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A stable solution method for natural gas density across a wide temperature range using the GERG-2008 equation of state
IF 2.8 3区 工程技术 Q3 CHEMISTRY, PHYSICAL Pub Date : 2025-01-07 DOI: 10.1016/j.fluid.2024.114328
Wenlong Jia, Xiujuan Wang, Xia Wu, Changjun Li, Fan Yang, Yupeng Liao
The GERG-2008 Equation of State (EoS) is recommended by ISO 20765–2 for computing the physical properties of natural gas. Due to the non-monotonic relationship between pressure and molar density described by the GERG-2008 EoS under low temperature conditions, multiple density solutions may exist, making the precise determination of density challenging. This paper first investigates the variation of molar densities with pressure at different temperatures. When the temperature is above Tr(x)(The composition-dependent reducing functions of the mixture temperature), the pressure described by the GERG-2008 EoS increases monotonically with the molar density, and only one molar density solution that satisfies the equation exists. However, when the temperature is below Tr(x), the pressure described by GERG-2008 EoS no longer changes monotonically with the increase in molar density, resulting in multiple molar density solutions that satisfy the equation. To address this problem, this paper proposes a novel solution method that employs a combination of one-dimensional search and the Newton-Raphson iteration to obtain the required molar density solutions. The true molar density solution is then determined based on the Gibbs free energy criterion, ensuring the correct molar density solution is obtained across a wide temperature range. A total of 903 sets of natural gas density data, covering pressures from 0 to 200 MPa and temperatures from 100 to 450 K, were used to validate this method. The computational results indicate that, when the temperature is aboveTr(x), the average relative deviation (ARD) between the calculated density values and the experimental values ranges from 0.1 % to 0.59 %. For temperatures below Tr(x), the ARD values using this method range from 0.01 % to 0.39 %. The proposed solution method enhances the stability and accuracy of solving the GERG-2008 equation, particularly for natural gas at low temperatures.
{"title":"A stable solution method for natural gas density across a wide temperature range using the GERG-2008 equation of state","authors":"Wenlong Jia,&nbsp;Xiujuan Wang,&nbsp;Xia Wu,&nbsp;Changjun Li,&nbsp;Fan Yang,&nbsp;Yupeng Liao","doi":"10.1016/j.fluid.2024.114328","DOIUrl":"10.1016/j.fluid.2024.114328","url":null,"abstract":"<div><div>The GERG-2008 Equation of State (EoS) is recommended by ISO 20765–2 for computing the physical properties of natural gas. Due to the non-monotonic relationship between pressure and molar density described by the GERG-2008 EoS under low temperature conditions, multiple density solutions may exist, making the precise determination of density challenging. This paper first investigates the variation of molar densities with pressure at different temperatures. When the temperature is above <span><math><mrow><msub><mi>T</mi><mi>r</mi></msub><mrow><mo>(</mo><mi>x</mi><mo>)</mo></mrow><mspace></mspace></mrow></math></span>(The composition-dependent reducing functions of the mixture temperature), the pressure described by the GERG-2008 EoS increases monotonically with the molar density, and only one molar density solution that satisfies the equation exists. However, when the temperature is below <span><math><mrow><msub><mi>T</mi><mi>r</mi></msub><mrow><mo>(</mo><mi>x</mi><mo>)</mo></mrow><mspace></mspace></mrow></math></span>, the pressure described by GERG-2008 EoS no longer changes monotonically with the increase in molar density, resulting in multiple molar density solutions that satisfy the equation. To address this problem, this paper proposes a novel solution method that employs a combination of one-dimensional search and the Newton-Raphson iteration to obtain the required molar density solutions. The true molar density solution is then determined based on the Gibbs free energy criterion, ensuring the correct molar density solution is obtained across a wide temperature range. A total of 903 sets of natural gas density data, covering pressures from 0 to 200 MPa and temperatures from 100 to 450 K, were used to validate this method. The computational results indicate