D. Hartanto
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1
Extractive distillation (ED) is a key technology for separating close-boiling and azeotropic mixtures by introducing an entrainer that modifies intermolecular interactions within the mixture. Through selective affinity toward specific components, the entrainer increases the non-ideality of the system, enhances relative volatility, and eliminates close-boiling and azeotropic behavior. However, conventional entrainers such as N-methyl-2-pyrrolidone (NMP) raise significant environmental and health concerns, including reproductive toxicity. Meanwhile, many greener candidates, including biobased and greener organic entrainers, as well as natural deep eutectic solvents (NADESs), remain insufficiently evaluated for ED applications. Nevertheless, systematic and validated entrainer selection strategies, supported by reliable vapor-liquid equilibrium (VLE) data and rigorous process performance comparisons for the close-boiling methylcyclohexane-toluene mixture and the azeotropic n-hexane-ethanol mixture containing these underexplored greener entrainers, are unavailable. Therefore, this thesis aims to develop a framework for screening greener entrainers, along with generating reliable VLE data and performing process performance comparison, to identify effective alternatives to NMP for these two representative separation challenges.
To achieve this objective, a multi-stage entrainer selection methodology was developed, integrating initial screening, predictive modelling, experimental validation, and process performance comparison. In Chapter 2, potential greener entrainers were screened using an initial screening phase, which identified potential greener entrainers based on high boiling temperatures, favorable solvency, and compliance with green chemistry principles. Subsequently, key separation metrics, such as selectivity and capacity at infinite dilution, and performance index, were predicted using quantum chemical calculations (COSMO-RS). In addition, relative volatility was predicted using both COSMO-RS and group contribution methods (UNIFAC and modified UNIFAC Dortmund). Promising candidates were then evaluated experimentally through miscibility tests and relative volatility measurements. Selected greener entrainer candidates, along with benchmark entrainer NMP in both mixtures, were examined for their vapor-liquid equilibrium (VLE) data. Chapters 3 and 4 focus on generating reliable VLE data for both mixtures in the presence of each selected greener entrainer at various entrainer-to-feed ratios (E/F) and operating pressures. The experimental data were examined through thermodynamic consistency tests. Moreover, the data were regressed using activity coefficient models (NRTL and UNIQUAC) to obtain the optimum binary interaction parameters. In Chapter 5, these parameters were implemented in Aspen Plus V.12 for ED process simulations. Greener entrainers were evaluated according their performance compared to NMP using economic indicator (total annual cost) and sustainability metrics, such as energy requirements, water consumption, and CO2 emissions. In addition, the use and limits of predictive tools for ED entrainer screening were evaluated.
The screening results in Chapter 2 identify promising greening entrainers. For the methylcyclohexane–toluene mixture, gamma-valerolactone (GVL), n-butyl-2-pyrrolidone (NBP), and dimethyl isosorbide (DMI) were selected for VLE data experimental evaluation, while NBP, DMI, and guaiacol were selected for the n-hexane–ethanol mixture. Some NADESs and other biobased and greener organic entrainers exhibited favorable predicted selectivity but showed immiscibility issues in the investigated mixtures and were therefore excluded from further evaluation. In Chapters 3 and 4, the measured VLE data for both mixtures containing each entrainer passed the thermodynamic consistency test, indicating the reliability of the data. The VLE data confirmed that the selected greener entrainers significantly increase the relative volatility of the mixtures and effectively remove close-boiling and azeotropic behavior. Process simulations discussed in Chapter 5 indicate that for the separation of methylcyclohexane-toluene, GVL reduces total annual cost (TAC) by 5.6% compared to NMP, while also having a lower energy intensity of 6.1%. In contrast, DMI and NBP exhibit slightly higher TAC values of 6.2% and 15.2%, respectively, along with slightly higher energy intensity of 3.0% and 18.2%. For CO2 emissions and water consumption, GVL remains comparable to NMP, with both exhibiting values of 0.04-0.05 kgCO2/kgproducts and 0.05 m3water/kgproducts. For the n-hexane-ethanol mixture, NBP shows a comparable TAC, with 1.6% slightly higher than that of NMP, with a 3.1% increase in energy intensity. Meanwhile, guaiacol and DMI demonstrate increasing TAC by 10.9% and 14.0%, respectively, along with energy intensity that are 12.5% and 18.8% higher. In addition, CO2 emissions for these options remain comparable at around 0.05-0.06 kgCO2/kgproducts and water consumption is similar at approximately 0.05-0.07 m3water/kgproducts. Importantly, these greener entrainers have significantly lower toxicity profiles than NMP. Furthermore, the TAC deviation threshold of 32% from predictive models compared to the experimental-based NRTL model makes them suitable for early-stage entrainer screening. However, experimental validation remains necessary for detailed process design.
