Pub Date : 2026-02-03DOI: 10.1016/j.fluid.2026.114688
N. Lauriello , K. Sindelka , D. Marchisio , M. Casalegno
Pluronics are nonionic amphiphilic copolymers with many applications in the pharmaceutical and cosmetic industry. In water these polymers may exist as unimers, micelles, and other supramolecular aggregates. The study of such phases by means of in-silico methods, like molecular dynamics and dissipative particle dynamics, can be expected to complement existing experimental data and better understand their molecular properties. In this work, we propose a two-scale approach where these two methods are combined to allow for the efficient study of Pluronics dynamics at different temperatures. The method is applied to study the thermoresponsive behavior of L61 in water. In line with the experimental data, our simulations show that L61 does not form micelles upon heating. At the highest concentration considered, a two-phase system is observed, where small and large aggregates coexist. This outcome and the applicability of the method to other Pluronics are discussed in the light of the existing literature.
{"title":"Understanding the thermoresponsive behavior of L61/Water mixtures via MD and DPD simulations: A two-scale approach","authors":"N. Lauriello , K. Sindelka , D. Marchisio , M. Casalegno","doi":"10.1016/j.fluid.2026.114688","DOIUrl":"10.1016/j.fluid.2026.114688","url":null,"abstract":"<div><div>Pluronics are nonionic amphiphilic copolymers with many applications in the pharmaceutical and cosmetic industry. In water these polymers may exist as unimers, micelles, and other supramolecular aggregates. The study of such phases by means of in-silico methods, like molecular dynamics and dissipative particle dynamics, can be expected to complement existing experimental data and better understand their molecular properties. In this work, we propose a two-scale approach where these two methods are combined to allow for the efficient study of Pluronics dynamics at different temperatures. The method is applied to study the thermoresponsive behavior of L61 in water. In line with the experimental data, our simulations show that L61 does not form micelles upon heating. At the highest concentration considered, a two-phase system is observed, where small and large aggregates coexist. This outcome and the applicability of the method to other Pluronics are discussed in the light of the existing literature.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"606 ","pages":"Article 114688"},"PeriodicalIF":2.7,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146122737","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}
Molecular dynamics (MD) simulations were performed to investigate high-pressure thermodynamic properties of CO2-hydrocarbon binary mixtures using different force field strategies ‒ united atom, all atom, and hybrid combinations. Simulations were carried out in the isothermal-isobaric (NPT) ensemble to obtain molar volumes as a function of pressure and composition. As a preliminary step, four cubic equations of state were tested against available compressibility factor data, and Peng-Robinson (PR) was selected as the reference cubic framework for the subsequent analyses. MD-derived molar volumes were then coupled to PR in a hybrid workflow: compressibility factors were computed and benchmarked against experimental data, and PR-based fugacity coefficients were evaluated using either PR-predicted or MD-derived molar volumes to quantify the sensitivity of ϕ to the volume source under identical (P, T, y) conditions. The results show that force field choice significantly affects high-pressure volumetric predictions, with TraPPE-based descriptions providing the closest agreement with experimental compressibility factors for CO2 + CH4 over the investigated conditions. Finally, effective PR mixture parameters were inferred by nonlinear least-squares fitting of the molar-volume form of PR to volumetric datasets, demonstrating that MD-generated Vm(P, T, y) data can serve as an independent input for cubic-EoS parameter inference when experimental information or calibrated mixture parameters are limited.
{"title":"Molecular dynamics simulations and cubic equations of state of high-pressure CO2-hydrocarbon mixtures: compressibility factor and fugacity coefficient","authors":"Juliana J․ F․ Souza-Rêgo , Itamar Borges Jr , Leonardo S․ de B․ Alves , Luiz O․ V․ Pereira , Ligia G․ Franco , Jakler Nichele","doi":"10.1016/j.fluid.2026.114686","DOIUrl":"10.1016/j.fluid.2026.114686","url":null,"abstract":"<div><div>Molecular dynamics (MD) simulations were performed to investigate high-pressure thermodynamic properties of CO<sub>2</sub>-hydrocarbon binary mixtures using different force field strategies ‒ united atom, all atom, and hybrid combinations. Simulations were carried out in the isothermal-isobaric (NPT) ensemble to obtain molar volumes as a function of pressure and composition. As a preliminary step, four cubic equations of state were tested against available compressibility factor data, and Peng-Robinson (PR) was selected as the reference cubic framework for the subsequent analyses. MD-derived molar volumes were then coupled to PR in a hybrid workflow: compressibility factors were computed and benchmarked against experimental data, and PR-based fugacity coefficients were evaluated using either PR-predicted or MD-derived molar volumes to quantify the sensitivity of <em>ϕ</em> to the volume source under identical (<em>P, T</em>, <strong><em>y</em></strong>) conditions. The results show that force field choice significantly affects high-pressure volumetric predictions, with TraPPE-based descriptions providing the closest agreement with experimental compressibility factors for CO<sub>2</sub> + CH<sub>4</sub> over the investigated conditions. Finally, effective PR mixture parameters were inferred by nonlinear least-squares fitting of the molar-volume form of PR to volumetric datasets, demonstrating that MD-generated <em>V<sub>m</sub></em>(<em>P, T</em>, <strong><em>y</em></strong>) data can serve as an independent input for cubic-EoS parameter inference when experimental information or calibrated mixture parameters are limited.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"605 ","pages":"Article 114686"},"PeriodicalIF":2.7,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090662","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}
Pub Date : 2026-01-24DOI: 10.1016/j.fluid.2026.114684
Sebastián Echeverri Restrepo , Guillermo E. Morales-Espejel
Refrigerants are increasingly being used as lubricating media in high-pressure, high-temperature applications such as compressors, where accurate prediction of their thermophysical properties is essential for effective design and performance optimisation. In this study, we present a molecular dynamics framework to simulate the density and viscosity of a refrigerant across a wide range of conditions relevant to the contact between a rolling element and the raceway of a bearing in an compressor. Using both Non-Equilibrium (SLLOD) and Equilibrium Molecular Dynamics (Green–Kubo) approaches, we evaluate the performance of the OPLS force field and validate the use of atomic SLLOD equations for small refrigerant molecules (instead of the more complex molecular version). The simulation results show good agreement with literature data. We conclude that this methodology offers a reliable and computationally efficient tool for characterising refrigerants, even under extreme operating conditions.
