Liquid−Liquid(−Liquid) Equilibria in Ternary Systems of Water + Cyclohexylamine + Aromatic Hydrocarbon (Toluene or Propylbenzene) or Aliphatic Hydrocarbon (Heptane or Octane)

Klauck, Mandy; Grenner, and Andreas; Schmelzer, Jürgen

doi:10.1021/je050520f

Cited by 23 publications

(36 citation statements)

References 16 publications

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“…Furthermore, and when considering HYSYS V9 with the non-zero BIPs as reported in Table 4, predicts a phase splitting behavior. Nevertheless, the ∆G mix /RT differs significantly from the other ∆G mix /RT calculated with Aspen Plus V9 and Klauck et al [30] BIPs.…”

Section: Theoretical Discussion Of Model Discrepancycontrasting

confidence: 57%

“…Figure 4 reports the ∆G L mix using the NRTL model at 70 • C and 100 • C. One should note that the temperatures selected were one lower, and the other higher than the Three Phases Region (TPR) at 1 atm, as reported by Tu et al [24]. Concerning the BIP (Binary Interaction Parameters), the ones from HYSYS V9, Aspen Plus V9, and Klauck et al [30] were used. In the case of HYSYS V9, two cases were considered: (a) the BIPs parameters for HYSYS V9 were set at the zero default values and (b) the BIPs were estimated by HYSYS V9 assuming liquid phase immiscibility.…”

Section: Theoretical Discussion Of Model Discrepancymentioning

confidence: 99%

“…With this end, a NTRL thermodynamic model was chosen for the various calculations. This model was programmed using Python, with the Gibbs free energy analysis considered using binary interaction parameters (BIP) from HYSYS V9, Aspen Plus V9 and the technical literature [30,37]. The aim was to better models leading to two-phase simulations, predicting vapor pressures and three phases region.…”

Section: Model Boiling Point Differencementioning

confidence: 99%

See 2 more Smart Citations

Thermodynamics and Machine Learning Based Approaches for Vapor–Liquid–Liquid Phase Equilibria in n-Octane/Water, as a Naphtha–Water Surrogate in Water Blends

et al. 2021

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The prediction of phase equilibria for hydrocarbon/water blends in separators, is a subject of considerable importance for chemical processes. Despite its relevance, there are still pending questions. Among them, is the prediction of the correct number of phases. While a stability analysis using the Gibbs Free Energy of mixing and the NRTL model, provide a good understanding with calculation issues, when using HYSYS V9 and Aspen Plus V9 software, this shows that significant phase equilibrium uncertainties still exist. To clarify these matters, n-octane and water blends, are good surrogates of naphtha/water mixtures. Runs were developed in a CREC vapor–liquid (VL_ Cell operated with octane–water mixtures under dynamic conditions and used to establish the two-phase (liquid–vapor) and three phase (liquid–liquid–vapor) domains. Results obtained demonstrate that the two phase region (full solubility in the liquid phase) of n-octane in water at 100 °C is in the 10-4 mol fraction range, and it is larger than the 10-5 mol fraction predicted by Aspen Plus and the 10-7 mol fraction reported in the technical literature. Furthermore, and to provide an effective and accurate method for predicting the number of phases, a machine learning (ML) technique was implemented and successfully demonstrated, in the present study.

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Section: Theoretical Discussion Of Model Discrepancycontrasting

confidence: 57%

Section: Theoretical Discussion Of Model Discrepancymentioning

confidence: 99%

Section: Model Boiling Point Differencementioning

confidence: 99%

See 1 more Smart Citation

Thermodynamics and Machine Learning Based Approaches for Vapor–Liquid–Liquid Phase Equilibria in n-Octane/Water, as a Naphtha–Water Surrogate in Water Blends

et al. 2021

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“…The average values of standard deviation of the measurements for unstirred aqueous-organic solutions and unstirred mixtures of flammable solvents is around 1.4 and 2.5 • C, respectively, both of which are greater than those of the complete stirring analogues, around 0.7 • C. Liquid-phase activity coefficients were estimated using the NRTL [26] and/or UNIQUAC equations [27]. Binary interaction parameters obtained either from the LLE or VLE data were used in this study, with parameters adopted from the literature [8,10,[28][29][30][31][32][33][34][35][36] (Tables 3 and 4). The parameters for relative van der Waals volume (r) and the surface area (q) for the pure components needed in the UNIQUAC equation were obtained from the literature [33,37] and are listed in Table 5 along with the Antoine coefficients sourced from the literature [34][35][36].…”