Overall, this thesis provides a systematic and experimentally validated framework for selecting greener entrainers in extractive distillation. The work delivers new and reliable VLE data along with optimum binary interaction parameters and a comparison of process-level performance. The findings demonstrate that replacing conventional entrainers, such as NMP, with greener alternatives is technically feasible, economically viable, and environmentally sustainable. This supports the transition toward more eco-efficient extractive distillation processes.
...
To achieve this objective, a multi-stage entrainer selection methodology was developed, integrating initial screening, predictive modelling, experimental validation, and process performance comparison. In Chapter 2, potential greener entrainers were screened using an initial screening phase, which identified potential greener entrainers based on high boiling temperatures, favorable solvency, and compliance with green chemistry principles. Subsequently, key separation metrics, such as selectivity and capacity at infinite dilution, and performance index, were predicted using quantum chemical calculations (COSMO-RS). In addition, relative volatility was predicted using both COSMO-RS and group contribution methods (UNIFAC and modified UNIFAC Dortmund). Promising candidates were then evaluated experimentally through miscibility tests and relative volatility measurements. Selected greener entrainer candidates, along with benchmark entrainer NMP in both mixtures, were examined for their vapor-liquid equilibrium (VLE) data. Chapters 3 and 4 focus on generating reliable VLE data for both mixtures in the presence of each selected greener entrainer at various entrainer-to-feed ratios (E/F) and operating pressures. The experimental data were examined through thermodynamic consistency tests. Moreover, the data were regressed using activity coefficient models (NRTL and UNIQUAC) to obtain the optimum binary interaction parameters. In Chapter 5, these parameters were implemented in Aspen Plus V.12 for ED process simulations. Greener entrainers were evaluated according their performance compared to NMP using economic indicator (total annual cost) and sustainability metrics, such as energy requirements, water consumption, and CO2 emissions. In addition, the use and limits of predictive tools for ED entrainer screening were evaluated.
The screening results in Chapter 2 identify promising greening entrainers. For the methylcyclohexane–toluene mixture, gamma-valerolactone (GVL), n-butyl-2-pyrrolidone (NBP), and dimethyl isosorbide (DMI) were selected for VLE data experimental evaluation, while NBP, DMI, and guaiacol were selected for the n-hexane–ethanol mixture. Some NADESs and other biobased and greener organic entrainers exhibited favorable predicted selectivity but showed immiscibility issues in the investigated mixtures and were therefore excluded from further evaluation. In Chapters 3 and 4, the measured VLE data for both mixtures containing each entrainer passed the thermodynamic consistency test, indicating the reliability of the data. The VLE data confirmed that the selected greener entrainers significantly increase the relative volatility of the mixtures and effectively remove close-boiling and azeotropic behavior. Process simulations discussed in Chapter 5 indicate that for the separation of methylcyclohexane-toluene, GVL reduces total annual cost (TAC) by 5.6% compared to NMP, while also having a lower energy intensity of 6.1%. In contrast, DMI and NBP exhibit slightly higher TAC values of 6.2% and 15.2%, respectively, along with slightly higher energy intensity of 3.0% and 18.2%. For CO2 emissions and water consumption, GVL remains comparable to NMP, with both exhibiting values of 0.04-0.05 kgCO2/kgproducts and 0.05 m3water/kgproducts. For the n-hexane-ethanol mixture, NBP shows a comparable TAC, with 1.6% slightly higher than that of NMP, with a 3.1% increase in energy intensity. Meanwhile, guaiacol and DMI demonstrate increasing TAC by 10.9% and 14.0%, respectively, along with energy intensity that are 12.5% and 18.8% higher. In addition, CO2 emissions for these options remain comparable at around 0.05-0.06 kgCO2/kgproducts and water consumption is similar at approximately 0.05-0.07 m3water/kgproducts. Importantly, these greener entrainers have significantly lower toxicity profiles than NMP. Furthermore, the TAC deviation threshold of 32% from predictive models compared to the experimental-based NRTL model makes them suitable for early-stage entrainer screening. However, experimental validation remains necessary for detailed process design.