that, when the temperature is above<span><math><mrow><msub><mi>T</mi><mi>r</mi></msub><mrow><mo>(</mo><mi>x</mi><mo>)</mo></mrow><mspace></mspace></mrow></math></span>, the average relative deviation (ARD) between the calculated density values and the experimental values ranges from 0.1 % to 0.59 %. For temperatures below <span><math><mrow><msub><mi>T</mi><mi>r</mi></msub><mrow><mo>(</mo><mi>x</mi><mo>)</mo></mrow><mspace></mspace></mrow></math></span>, the ARD values using this method range from 0.01 % to 0.39 %. The proposed solution method enhances the stability and accuracy of solving the GERG-2008 equation, particularly for natural gas at low temperatures.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"593 ","pages":"Article 114328"},"PeriodicalIF":2.8,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143138877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Density gradients in aqueous salt solutions: A challenging calculation for electrolyte equations of state
IF 2.8 3区 工程技术 Q3 CHEMISTRY, PHYSICAL Pub Date : 2025-01-04 DOI: 10.1016/j.fluid.2024.114327
Iván Cubilla , Marcos Cáceres , Christian E. Schaerer , Marcelo Castier
In clinical laboratories around the world, isopycnic separations are routinely used to separate biological materials based on density differences. One of the techniques to form a density gradient for such separations is to centrifuge an aqueous salt solution. The high angular speeds, salt concentration and pressure can reach high values, creating challenging conditions for the modeling of centrifugation equilibrium. This paper addresses this problem and presents a formulation and a solution procedure for determining the thermodynamic equilibrium of electrolyte solutions during centrifugation. This is accomplished by a nested-loop algorithm; the outer loop iterates on the liquid volume; the inner loop minimizes the Helmholtz function at the given temperature and component amounts, for the current volume value. The Helmholtz function is evaluated as the summation of an intrinsic contribution given by the eSAFT-VR Mie equation of state, an external contribution of the centrifugal field, and induced electrostatic contribution associated with the possible displacement of charged species in the system. In general, qualitative agreement between the experimental and calculated density profiles was observed in the three systems studied.
{"title":"Density gradients in aqueous salt solutions: A challenging calculation for electrolyte equations of state","authors":"Iván Cubilla ,&nbsp;Marcos Cáceres ,&nbsp;Christian E. Schaerer ,&nbsp;Marcelo Castier","doi":"10.1016/j.fluid.2024.114327","DOIUrl":"10.1016/j.fluid.2024.114327","url":null,"abstract":"<div><div>In clinical laboratories around the world, isopycnic separations are routinely used to separate biological materials based on density differences. One of the techniques to form a density gradient for such separations is to centrifuge an aqueous salt solution. The high angular speeds, salt concentration and pressure can reach high values, creating challenging conditions for the modeling of centrifugation equilibrium. This paper addresses this problem and presents a formulation and a solution procedure for determining the thermodynamic equilibrium of electrolyte solutions during centrifugation. This is accomplished by a nested-loop algorithm; the outer loop iterates on the liquid volume; the inner loop minimizes the Helmholtz function at the given temperature and component amounts, for the current volume value. The Helmholtz function is evaluated as the summation of an intrinsic contribution given by the eSAFT-VR Mie equation of state, an external contribution of the centrifugal field, and induced electrostatic contribution associated with the possible displacement of charged species in the system. In general, qualitative agreement between the experimental and calculated density profiles was observed in the three systems studied.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"592 ","pages":"Article 114327"},"PeriodicalIF":2.8,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143155495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Bubble points and densities of H2 (up to ∼ 5%) in CO2-rich binary systems
IF 2.8 3区 工程技术 Q3 CHEMISTRY, PHYSICAL Pub Date : 2025-01-03 DOI: 10.1016/j.fluid.2024.114321
Franklin Okoro, Friday Junior Owuna, Antonin Chapoy, Pezhman Ahmadi, Rod Burgass
