Effect of ionic liquids on the isobaric vapor–liquid equilibrium behavior of dichloromethane + methanol at 101.3 kPa

Luo, Chengjingyan; Yue, Kun; Qiao, Ruiqi; Li, Chunjiang; Zhou, Jun; Li, Qunsheng

doi:10.1016/j.molliq.2017.08.083

Cited by 21 publications

(9 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The activity coefficient (γ i ) and the relative volatility (α 12 ) were introduced into the study, and they could intuitively show the change of separation ability. − When the value of relative volatility was 1, the system could not be completely separated by ordinary distillation. Taking the ideality of the gas phase into account, the equations of γ i and α 12 were given as follows where x i and y i are the mole fractions of component i in liquid phase and vapor phase, respectively, P represents the pressure of the system (atmospheric pressure, kPa), P i s is the saturated vapor pressure at the operating temperature for component i (kPa); what is more, it can be obtained using Antoine’s equation, in which there were three parameters, as shown in the following equation where P i s is the saturated vapor pressure at operating temperature (mmHg) and t represents the temperature (°C) (Table ).…”

Section: Resultsmentioning

confidence: 99%

“…There are many parameters that can be used to evaluate the accuracy of fitting data, including absolute deviation of vapor phase (δ y ), standard deviation of vapor phase (σ y ), absolute deviation of temperature (δ T ), standard deviation of temperature (σ T ), and the average relative deviation (ARD). Their formulas are listed below, ,, and their calculated values are given in Table Where exptl and calcd represent experimental data and calculated data, respectively, n and m are the number of original data and parameters to be associated, respectively, y is the concentration of component i in the gas phase, T is the temperature of the system, and γ is the activity coefficient.…”

Section: Data Fittingmentioning

confidence: 99%

See 1 more Smart Citation

Vapor–Liquid Equilibrium Experiment and Process Simulation for Methanol and Ethyl Formate at 101.3 kPa

Han

Wang

et al. 2021

J. Chem. Eng. Data

Self Cite

View full text Add to dashboard Cite

As there is an azeotropic point between methanol and ethyl formate, they cannot be completely separated by ordinary distillation. In this paper, extractive distillation was applied and dimethyl sulfoxide (DMSO) and ethylene glycol (EG) were used as entrainers. Vapor−liquid equilibrium (VLE) data for methanol−ethyl formate, methanol−ethyl formate−DMSO, and methanol− ethyl formate−EG were measured at 101.3 kPa, and the NRTL model was applied for data fitting. It was found that the experimental value and the calculated value were accordant well through the deviation value. Then, the NRTL model was used for simulation by Aspen Plus to achieve the separation goal, and it verified the feasibility of the experimental scheme.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Data Fittingmentioning

confidence: 99%

Vapor–Liquid Equilibrium Experiment and Process Simulation for Methanol and Ethyl Formate at 101.3 kPa

Han

Wang

et al. 2021

J. Chem. Eng. Data

Self Cite

View full text Add to dashboard Cite

show abstract

“…Vapor–liquid phase diagram of (a) {methanol-acetonitrile/butanone/tetrahydrofuran/dichloromethane-[C4MIm][Tf2N]} − and (b) {methanol/ethanol-tetrahydrofuran-[C4MIm][BF4]}. , …”

Section: Resultsmentioning

confidence: 99%

Comprehensive Evaluation of COSMO-RS for Predicting Ternary and Binary Ionic Liquid-Containing Vapor–Liquid Equilibria

Qin

Wang

Zhou

et al. 2021

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

To develop efficient ionic liquid (IL)-based separation processes like extractive distillation, the knowledge of IL-involved vapor–liquid equilibria (VLE) is necessary. Since experimental measurements are usually time-consuming and expensive, reliable models for VLE prediction are highly desirable. In this work, the predictive performance of COSMO-RS is systematically evaluated for ternary and binary IL-containing VLE systems. A large experimental VLE database is established from the literature, including 6531 and 2265 data points for ternary and binary systems, respectively. The ternary and binary VLE systems are divided into five and three subsets based on the varieties of molecular solutes. The COSMO-RS performance in capturing the effects of IL and solute structures, IL dosage, and temperature on VLE is analyzed. COSMO-RS provides generally qualitative and in some cases quantitative description of the VLE behaviors and thus could be used as a valuable tool for prior IL screening and process analysis for related separations.

show abstract

“…The selection of an appropriate thermodynamic model is important for accurate simulation. Different predicted VLE data (at 1 atm) of various built-in thermodynamic models in Aspen are compared with two sets of different experimental data , on the basis of their calculated root-mean-square deviations (RMSDs), as shown in Table S1. The vapor–liquid equilibrium diagram and T – xy diagram for dichloromethane–methanol is shown in Figure S1.…”

Section: Process Studymentioning

confidence: 99%

Extractive Dividing-Wall Column Distillation with a Novel Control Structure Integrating Pressure Swing and Pressure Compensation

Jing

Zhu

Dang

et al. 2021

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

In this work, an energy-efficient extractive dividingwall column process with heat integration (E-DWC-HI) is proposed for the first time to separate the dichloromethane (DCM)−methanol (MeOH) azeotrope, which is a widely existing waste effluent in the pharmaceutical industry. The result of economic evaluation shows that the E-DWC-HI process is a preferred choice for the separation of DCM−MeOH mixture. Designing a robust control strategy is essential for the E-DWC-HI process. Thus, four control structures are proposed and tested under the disturbances of ±20% feed flow rate and ±5% feed composition. The basic control structure (CS1) and the double temperature difference control structure (CS2) both have a fixed vapor split. The dynamic response shows that the required purity cannot be met due to the loss of an important control degree of freedom. In CS3, variable vapor split is carried out by adjusting the pressures on the two sides of the dividing wall, and all product purities are held close to their set points except for MeOH product purity with an obvious offset. The dynamic performance of CS4 has been significantly improved by integrating pressure swing and pressure compensation. The offset of MeOH product purity is significantly reduced from 2.05 to 0.03%.

show abstract

Effect of ionic liquids on the isobaric vapor–liquid equilibrium behavior of dichloromethane + methanol at 101.3 kPa

Cited by 21 publications

References 24 publications

Vapor–Liquid Equilibrium Experiment and Process Simulation for Methanol and Ethyl Formate at 101.3 kPa

Vapor–Liquid Equilibrium Experiment and Process Simulation for Methanol and Ethyl Formate at 101.3 kPa

Comprehensive Evaluation of COSMO-RS for Predicting Ternary and Binary Ionic Liquid-Containing Vapor–Liquid Equilibria

Extractive Dividing-Wall Column Distillation with a Novel Control Structure Integrating Pressure Swing and Pressure Compensation

Contact Info

Product

Resources

About