Overall, this thesis provides a systematic and experimentally validated framework for selecting greener entrainers in extractive distillation. The work delivers new and reliable VLE data along with optimum binary interaction parameters and a comparison of process-level performance. The findings demonstrate that replacing conventional entrainers, such as NMP, with greener alternatives is technically feasible, economically viable, and environmentally sustainable. This supports the transition toward more eco-efficient extractive distillation processes.
...
Extractive distillation (ED) is a key technology for separating close-boiling and azeotropic mixtures by introducing an entrainer that modifies intermolecular interactions within the mixture. Through selective affinity toward specific components, the entrainer increases the non-ideality of the system, enhances relative volatility, and eliminates close-boiling and azeotropic behavior. However, conventional entrainers such as N-methyl-2-pyrrolidone (NMP) raise significant environmental and health concerns, including reproductive toxicity. Meanwhile, many greener candidates, including biobased and greener organic entrainers, as well as natural deep eutectic solvents (NADESs), remain insufficiently evaluated for ED applications. Nevertheless, systematic and validated entrainer selection strategies, supported by reliable vapor-liquid equilibrium (VLE) data and rigorous process performance comparisons for the close-boiling methylcyclohexane-toluene mixture and the azeotropic n-hexane-ethanol mixture containing these underexplored greener entrainers, are unavailable. Therefore, this thesis aims to develop a framework for screening greener entrainers, along with generating reliable VLE data and performing process performance comparison, to identify effective alternatives to NMP for these two representative separation challenges.
To achieve this objective, a multi-stage entrainer selection methodology was developed, integrating initial screening, predictive modelling, experimental validation, and process performance comparison. In Chapter 2, potential greener entrainers were screened using an initial screening phase, which identified potential greener entrainers based on high boiling temperatures, favorable solvency, and compliance with green chemistry principles. Subsequently, key separation metrics, such as selectivity and capacity at infinite dilution, and performance index, were predicted using quantum chemical calculations (COSMO-RS). In addition, relative volatility was predicted using both COSMO-RS and group contribution methods (UNIFAC and modified UNIFAC Dortmund). Promising candidates were then evaluated experimentally through miscibility tests and relative volatility measurements. Selected greener entrainer candidates, along with benchmark entrainer NMP in both mixtures, were examined for their vapor-liquid equilibrium (VLE) data. Chapters 3 and 4 focus on generating reliable VLE data for both mixtures in the presence of each selected greener entrainer at various entrainer-to-feed ratios (E/F) and operating pressures. The experimental data were examined through thermodynamic consistency tests. Moreover, the data were regressed using activity coefficient models (NRTL and UNIQUAC) to obtain the optimum binary interaction parameters. In Chapter 5, these parameters were implemented in Aspen Plus V.12 for ED process simulations. Greener entrainers were evaluated according their performance compared to NMP using economic indicator (total annual cost) and sustainability metrics, such as energy requirements, water consumption, and CO2 emissions. In addition, the use and limits of predictive tools for ED entrainer screening were evaluated.