In this study, experimental measurements of the bubble points of binary mixtures containing varying concentrations of CO2 (99.5 %, 99 %, 98.5 %,98 %, and ∼ 95 %) with hydrogen (H2) were made. These measurements were carried out from low temperatures (240.20 K) up to 294.84 K (with uncertainties of 0.14 K) using the constant composition expansion method. The experimental data were used to validate two thermodynamic models - the Peng-Robinson and Multi-Fluid Helmholtz Energy Approximation Equation of state (PR-EoS and MFHEA-EoS). From the results, the presence of H2 in CO2 at concentrations between 0.5 and 5 % caused a significant (∼19–980 %) positive deviation from the phase behaviour of CO2 stream compared to that of pure CO2. This effect intensified with higher concentrations of H2 and decreased with rising temperatures. Both models demonstrated good agreement with the experimental bubble point data, exhibiting <4 % average deviation for the system. Notably, the PR-EoS outperformed the MFHEA-EoS, showing <3 % average deviation. Densities of CO2 (99.5 %) with H2 were measured at 278.14, 298.34, 323.55, and 348.40 K and pressures up to 35 MPa. While the densities of CO2 (94.99 %) with H2 were measured at 278.06, 288.13, 298.26, and 323.53 K and pressures up to 35 MPa using a vibrating tube densimeter which was calibrated using water and hydrogen. For the 99.5 % CO2 binary mixture, the average absolute relative deviations (AARD) of the model predictions were 0.09 % and 0.26 % against MFHEA and PR EoS respectively. The AARD of the model predictions for the 94.99 % CO2 were 0.33 % and 1.49 % with MFHEA and PR EoS respectively. Furthermore, even at low concentrations (0.5 %), the presence of H2 led to a substantial reduction (>35 %) in the density of the mixture compared to that of pure CO2 at lower pressure conditions with this effect becoming more pronounced at higher temperatures and concentrations of H2. Both models predicted the densities of the system well (with <2 % deviations from the experimental data), though MFHEA-Eos was more accurate with <0.4 % maximum relative deviation (MaxRD) for all the data points.
{"title":"Bubble points and densities of H2 (up to ∼ 5%) in CO2-rich binary systems","authors":"Franklin Okoro,&nbsp;Friday Junior Owuna,&nbsp;Antonin Chapoy,&nbsp;Pezhman Ahmadi,&nbsp;Rod Burgass","doi":"10.1016/j.fluid.2024.114321","DOIUrl":"10.1016/j.fluid.2024.114321","url":null,"abstract":"<div><div>In this study, experimental measurements of the bubble points of binary mixtures containing varying concentrations of CO<sub>2</sub> (99.5 %, 99 %, 98.5 %,98 %, and ∼ 95 %) with hydrogen (H<sub>2</sub>) were made. These measurements were carried out from low temperatures (240.20 K) up to 294.84 K (with uncertainties of 0.14 K) using the constant composition expansion method. The experimental data were used to validate two thermodynamic models - the Peng-Robinson and Multi-Fluid Helmholtz Energy Approximation Equation of state (PR-EoS and MFHEA-EoS). From the results, the presence of H<sub>2</sub> in CO<sub>2</sub> at concentrations between 0.5 and 5 % caused a significant (∼19–980 %) positive deviation from the phase behaviour of CO<sub>2</sub> stream compared to that of pure CO<sub>2</sub>. This effect intensified with higher concentrations of H<sub>2</sub> and decreased with rising temperatures. Both models demonstrated good agreement with the experimental bubble point data, exhibiting &lt;4 % average deviation for the system. Notably, the PR-EoS outperformed the MFHEA-EoS, showing &lt;3 % average deviation. Densities of CO<sub>2</sub> (99.5 %) with H<sub>2</sub> were measured at 278.14, 298.34, 323.55, and 348.40 K and pressures up to 35 MPa. While the densities of CO<sub>2</sub> (94.99 %) with H<sub>2</sub> were measured at 278.06, 288.13, 298.26, and 323.53 K and pressures up to 35 MPa using a vibrating tube densimeter which was calibrated using water and hydrogen. For the 99.5 % CO<sub>2</sub> binary mixture, the average absolute relative deviations (AARD) of the model predictions were 0.09 % and 0.26 % against MFHEA and PR EoS respectively. The AARD of the model predictions for the 94.99 % CO<sub>2</sub> were 0.33 % and 1.49 % with MFHEA and PR EoS respectively. Furthermore, even at low concentrations (0.5 %), the presence of H<sub>2</sub> led to a substantial reduction (&gt;35 %) in the density of the mixture compared to that of pure CO<sub>2</sub> at lower pressure conditions with this effect becoming more pronounced at higher temperatures and concentrations of H<sub>2</sub>. Both models predicted the densities of the system well (with &lt;2 % deviations from the experimental data), though MFHEA-Eos was more accurate with &lt;0.4 % maximum relative deviation (MaxRD) for all the data points.