Isobaric vapor – liquid – liquid equilibrium for water + MTBE + alcohol (ethanol or 1-butanol) mixtures

Mejı́a, Andrés; Cartes, Marcela; Chaparro, Gustavo

doi:10.1016/j.fluid.2020.112768

Cited by 10 publications

(11 citation statements)

References 49 publications

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“…For this example, both phase equilibrium and interfacial tensions have been recently measured by some of us. 41,42 Notebooks W21 and W22 (Supporting Information) include all the needed parameters to carry out the calculation of the phase equilibrium and the corresponding interfacial tensions.…”

Section: Description and Application Of The Sgtpy Packagementioning

confidence: 99%

“…This system can exhibit vapor–liquid–liquid phase equilibrium, characterized by three interfacial regions (i.e., VL 1 , VL 2 , and L 1 L 2 ), each associating with an interfacial or surface tension (i.e., γ VL1 , γ VL2 , and γ L1L2 ). For this example, both phase equilibrium and interfacial tensions have been recently measured by some of us. , Notebooks W21 and W22 (Supporting Information) include all the needed parameters to carry out the calculation of the phase equilibrium and the corresponding interfacial tensions.…”

Section: Description and Application Of The Sgtpy Packagementioning

confidence: 99%

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SGTPy: A Python Code for Calculating the Interfacial Properties of Fluids Based on the Square Gradient Theory Using the SAFT-VR Mie Equation of State

Mejı́a

Müller

Chaparro

2021

J. Chem. Inf. Model.

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In this work, we showcase SGTPy, a Python open-source code developed to calculate interfacial properties (interfacial concentration profiles and interfacial or surface tension) for pure fluids and fluid mixtures. SGTPy employs the Square Gradient Theory (SGT) coupled to the Statistical Associating Fluid Theory of Variable Range employing a Mie potential (SAFT-VR-Mie). SGTPy uses standard Python numerical packages (i.e., NumPy, SciPy) and can be used under Jupyter notebooks. Its features are the calculation of phase stability, phase equilibria, interfacial properties, and the optimization of the SGT and SAFT parameters for vapor–liquid, liquid–liquid and vapor–liquid–liquid equilibria for pure fluids and multicomponent mixtures. Phase equilibrium calculations include two-phase and multiphase flash, bubble and dew points, and the tangent plane distance. For the computation of interfacial properties, SGTPy incorporates several options to solve the interfacial concentration, such as the path technique, an auxiliary time function, and orthogonal collocation. Additionally, the SGTPy code allows the inclusion of subroutines from other languages (e.g., Fortran, and C++) through Cython and f2py Python tools, which opens the possibility for future extensions or recycling tested and optimized subroutines from other codes. Supporting Information includes a review of the theoretical expressions required to couple SAFT-VR-Mie equation of state with the SGT. The use and capabilities of SGTPy are illustrated through step by step examples written on Jupyter notebooks for the cases of pure fluids and binary and ternary mixtures in bi- and three- phasic equilibria. The SGTPy code can be downloaded from .

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Section: Description and Application Of The Sgtpy Packagementioning

confidence: 99%

Section: Description and Application Of The Sgtpy Packagementioning

confidence: 99%

SGTPy: A Python Code for Calculating the Interfacial Properties of Fluids Based on the Square Gradient Theory Using the SAFT-VR Mie Equation of State

Mejı́a

Müller

Chaparro

2021

J. Chem. Inf. Model.

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“…Thus, it is mainly applicable to type 2 biphasic solvent systems (two miscible solvents are not miscible with the third one), as the ternary phase diagram has converging tie lines. The MtBE/n-BuOH/water solvent system shows such a type 2 ternary diagram (Figure 2), allowing its use for an organic mobile phase polarity gradient (ascending mode) [26].…”