The screening results in Chapter 2 identify promising greening entrainers. For the methylcyclohexane–toluene mixture, gamma-valerolactone (GVL), n-butyl-2-pyrrolidone (NBP), and dimethyl isosorbide (DMI) were selected for VLE data experimental evaluation, while NBP, DMI, and guaiacol were selected for the n-hexane–ethanol mixture. Some NADESs and other biobased and greener organic entrainers exhibited favorable predicted selectivity but showed immiscibility issues in the investigated mixtures and were therefore excluded from further evaluation. In Chapters 3 and 4, the measured VLE data for both mixtures containing each entrainer passed the thermodynamic consistency test, indicating the reliability of the data. The VLE data confirmed that the selected greener entrainers significantly increase the relative volatility of the mixtures and effectively remove close-boiling and azeotropic behavior. Process simulations discussed in Chapter 5 indicate that for the separation of methylcyclohexane-toluene, GVL reduces total annual cost (TAC) by 5.6% compared to NMP, while also having a lower energy intensity of 6.1%. In contrast, DMI and NBP exhibit slightly higher TAC values of 6.2% and 15.2%, respectively, along with slightly higher energy intensity of 3.0% and 18.2%. For CO2 emissions and water consumption, GVL remains comparable to NMP, with both exhibiting values of 0.04-0.05 kgCO2/kgproducts and 0.05 m3water/kgproducts. For the n-hexane-ethanol mixture, NBP shows a comparable TAC, with 1.6% slightly higher than that of NMP, with a 3.1% increase in energy intensity. Meanwhile, guaiacol and DMI demonstrate increasing TAC by 10.9% and 14.0%, respectively, along with energy intensity that are 12.5% and 18.8% higher. In addition, CO2 emissions for these options remain comparable at around 0.05-0.06 kgCO2/kgproducts and water consumption is similar at approximately 0.05-0.07 m3water/kgproducts. Importantly, these greener entrainers have significantly lower toxicity profiles than NMP. Furthermore, the TAC deviation threshold of 32% from predictive models compared to the experimental-based NRTL model makes them suitable for early-stage entrainer screening. However, experimental validation remains necessary for detailed process design.
Overall, this thesis provides a systematic and experimentally validated framework for selecting greener entrainers in extractive distillation. The work delivers new and reliable VLE data along with optimum binary interaction parameters and a comparison of process-level performance. The findings demonstrate that replacing conventional entrainers, such as NMP, with greener alternatives is technically feasible, economically viable, and environmentally sustainable. This supports the transition toward more eco-efficient extractive distillation processes.
To achieve this objective, a multi-stage entrainer selection methodology was developed, integrating initial screening, predictive modelling, experimental validation, and process performance comparison. In Chapter 2, potential greener entrainers were screened using an initial screening phase, which identified potential greener entrainers based on high boiling temperatures, favorable solvency, and compliance with green chemistry principles. Subsequently, key separation metrics, such as selectivity and capacity at infinite dilution, and performance index, were predicted using quantum chemical calculations (COSMO-RS). In addition, relative volatility was predicted using both COSMO-RS and group contribution methods (UNIFAC and modified UNIFAC Dortmund). Promising candidates were then evaluated experimentally through miscibility tests and relative volatility measurements. Selected greener entrainer candidates, along with benchmark entrainer NMP in both mixtures, were examined for their vapor-liquid equilibrium (VLE) data. Chapters 3 and 4 focus on generating reliable VLE data for both mixtures in the presence of each selected greener entrainer at various entrainer-to-feed ratios (E/F) and operating pressures. The experimental data were examined through thermodynamic consistency tests. Moreover, the data were regressed using activity coefficient models (NRTL and UNIQUAC) to obtain the optimum binary interaction parameters. In Chapter 5, these parameters were implemented in Aspen Plus V.12 for ED process simulations. Greener entrainers were evaluated according their performance compared to NMP using economic indicator (total annual cost) and sustainability metrics, such as energy requirements, water consumption, and CO2 emissions. In addition, the use and limits of predictive tools for ED entrainer screening were evaluated.