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"592 ","pages":"Article 114321"},"PeriodicalIF":2.8,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143155498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Studying the influence of temperature on the thermodynamic, structural, and dynamic properties of 11 recently reparametrized rigid water models via molecular dynamics simulations
IF 2.8 3区 工程技术 Q3 CHEMISTRY, PHYSICAL Pub Date : 2025-01-03 DOI: 10.1016/j.fluid.2024.114329
Adnan Jaradat, Khadeejeh Abudalbouh, Ali Al-Mahmoud, Rakan Alsalman, Abdalla Obeidat
Molecular dynamics simulations were conducted to investigate 11 recently reparametrized 3-site, 4-site, and 5-site rigid water models, including TIP4P/ε, OPC, TIP3P-FB, TIP4P-FB, TIP4P-D, SPC/ε, OPC3, TIP5P-2018, TIP3P-ST, TIP4P-ST, and FBA/ε. The study focused on the effects of temperature on the thermodynamic, structural, and dynamic properties of water. A wide range of physical properties was examined using both slab and closed systems across temperatures ranging from 270 to 630 Kelvin. The results were compared with older rigid and non-rigid water models. Among the models tested, TIP4P-FB demonstrated the best overall performance, while OPC3 was identified as the most accurate among the 3-site models tested in this study.
{"title":"Studying the influence of temperature on the thermodynamic, structural, and dynamic properties of 11 recently reparametrized rigid water models via molecular dynamics simulations","authors":"Adnan Jaradat,&nbsp;Khadeejeh Abudalbouh,&nbsp;Ali Al-Mahmoud,&nbsp;Rakan Alsalman,&nbsp;Abdalla Obeidat","doi":"10.1016/j.fluid.2024.114329","DOIUrl":"10.1016/j.fluid.2024.114329","url":null,"abstract":"<div><div>Molecular dynamics simulations were conducted to investigate 11 recently reparametrized 3-site, 4-site, and 5-site rigid water models, including TIP4P/ε, OPC, TIP3P-FB, TIP4P-FB, TIP4P-D, SPC/ε, OPC3, TIP5P-2018, TIP3P-ST, TIP4P-ST, and FBA/ε. The study focused on the effects of temperature on the thermodynamic, structural, and dynamic properties of water. A wide range of physical properties was examined using both slab and closed systems across temperatures ranging from 270 to 630 Kelvin. The results were compared with older rigid and non-rigid water models. Among the models tested, TIP4P-FB demonstrated the best overall performance, while OPC3 was identified as the most accurate among the 3-site models tested in this study.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"592 ","pages":"Article 114329"},"PeriodicalIF":2.8,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143155494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Influence of water content on thermophysical properties of aqueous glyceline solutions predicted by molecular dynamics simulations
IF 2.8 3区 工程技术 Q3 CHEMISTRY, PHYSICAL Pub Date : 2025-01-02 DOI: 10.1016/j.fluid.2024.114324
Marcelle B.M. Spera , Samir Darouich , Jürgen Pleiss , Niels Hansen
Molecular simulations allow the prediction of a large variety of thermophysical properties for complex mixtures based on one underlying model, i.e. the force field. In the present work static and dynamic properties of aqueous 1:2 choline chloride:glycerol mixtures are computed by molecular dynamics simulations with the aim to report robust simulation protocols that allow for a thorough evaluation of the molecular model with regard to experimental data. In particular for the shear viscosity a rather strong dependence of the results on the simulation method can be found. The simulations do not only provide quantitative data but also insight into the effect of water on the microscopic structure of the fluid. The isobaric thermal expansivity shows a transition from DES-like to water-like behavior beyond a water mole fraction of 0.75. Moreover, inconsistencies in experimental datasets are identified. Molecular dynamics simulations serve as a powerful tool to support the decision for one or the other data set in case of contradictory experimental data.