Section: Development Of a Strategy For The Physical Suppression Of Propylene Glycol And Propanediol In Natural Extractsmentioning

confidence: 99%

Dereplication of Natural Extracts Diluted in Propylene Glycol, 1,3-Propanediol and Glycerin. Comparison of Leontopodium alpinum Cass. (Edelweiss) Extracts as a Case Study

et al. 2021

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Many natural extracts used as cosmetic ingredients are available as solutions prepared in high-boiling-point solvents, called carrier solvents, such as propylene glycol (1,2-propanediol), propanediol (1,3-propanediol) and glycerin. The upstream chemical profiling of these extracts represents a major asset for the cosmetic industry, because it accelerates product development. A new workflow for the rapid characterization of the main metabolites present in natural extracts diluted in propylene glycol and 1,3-propanediol is presented here as an extension of previous works on glycerin-containing extracts. This method is an optimized version of a well-established dereplication procedure and consists of a fractionation by centrifugal partition chromatography followed by 13C nuclear magnetic resonance analysis and dedicated data processing. The concentration by evaporation under reduced pressure was considered as a pertinent preliminary step, particularly adapted to the analysis of highly diluted extracts. A dried hydro-ethanolic extract of Leontopodium alpinum Cass. was prepared at laboratory scale and used for method validation. Three solutions at 5% wt. of dry extract were prepared with propylene glycol/water (1:1), 1,3-propanediol/water (1:1) and glycerin/water (1:1) as carrier solvents. The dereplication workflow was applied to the three resulting L. alpinum extracts. Each study led to the quick identification of 26 metabolites including five flavonoids (luteolin and its derivatives), five hydroxycinnamic acids (among which are leontopodic acids), sugars and organic acids.

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“…This mixture has experimentally shown VLLE in a narrow temperature range. 64 First, the MTBE component has to be created and added to the already existing mixture. As this is a new mixture a new EoS object must be created (Listing 13).…”

Section: Two-phase Equilibriamentioning

confidence: 99%

“…In order to illustrate this implementation the ternary mixture of water, ethanol and methyl tert‐butyl ether (MTBE) is studied. This mixture has experimentally shown VLLE in a narrow temperature range 64 . First, the MTBE component has to be created and added to the already existing mixture.…”

Section: Multiphase Equilibriamentioning

confidence: 99%

Phasepy: A Python based framework for fluid phase equilibria and interfacial properties computation

Chaparro

Mejı́a

2020

J Comput Chem

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Phasepy is a Python based package for fluid phase equilibria and interfacial properties calculation from equation of state (EoS). Phasepy uses several tools (i.e., NumPy, SciPy, Pandas, Matplotlib) allowing use Phasepy under Jupyter Notebooks. Phasepy models phase equilibria with the traditional ϕ-γ and ϕ-ϕ approaches, where ϕ (fugacity coefficient) can be modeled as a perfect gas, virial gas or EoS fluid, whereas γ (activity coefficient) can be described by conventional models (NRTL, Wilson, Redlich-Kister expansion, and the group contribution modified-UNIFAC). Interfacial properties are based on the square gradient theory couple to ϕ-ϕ approach. The available EoSs are the cubic EoS family extended to mixtures through the quadratic, modified-Huron-Vidal, and Wong-Sandler mixing rules. Phasepy allows to analyze phase stability, compute phase equilibria, interfacial properties, and optimize their parameters for vapor-liquid, liquid-liquid, and vapor-liquid-liquid equilibria for multicomponent mixtures. Phasepy implementation, and robustness are illustrated for binary and ternary mixtures.

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Isobaric vapor – liquid – liquid equilibrium for water + MTBE + alcohol (ethanol or 1-butanol) mixtures

Cited by 10 publications

References 49 publications

SGTPy: A Python Code for Calculating the Interfacial Properties of Fluids Based on the Square Gradient Theory Using the SAFT-VR Mie Equation of State

SGTPy: A Python Code for Calculating the Interfacial Properties of Fluids Based on the Square Gradient Theory Using the SAFT-VR Mie Equation of State

Dereplication of Natural Extracts Diluted in Propylene Glycol, 1,3-Propanediol and Glycerin. Comparison of Leontopodium alpinum Cass. (Edelweiss) Extracts as a Case Study

Phasepy: A Python based framework for fluid phase equilibria and interfacial properties computation

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