Section: Parameters Used In This Manuscriptmentioning

confidence: 99%

Effect of stirring on the safety of flammable liquid mixtures

Liaw

Gerbaud

Chen

et al. 2010

Journal of Hazardous Materials

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Flash point is the most important variable employed to characterize fire and explosion hazard of liquids. The models developed for predicting the flash point of partially miscible mixtures in the literature to date are all based on the assumption of liquid-liquid equilibrium. In real-world environments, however, the liquid-liquid equilibrium assumption does not always hold, such as the collection or accumulation of waste solvents without stirring, where complete stirring for a period of time is usually used to ensure the liquid phases being in equilibrium. This study investigated the effect of stirring on the flash-point behavior of binary partially miscible mixtures. Two series of partially miscible binary mixtures were employed to elucidate the effect of stirring. The first series was aqueous-organic mixtures, including water+1-butanol, water+2-butanol, water+isobutanol, water+1-pentanol, and water+octane; the second series was the mixtures of two flammable solvents, which included methanol+decane, methanol+2,2,4-trimethylpentane, and methanol+octane. Results reveal that for binary aqueous-organic solutions the flash-point values of unstirred mixtures were located between those of the completely stirred mixtures and those of the flammable component. Therefore, risk assessment could be done based on the flammable component flash-point value. However, for the assurance of safety, it is suggested to completely stir those mixtures before handling to reduce the risk.

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“…This modeling has been considered by de Loos et al [21] for the ternary system water-oil-C 7 E 5 ; by Schmelzer et al [22][23][24][25] for ternary systems water-oil-phenols [22,23] and systems containing aniline or cyclohexylamine [24,25]; and by Revellame et al [26] who investigated the possibility of using solvent extraction to recover lipids from microbial sources for renewable fuel applications. Most of the predictions of three-phase equilibria with interaction parameters obtained from binary systems do not adequately represent all the regions of the phase diagrams.…”

Section: Introductionmentioning

confidence: 99%

Correlation of three-liquid-phase equilibria involving ionic liquids

Rodríguez-Escontrela

Arce

Soto

et al. 2016

Phys. Chem. Chem. Phys.

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The difficulty of achieving a good thermodynamic description of phase equilibria is finding a model that can be extended to a large variety of chemical families and conditions. This problem gets worse in the case of systems containing more than two phases or involving complex compounds such as ionic liquids. However, there are interesting applications that involve multiphasic systems, and the promising features of ionic liquids suggest that they will play an important role in many future processes. In this work, for the first time, the simultaneous correlation of liquid-liquid and liquidliquid-liquid equilibrium data for ternary systems involving ionic liquids has been carried out. To that end, the phase diagram for the system water + [P 6 6 6 14 ][DCA] + hexane has been determined at 298.15 K and 323.15 K and atmospheric pressure. The importance of this system lies in the possibility of using the surface active ionic liquid to improve surfactant enhanced oil recovery methods. With those and previous measurements, thirteen sets of equilibrium data of ternary systems water + ionic liquid + oil have been correlated. The isoactivity equilibrium condition, using the NRTL model, and some pivotal strategies are proposed to correlate these complex systems.Good agreement has been found between experimental and calculated data in all the regions (one triphasic and two biphasic) of the diagrams. The geometric aspects related to the Gibbs energy of mixing function obtained with the model, together with the minor common tangent plane equilibrium condition, are valuable tools to check the consistency of the obtained correlation results.

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Liquid−Liquid(−Liquid) Equilibria in Ternary Systems of Water + Cyclohexylamine + Aromatic Hydrocarbon (Toluene or Propylbenzene) or Aliphatic Hydrocarbon (Heptane or Octane)

Cited by 23 publications

References 16 publications

Thermodynamics and Machine Learning Based Approaches for Vapor–Liquid–Liquid Phase Equilibria in n-Octane/Water, as a Naphtha–Water Surrogate in Water Blends

Thermodynamics and Machine Learning Based Approaches for Vapor–Liquid–Liquid Phase Equilibria in n-Octane/Water, as a Naphtha–Water Surrogate in Water Blends

Effect of stirring on the safety of flammable liquid mixtures

Correlation of three-liquid-phase equilibria involving ionic liquids

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