{"title":"Influence of water content on thermophysical properties of aqueous glyceline solutions predicted by molecular dynamics simulations","authors":"Marcelle B.M. Spera ,&nbsp;Samir Darouich ,&nbsp;Jürgen Pleiss ,&nbsp;Niels Hansen","doi":"10.1016/j.fluid.2024.114324","DOIUrl":"10.1016/j.fluid.2024.114324","url":null,"abstract":"<div><div>Molecular simulations allow the prediction of a large variety of thermophysical properties for complex mixtures based on one underlying model, i.e. the force field. In the present work static and dynamic properties of aqueous 1:2 choline chloride:glycerol mixtures are computed by molecular dynamics simulations with the aim to report robust simulation protocols that allow for a thorough evaluation of the molecular model with regard to experimental data. In particular for the shear viscosity a rather strong dependence of the results on the simulation method can be found. The simulations do not only provide quantitative data but also insight into the effect of water on the microscopic structure of the fluid. The isobaric thermal expansivity shows a transition from DES-like to water-like behavior beyond a water mole fraction of 0.75. Moreover, inconsistencies in experimental datasets are identified. Molecular dynamics simulations serve as a powerful tool to support the decision for one or the other data set in case of contradictory experimental data.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"592 ","pages":"Article 114324"},"PeriodicalIF":2.8,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143155496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A machine learning approach to predict CO2 diffusivity in liquid H2O over a wide pressure and temperature range
IF 2.8 3区 工程技术 Q3 CHEMISTRY, PHYSICAL Pub Date : 2024-12-31 DOI: 10.1016/j.fluid.2024.114325
Georgios Gravanis , Simira Papadopoulou , Spyros Voutetakis , Konstantinos Diamantaras , Ioannis N. Tsimpanogiannis
This study presents a machine learning approach for predicting the diffusivity of CO2 in liquid H2O over a wide range of temperatures and pressures. A comprehensive experimental dataset is compiled, including over 300 data points from existing literature, as well as, 75 newly identified diffusivity measurements. These data span a broad spectrum of temperatures and pressures. Various machine learning models namely, Support Vector Machines (SVM), Random Forest (RF), k-Nearest Neighbors (kNN), and Autoencoders, are trained on this enhanced dataset and evaluated for their accuracy in diffusivity prediction. Results show that the Autoencoder model achieves superior performance, accurately predicting CO2 diffusivity even in regions where experimental data is sparse. The model’s ability to generalize across a wide range of temperatures and pressures, demonstrates its potential for use in real-world applications, enabling fast, reliable predictions with minimized computational cost.
{"title":"A machine learning approach to predict CO2 diffusivity in liquid H2O over a wide pressure and temperature range","authors":"Georgios Gravanis ,&nbsp;Simira Papadopoulou ,&nbsp;Spyros Voutetakis ,&nbsp;Konstantinos Diamantaras ,&nbsp;Ioannis N. Tsimpanogiannis","doi":"10.1016/j.fluid.2024.114325","DOIUrl":"10.1016/j.fluid.2024.114325","url":null,"abstract":"<div><div>This study presents a machine learning approach for predicting the diffusivity of CO<sub>2</sub> in liquid H<sub>2</sub>O over a wide range of temperatures and pressures. A comprehensive experimental dataset is compiled, including over 300 data points from existing literature, as well as, 75 newly identified diffusivity measurements. These data span a broad spectrum of temperatures and pressures. Various machine learning models namely, Support Vector Machines (SVM), Random Forest (RF), k-Nearest Neighbors (kNN), and Autoencoders, are trained on this enhanced dataset and evaluated for their accuracy in diffusivity prediction. Results show that the Autoencoder model achieves superior performance, accurately predicting CO<sub>2</sub> diffusivity even in regions where experimental data is sparse. The model’s ability to generalize across a wide range of temperatures and pressures, demonstrates its potential for use in real-world applications, enabling fast, reliable predictions with minimized computational cost.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"592 ","pages":"Article 114325"},"PeriodicalIF":2.8,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Separation of azeotropic mixture using a novel hybrid entrainer based on deep eutectic solvents
IF 2.8 3区 工程技术 Q3 CHEMISTRY, PHYSICAL Pub Date : 2024-12-30 DOI: 10.1016/j.fluid.2024.114326
Yong Peng , Yanhao Shen , Junfeng Niu , Xiaoyu Han
In recent years, deep eutectic solvents (DESs) have emerged as environmentally friendly distillation entrainers. However, most research has focused on pure DESs, and developing new DESs remains challenging. This process requires significant time to screen suitable hydrogen bond donors and acceptors. This study explores a hybrid approach to enhance the efficacy of single DESs. Using the widely studied ethanol/water azeotropic mixture as a model system, Choline chloride (ChCl):urea (1:2, mol/mol) was selected as the benchmark entrainer. Among the 13 inorganic salts tested, CaCl2 was chosen as an additive to prepare a hybrid entrainer (5 wt% CaCl2 + 95 wt% ChCl:urea). Increasing the hybrid entrainer content from 0 to 36.9 wt% resulted in a 270% increase in relative volatility, outperforming pure DESs. This hybrid approach demonstrates potential to reduce ChCl:urea usage by 50%. Vapor-liquid equilibria were determined, with a good fit between experimental and theoretical data using the NRTL model.