The screening results in Chapter 2 identify promising greening entrainers. For the methylcyclohexane–toluene mixture, gamma-valerolactone (GVL), n-butyl-2-pyrrolidone (NBP), and dimethyl isosorbide (DMI) were selected for VLE data experimental evaluation, while NBP, DMI, and guaiacol were selected for the n-hexane–ethanol mixture. Some NADESs and other biobased and greener organic entrainers exhibited favorable predicted selectivity but showed immiscibility issues in the investigated mixtures and were therefore excluded from further evaluation. In Chapters 3 and 4, the measured VLE data for both mixtures containing each entrainer passed the thermodynamic consistency test, indicating the reliability of the data. The VLE data confirmed that the selected greener entrainers significantly increase the relative volatility of the mixtures and effectively remove close-boiling and azeotropic behavior. Process simulations discussed in Chapter 5 indicate that for the separation of methylcyclohexane-toluene, GVL reduces total annual cost (TAC) by 5.6% compared to NMP, while also having a lower energy intensity of 6.1%. In contrast, DMI and NBP exhibit slightly higher TAC values of 6.2% and 15.2%, respectively, along with slightly higher energy intensity of 3.0% and 18.2%. For CO2 emissions and water consumption, GVL remains comparable to NMP, with both exhibiting values of 0.04-0.05 kgCO2/kgproducts and 0.05 m3water/kgproducts. For the n-hexane-ethanol mixture, NBP shows a comparable TAC, with 1.6% slightly higher than that of NMP, with a 3.1% increase in energy intensity. Meanwhile, guaiacol and DMI demonstrate increasing TAC by 10.9% and 14.0%, respectively, along with energy intensity that are 12.5% and 18.8% higher. In addition, CO2 emissions for these options remain comparable at around 0.05-0.06 kgCO2/kgproducts and water consumption is similar at approximately 0.05-0.07 m3water/kgproducts. Importantly, these greener entrainers have significantly lower toxicity profiles than NMP. Furthermore, the TAC deviation threshold of 32% from predictive models compared to the experimental-based NRTL model makes them suitable for early-stage entrainer screening. However, experimental validation remains necessary for detailed process design.
Overall, this thesis provides a systematic and experimentally validated framework for selecting greener entrainers in extractive distillation. The work delivers new and reliable VLE data along with optimum binary interaction parameters and a comparison of process-level performance. The findings demonstrate that replacing conventional entrainers, such as NMP, with greener alternatives is technically feasible, economically viable, and environmentally sustainable. This supports the transition toward more eco-efficient extractive distillation processes.
In extractive distillation for the separation of azeotropic mixtures, eco-friendly solvents have demonstrated potential as greener alternatives to conventional entrainers. However, the absence of thermodynamic data for mixtures that include green solvents presents a significant hurdle to their practical application. This work explores, for the first time, vapor-liquid equilibrium (VLE) data for the azeotropic mixture of n-hexane and ethanol in the presence of the biobased entrainers guaiacol and dimethyl isosorbide (DMI). The VLE measurements were conducted using a Fischer Labodest VLE 502 ebulliometer with varying pressures and entrainer-to-feed ratios (E/Fs). The VLE data met the criteria of the Van Ness method and thereby pass the thermodynamic consistency test. The results confirm that the relative volatility of n-hexane to ethanol is increased by the addition of guaiacol and DMI to the mixture. Moreover, the azeotrope has been successfully removed. The VLE data were well regressed using the Non-Random Two Liquid (NRTL) thermodynamic model, which provided accurate binary interaction parameters (BIPs). The thermodynamic modeling verifies the reliability of the experimental data and its relevance for effective process design, emphasizing the viability of guaiacol and DMI as biobased entrainers for more sustainable and greener extractive distillation.
...
