Nonrandom Two-Liquid Segment Activity Coefficient Model with Association Theory

Hao, Ying; Chen, Chau‐Chyun

doi:10.1021/acs.iecr.9b02078

Cited by 19 publications

(30 citation statements)

References 24 publications

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“…We present in the Supporting Information that the association term alone qualitatively predicts the excess enthalpy of mixing. As the model shares the same association term expression and parameters as the association NRTL‐SAC model, 16 the prediction of excess enthalpy is identical to that from the association NRTL‐SAC model.…”

Section: Correlation Of Association Systemsmentioning

confidence: 95%

“…Specifically, the electrons on oxygen of the hydroxyl group and the ether group form HB acceptor sites with difference association strengths. As noted by Hao and Chen, 16 the HB donor sites and HB acceptor sites on the OH group can be approximated with the same association strength of water. On the other hand, the association strength of the HB acceptor sites on EGBE ether group, δ A 2 , is regressed simultaneously with the binary interaction parameters, τ IJ .…”

Section: Correlation Of Association Systemsmentioning

confidence: 98%

“…Following the association NRTL‐SAC model, 16 the proposed association NRTL model combines the classical NRTL model with the NRTL‐SAC association term. Specifically, the model calculates activity coefficient with three terms: the combinatorial term ( γ Comb ) accounting for entropy contribution, and the residual term ( γ Resd ) and the association term ( γ Asso ) accounting for enthalpy contribution due to physical interactions and chemical associations, respectively:

\ln γ_{I} = \ln γ_{I}^{Comb} + \ln γ_{I}^{Resd} + \ln γ_{I}^{Asso}

where I is the component index.…”

Section: Association Nrtl Modelmentioning

confidence: 99%

“…These test systems cover a variety of association scenarios: with self‐association only; with cross‐association only; and with both self‐ and cross‐associations. To model these systems, the association term, γ Asso , is calculated with the molecule‐specific parameters reported in Table 1 for the association NRTL‐SAC model 16 . Specifically, A and D are the numbers of hydrogen bond (HB) acceptor and donor sites on each molecule, respectively; δ A and δ D are the association strength parameters of the corresponding sites; r is the normalized volume parameter.…”

Section: Correlation Of Association Systemsmentioning

confidence: 99%

“…Recently, a “predictive” association NRTL‐SAC model 16 has been successfully developed to integrate the association theory with the NRTL‐SAC activity coefficient model 17 . Adopting the conceptual segment approach of NRTL‐SAC, the association NRTL‐SAC model treats all molecules as the sum of two types of conceptual segment (nonpolar and polar) for physical interactions and two types of association sites (hydrogen bond donor and acceptor) with molecule‐specific association strengths for chemical associations.…”

Section: Introductionmentioning

confidence: 99%

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Nonrandom two‐liquid activity coefficient model with association theory

Hao

Chen

2020

AIChE Journal

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Considered one of the most versatile and widely used classical thermodynamic models to correlate phase equilibria behavior of nonideal systems, the nonrandom two‐liquid (NRTL) theory does not explicitly account for specific chemical associations such as hydrogen bonding. This deficiency has been recognized as the cause for unsatisfactory representation of association systems like methanol–alkanes binaries. This work presents a practical approach to integrate Wertheim's perturbation theory for association contribution with the classical NRTL model. Specifically, the association contribution is calculated from pre‐determined molecule‐specific association strengths while the physical interaction contribution is captured with NRTL binary interaction parameters. The resulting association NRTL model correlates fluid phase equilibria of association systems with few adjustable parameters and offers improved predictive capability for higher order systems.

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Section: Correlation Of Association Systemsmentioning

confidence: 95%

Section: Correlation Of Association Systemsmentioning

confidence: 98%

\ln γ_{I} = \ln γ_{I}^{Comb} + \ln γ_{I}^{Resd} + \ln γ_{I}^{Asso}

where I is the component index.…”

Section: Association Nrtl Modelmentioning

confidence: 99%

Section: Correlation Of Association Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Nonrandom two‐liquid activity coefficient model with association theory

Hao

Chen

2020

AIChE Journal

Self Cite

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Association‐based activity coefficient model for electrolyte solutions

2021

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This work presents an association-based activity coefficient model that explicitly considers the solution nonideality due to associations among ions and solvent species. Built upon the electrolyte nonrandom two-liquid (eNRTL) model, the model greatly improves the accuracy of eNRTL model for strongly associating electrolyte solutions due to presence of ionic species with high surface charge density. The model successfully correlates mean ionic activity coefficients of 46 aqueous singlesalt systems from 10 cations and 5 anions at 298.15 K up to their solubility limits.With the ion-specific association parameters identified, the model accurately predicts activity and osmotic coefficients for aqueous mixed-salt systems at 298.15 K. The temperature dependence of the model results has also been examined at 273-373 K.With superior accuracy over a wide range of concentration and temperature, the model represents a major advancement over eNRTL model and has a great potential to be a next-generation model for electrolyte solutions.

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