{"title":"Separation of azeotropic mixture using a novel hybrid entrainer based on deep eutectic solvents","authors":"Yong Peng ,&nbsp;Yanhao Shen ,&nbsp;Junfeng Niu ,&nbsp;Xiaoyu Han","doi":"10.1016/j.fluid.2024.114326","DOIUrl":"10.1016/j.fluid.2024.114326","url":null,"abstract":"<div><div>In recent years, deep eutectic solvents (DESs) have emerged as environmentally friendly distillation entrainers. However, most research has focused on pure DESs, and developing new DESs remains challenging. This process requires significant time to screen suitable hydrogen bond donors and acceptors. This study explores a hybrid approach to enhance the efficacy of single DESs. Using the widely studied ethanol/water azeotropic mixture as a model system, Choline chloride (ChCl):urea (1:2, mol/mol) was selected as the benchmark entrainer. Among the 13 inorganic salts tested, CaCl<sub>2</sub> was chosen as an additive to prepare a hybrid entrainer (5 wt% CaCl<sub>2</sub> + 95 wt% ChCl:urea). Increasing the hybrid entrainer content from 0 to 36.9 wt% resulted in a 270% increase in relative volatility, outperforming pure DESs. This hybrid approach demonstrates potential to reduce ChCl:urea usage by 50%. Vapor-liquid equilibria were determined, with a good fit between experimental and theoretical data using the NRTL model.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"592 ","pages":"Article 114326"},"PeriodicalIF":2.8,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143155499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The impact of inaccurate property data in process modelling
IF 2.8 3区 工程技术 Q3 CHEMISTRY, PHYSICAL Pub Date : 2024-12-29 DOI: 10.1016/j.fluid.2024.114322
José M.S. Fonseca , María Francisco Casal
It is widely accepted that high-quality thermophysical property data are essential for the accurate modelling of chemical processes, both in the conceptual design phase of process development and in the optimization of existing processes. Unfortunately, over the last decades, the chemical industry has experienced the closure of many physical property data laboratories. This trend is not limited to experimental facilities, also applied thermodynamic groups have been significantly downsized or sometimes extinguished. Process engineers and modelling experts often take over the tasks of evaluating and testing the thermodynamic property packages used in their models. From the simulation industry, we see that it is increasingly common that users request out-of-the-box property data that can be used directly in their simulations. Estimation methods are sometimes being used without a proper acknowledgment of their limitations and associated uncertainties. We believe it is, therefore, important to raise awareness of how large the impact of potential property data errors on process modelling can be, more specifically on the modelling of typical downstream unit operations. In this work, we provide practical insights on this issue, by revisiting textbook examples and by delving into real-life industrial cases we have encountered over the years. Critical considerations on the direct use of data from large databanks and estimation methods are also presented. The last is particularly relevant, with an increasing number of research groups working on the development of machine learning methods as means to generate massive amounts of property data.