In extractive distillation for the separation of azeotropic mixtures, eco-friendly solvents have demonstrated potential as greener alternatives to conventional entrainers. However, the absence of thermodynamic data for mixtures that include green solvents presents a significant hurdle to their practical application. This work explores, for the first time, vapor-liquid equilibrium (VLE) data for the azeotropic mixture of n-hexane and ethanol in the presence of the biobased entrainers guaiacol and dimethyl isosorbide (DMI). The VLE measurements were conducted using a Fischer Labodest VLE 502 ebulliometer with varying pressures and entrainer-to-feed ratios (E/Fs). The VLE data met the criteria of the Van Ness method and thereby pass the thermodynamic consistency test. The results confirm that the relative volatility of n-hexane to ethanol is increased by the addition of guaiacol and DMI to the mixture. Moreover, the azeotrope has been successfully removed. The VLE data were well regressed using the Non-Random Two Liquid (NRTL) thermodynamic model, which provided accurate binary interaction parameters (BIPs). The thermodynamic modeling verifies the reliability of the experimental data and its relevance for effective process design, emphasizing the viability of guaiacol and DMI as biobased entrainers for more sustainable and greener extractive distillation.
Green solvents have emerged as promising green entrainers to substitute conventional entrainers in extractive distillation to separate azeotropic mixtures. However, the limited availability of thermodynamic data for green-solvent-containing mixtures continues to hinder their practical implementation in this process. This study is the first to report experimental vapor–liquid equilibrium (VLE) data for the n-hexane + ethanol azeotropic system containing the greener entrainer 1-butylpyrrolidin-2-one (NBP) alongside the benchmark entrainer 1-methylpyrrolidin-2-one (NMP). Using a Fischer Labodest VLE602 ebulliometer, VLE measurements were performed at pressures of 50.0 and 100.0 kPa and various entrainer-to-feed ratios (E/F). The reliability of the reported VLE data was tested and confirmed using the Van Ness thermodynamic consistency test. The results show that NBP enhances relative volatility and effectively eliminates the azeotrope, performing comparably to the benchmark entrainer NMP. The nonrandom-two-liquid (NRTL) model was utilized to regress the investigated VLE data and determine the optimum binary interaction parameters (BIPs). As a result, the NRTL model demonstrates good agreement with the experimental data. This thermodynamic modeling confirms the data’s reliability and suitability for process design, highlighting NBP’s potential as an environmentally friendly alternative entrainer in extractive distillation.
...
Green solvents have emerged as promising green entrainers to substitute conventional entrainers in extractive distillation to separate azeotropic mixtures. However, the limited availability of thermodynamic data for green-solvent-containing mixtures continues to hinder their practical implementation in this process. This study is the first to report experimental vapor–liquid equilibrium (VLE) data for the n-hexane + ethanol azeotropic system containing the greener entrainer 1-butylpyrrolidin-2-one (NBP) alongside the benchmark entrainer 1-methylpyrrolidin-2-one (NMP). Using a Fischer Labodest VLE602 ebulliometer, VLE measurements were performed at pressures of 50.0 and 100.0 kPa and various entrainer-to-feed ratios (E/F). The reliability of the reported VLE data was tested and confirmed using the Van Ness thermodynamic consistency test. The results show that NBP enhances relative volatility and effectively eliminates the azeotrope, performing comparably to the benchmark entrainer NMP. The nonrandom-two-liquid (NRTL) model was utilized to regress the investigated VLE data and determine the optimum binary interaction parameters (BIPs). As a result, the NRTL model demonstrates good agreement with the experimental data. This thermodynamic modeling confirms the data’s reliability and suitability for process design, highlighting NBP’s potential as an environmentally friendly alternative entrainer in extractive distillation.
