at all of the various molar ratios investigated. (C) 2017 Elsevier B.V. All rights reserved.

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