{"title":"The impact of inaccurate property data in process modelling","authors":"José M.S. Fonseca ,&nbsp;María Francisco Casal","doi":"10.1016/j.fluid.2024.114322","DOIUrl":"10.1016/j.fluid.2024.114322","url":null,"abstract":"<div><div>It is widely accepted that high-quality thermophysical property data are essential for the accurate modelling of chemical processes, both in the conceptual design phase of process development and in the optimization of existing processes. Unfortunately, over the last decades, the chemical industry has experienced the closure of many physical property data laboratories. This trend is not limited to experimental facilities, also applied thermodynamic groups have been significantly downsized or sometimes extinguished. Process engineers and modelling experts often take over the tasks of evaluating and testing the thermodynamic property packages used in their models. From the simulation industry, we see that it is increasingly common that users request out-of-the-box property data that can be used directly in their simulations. Estimation methods are sometimes being used without a proper acknowledgment of their limitations and associated uncertainties. We believe it is, therefore, important to raise awareness of how large the impact of potential property data errors on process modelling can be, more specifically on the modelling of typical downstream unit operations. In this work, we provide practical insights on this issue, by revisiting textbook examples and by delving into real-life industrial cases we have encountered over the years. Critical considerations on the direct use of data from large databanks and estimation methods are also presented. The last is particularly relevant, with an increasing number of research groups working on the development of machine learning methods as means to generate massive amounts of property data.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"592 ","pages":"Article 114322"},"PeriodicalIF":2.8,"publicationDate":"2024-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143155493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Methane/ethane adsorption behavior in shale nanopore systems with mesopores and micropores: Evaluating micropore contribution
IF 2.8 3区 工程技术 Q3 CHEMISTRY, PHYSICAL Pub Date : 2024-12-25 DOI: 10.1016/j.fluid.2024.114323
Wuquan Li , Jinrong Cao , Yunfeng Liang , Yoshihiro Masuda , Takeshi Tsuji , Kohei Tamura , Tomoaki Ishiwata , Daisuke Kuramoto , Toshifumi Matsuoka
Shale gas has garnered significant attention as a clean and high-quality fuel resource. Shale formations exhibit broad pore size distributions, with micropores (< 2 nm) and mesopores (2–50 nm), showing different gas sorption behaviors. The sorption behavior in kerogen nanopore systems with interconnected micropores and mesopores remains poorly understood. This study introduces three kerogen nanopore systems—low-density, middle-density, and high-density—each featuring a 7.5-nm mesopore and numerous micropores. Using Grand Canonical Monte Carlo (GCMC) simulations, the sorption behaviors of pure CH4, C2H6, and their mixture (9:1) across a range of pressures (1 MPa to 13 MPa) and temperatures (313.15 K, 323.15 K, and 333.15 K) were investigated. The study identified three Zones: Zone I for the free gas phase, Zone II for adsorption in mesopores, and Zone III for absorption in micropores. The sorption isotherms were calculated by integrating the adsorption amounts, normalized by measured pore volume in the mesopore domain, and absorption amounts, normalized by total organic content. The calculated excess sorption isotherms across different kerogen nanopore systems aligned with experimental results, allowing us to estimate the micropore contribution. We calculated the actual density profiles and estimated the adsorption density in micropores and those on mesopore walls, which can be used for field applications. The selectivity in three zones was compared across three kerogen nanopore systems, showing that it was not so significantly influenced by the pore geometry at all temperatures and pressures. The absolute absorption in micropores and the micropore contribution to the total absolute sorption (in percentage) align consistently with micropore volume across different kerogen nanopore systems, revealing a linear relationship with micropore volume. This research provides recommendations for laboratory experiments and offers valuable insights into the microscopic distribution of shale gas in nanopore systems, emphasizing the significance of micropores in addition to mesopores.
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引用次数: 0
Can MOF — Isobutane integration enhance adsorption refrigeration cycle? An accelerated approach using active learning and Monte Carlo simulations
IF 2.8 3区 工程技术 Q3 CHEMISTRY, PHYSICAL Pub Date : 2024-12-24 DOI: 10.1016/j.fluid.2024.114315
S. Muthu Krishnan , Jayant K. Singh
This study investigates the use of MOF adsorbents with low GWP refrigerant isobutane for a sustainable adsorption-based refrigeration cycle. An innovative active learning-based strategy was used to accelerate the screening process. The combination of a probabilistic surrogate model, trained with a labelled dataset that is iteratively updated by the data query process of an acquisition function, allowed for an efficient exploration of the dataset only in the region of high probability of finding the best MOF rather than the whole dataset. This fusion of active learning with Monte Carlo simulation for labelling the dataset accelerated the screening process by almost 83%. The screening results converged to the highest COP of 0.786 and the highest cooling capacity of 305.9 kJ/kg which is almost 50% higher than the reported value for MOF - isobutane integration. Further, we performed an analysis to find the influence of the largest cavity diameter (LCD) on COP.
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引用次数: 0
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Fluid Phase Equilibria
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