In this work, dimethyl isosorbide (DMI) and 1-butylpyrrolidin-2-one (NBP), as biobased and greener organic solvents, were used for the first time as entrainers in extractive distillation to separate a close-boiling mixture of methylcyclohexane and toluene. Vapor–liquid equilibrium (VLE) data were collected for pseudoternary mixtures consisting of methylcyclohexane and toluene in the presence of DMI and NBP at various entrainer-to-feed ratios (E/F) and pressures. The VLE measurements were conducted by using a Fischer Labodest VLE602 ebulliometer, and the thermodynamic consistency of the data was verified by using the Van Ness test. Both DMI and NBP were found to increase the relative volatility of methylcyclohexane to toluene, successfully eliminating close-boiling behavior. Compared to benchmark entrainers, both outperformed 1-methylpyrrolidin-2-one (NMP) and sulfolane under certain conditions. In comparison with other green entrainers, DMI and NBP showed similar performance to gamma-valerolactone (GVL) and Cyrene under specific conditions. The VLE data were accurately correlated by using the nonrandom two-liquid (NRTL) model.
...
In this work, dimethyl isosorbide (DMI) and 1-butylpyrrolidin-2-one (NBP), as biobased and greener organic solvents, were used for the first time as entrainers in extractive distillation to separate a close-boiling mixture of methylcyclohexane and toluene. Vapor–liquid equilibrium (VLE) data were collected for pseudoternary mixtures consisting of methylcyclohexane and toluene in the presence of DMI and NBP at various entrainer-to-feed ratios (E/F) and pressures. The VLE measurements were conducted by using a Fischer Labodest VLE602 ebulliometer, and the thermodynamic consistency of the data was verified by using the Van Ness test. Both DMI and NBP were found to increase the relative volatility of methylcyclohexane to toluene, successfully eliminating close-boiling behavior. Compared to benchmark entrainers, both outperformed 1-methylpyrrolidin-2-one (NMP) and sulfolane under certain conditions. In comparison with other green entrainers, DMI and NBP showed similar performance to gamma-valerolactone (GVL) and Cyrene under specific conditions. The VLE data were accurately correlated by using the nonrandom two-liquid (NRTL) model.
The isobaric vapor–liquid equilibrium (VLE) data of the binary mixture of methylcyclohexane (1) + toluene (2) at 101.3 kPa; the pseudoternary mixture of methylcyclohexane (1) + toluene (2) + gamma-valerolactone (GVL) (3) with the entrainer-to-feed ratio (E/F) = 1 (mass basis) at 50, 80, and 100 kPa, and E/F = 2 and 3 at 100 kPa; and the pseudoternary mixture of methylcyclohexane (1) + toluene (2) + 1-methylpyrrolidin-2-one (NMP) (3) with E/F = 1 at 100 kPa were measured using a Fischer Labodest VLE602 ebulliometer. The reliability of the experimental VLE data was tested and confirmed by Van Ness and Fredenslund thermodynamic consistency tests. The experimental results indicate that the presence of GVL and NMP increases the relative volatility of methylcyclohexane to toluene; therefore, both entrainers remove a close-boiling behavior in the mixture. Non-random two-liquid (NRTL) and universal quasi chemical (UNIQUAC) thermodynamic models were applied in the experimental data correlation to obtain the optimum binary interaction parameters. For the mixture involving GVL, the experimental VLE data were accurately correlated by NRTL and UNIQUAC. However, NRTL has more accurate results compared with UNIQUAC. For the mixture containing NMP, both the UNIQUAC and NRTL models show favorable regression results.
...
The isobaric vapor–liquid equilibrium (VLE) data of the binary mixture of methylcyclohexane (1) + toluene (2) at 101.3 kPa; the pseudoternary mixture of methylcyclohexane (1) + toluene (2) + gamma-valerolactone (GVL) (3) with the entrainer-to-feed ratio (E/F) = 1 (mass basis) at 50, 80, and 100 kPa, and E/F = 2 and 3 at 100 kPa; and the pseudoternary mixture of methylcyclohexane (1) + toluene (2) + 1-methylpyrrolidin-2-one (NMP) (3) with E/F = 1 at 100 kPa were measured using a Fischer Labodest VLE602 ebulliometer. The reliability of the experimental VLE data was tested and confirmed by Van Ness and Fredenslund thermodynamic consistency tests. The experimental results indicate that the presence of GVL and NMP increases the relative volatility of methylcyclohexane to toluene; therefore, both entrainers remove a close-boiling behavior in the mixture. Non-random two-liquid (NRTL) and universal quasi chemical (UNIQUAC) thermodynamic models were applied in the experimental data correlation to obtain the optimum binary interaction parameters. For the mixture involving GVL, the experimental VLE data were accurately correlated by NRTL and UNIQUAC. However, NRTL has more accurate results compared with UNIQUAC. For the mixture containing NMP, both the UNIQUAC and NRTL models show favorable regression results.
Green organic entrainers and natural deep eutectic solvents (NADESs) possessing high boiling points and decomposition temperatures, exhibit considerable potential as advanced materials for green entrainers in extractive distillation. However, there is a wide range of solvents to choose from and their properties are only rarely available for use in process design and simulation. The present study aims to assess the selection parameters and examine the performance of and select green organic entrainers and NADESs for the separation of the close boiling mixture methylcyclohexane-toluene. The evaluation carried out was based on selectivity and relative volatility values obtained by using predictive models. COSMO-RS (a unimolecular quantum chemical calculation) was employed to predict the selectivity at infinite dilution, while group contribution methods such as UNIFAC and modified UNIFAC (Dortmund) were used to predict the relative volatility. According to the calculated results, the selectivity appeared a more important selection parameter than the performance index. The relative volatility prediction using the UNIFAC and UNIFAC Dortmund methods exhibits comparable trends to the selectivity results derived from COSMO-RS. However, the use of UNIFAC and modified UNIFAC (Dortmund) in predicting the relative volatility of NADES containing mixtures is limited due to the absence of functional group parameters. This CAPE study reveals that, based on the calculated selectivity (using COSMO-RS) and relative volatility (using UNIFAC, and modified UNIFAC (Dortmund)), most of the proposed green organic entrainers and NADESs exhibit a higher or comparable selectivity and relative volatility as the benchmark entrainers. This confirms the potential of the evaluated green entrainers with higher selectivity and relative volatility to enhance the design of extractive distillation. Therefore, the cost, energy and water consumption, as well as CO2 emissions in the methylcyclohexane and toluene separation can be reduced.
...
Green organic entrainers and natural deep eutectic solvents (NADESs) possessing high boiling points and decomposition temperatures, exhibit considerable potential as advanced materials for green entrainers in extractive distillation. However, there is a wide range of solvents to choose from and their properties are only rarely available for use in process design and simulation. The present study aims to assess the selection parameters and examine the performance of and select green organic entrainers and NADESs for the separation of the close boiling mixture methylcyclohexane-toluene. The evaluation carried out was based on selectivity and relative volatility values obtained by using predictive models. COSMO-RS (a unimolecular quantum chemical calculation) was employed to predict the selectivity at infinite dilution, while group contribution methods such as UNIFAC and modified UNIFAC (Dortmund) were used to predict the relative volatility. According to the calculated results, the selectivity appeared a more important selection parameter than the performance index. The relative volatility prediction using the UNIFAC and UNIFAC Dortmund methods exhibits comparable trends to the selectivity results derived from COSMO-RS. However, the use of UNIFAC and modified UNIFAC (Dortmund) in predicting the relative volatility of NADES containing mixtures is limited due to the absence of functional group parameters. This CAPE study reveals that, based on the calculated selectivity (using COSMO-RS) and relative volatility (using UNIFAC, and modified UNIFAC (Dortmund)), most of the proposed green organic entrainers and NADESs exhibit a higher or comparable selectivity and relative volatility as the benchmark entrainers. This confirms the potential of the evaluated green entrainers with higher selectivity and relative volatility to enhance the design of extractive distillation. Therefore, the cost, energy and water consumption, as well as CO2 emissions in the methylcyclohexane and toluene separation can be reduced.