{"title":"Density and viscosity of refrigerant R123 with OPLS force field and atomic SLLOD","authors":"Sebastián Echeverri Restrepo , Guillermo E. Morales-Espejel","doi":"10.1016/j.fluid.2026.114684","DOIUrl":"10.1016/j.fluid.2026.114684","url":null,"abstract":"<div><div>Refrigerants are increasingly being used as lubricating media in high-pressure, high-temperature applications such as compressors, where accurate prediction of their thermophysical properties is essential for effective design and performance optimisation. In this study, we present a molecular dynamics framework to simulate the density and viscosity of a refrigerant across a wide range of conditions relevant to the contact between a rolling element and the raceway of a bearing in an compressor. Using both Non-Equilibrium (SLLOD) and Equilibrium Molecular Dynamics (Green–Kubo) approaches, we evaluate the performance of the OPLS force field and validate the use of <em>atomic</em> SLLOD equations for small refrigerant molecules (instead of the more complex <em>molecular</em> version). The simulation results show good agreement with literature data. We conclude that this methodology offers a reliable and computationally efficient tool for characterising refrigerants, even under extreme operating conditions.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"605 ","pages":"Article 114684"},"PeriodicalIF":2.7,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090663","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}
Pub Date : 2026-01-22DOI: 10.1016/j.fluid.2026.114685
Mahdi Mansoury , Mohammad Ali Badamchizadeh , Peyman Roozafzoon Bashsiz , Sina Pakkhesal , Elaheh Rahimpour , Abolghasem Jouyban
Drug solubility is a critical physicochemical property in pharmaceutical research, governing drug formulation, therapeutic efficacy, and bioavailability. Conventional methods for solubility determination and prediction often rely on labor-intensive experimental approaches or computationally limited thermodynamic models. This study employs advanced machine learning and deep learning techniques to simulate the solubility of azole-based antifungal drugs in binary solvent systems at various temperatures, benchmarking their performance against traditional thermodynamic models. Experimental solubility data for ten azole drugs in various binary solvent mixtures were analyzed. Models evaluated included linear algorithms, tree-based methods, ensemble boosting techniques (XGBoost, LightGBM, CatBoost), kernel-based approaches (support vector regression, Gaussian process regression), and deep learning architectures (multilayer perceptrons, hybrid frameworks). The performances of the models were evaluated using mean relative deviation (MRD) as the primary performance metric. CatBoost (MRD = 6.9 %), the hybrid framework (MRD = 9.2 %), and XGBoost (MRD = 12.0 %) were identified as the top three models. In addition, their performances were comprehensively evaluated using a set of supplementary metrics to ensure robust comparative assessment. The findings highlight the superior predictive accuracy of data-driven algorithms, demonstrating their potential as robust tools for pharmaceutical development and the optimization of solvent systems.
{"title":"Evaluating machine learning models for accurate solubility prediction of azole drugs in binary solvents at various temperatures","authors":"Mahdi Mansoury , Mohammad Ali Badamchizadeh , Peyman Roozafzoon Bashsiz , Sina Pakkhesal , Elaheh Rahimpour , Abolghasem Jouyban","doi":"10.1016/j.fluid.2026.114685","DOIUrl":"10.1016/j.fluid.2026.114685","url":null,"abstract":"<div><div>Drug solubility is a critical physicochemical property in pharmaceutical research, governing drug formulation, therapeutic efficacy, and bioavailability. Conventional methods for solubility determination and prediction often rely on labor-intensive experimental approaches or computationally limited thermodynamic models. This study employs advanced machine learning and deep learning techniques to simulate the solubility of azole-based antifungal drugs in binary solvent systems at various temperatures, benchmarking their performance against traditional thermodynamic models. Experimental solubility data for ten azole drugs in various binary solvent mixtures were analyzed. Models evaluated included linear algorithms, tree-based methods, ensemble boosting techniques (XGBoost, LightGBM, CatBoost), kernel-based approaches (support vector regression, Gaussian process regression), and deep learning architectures (multilayer perceptrons, hybrid frameworks). The performances of the models were evaluated using mean relative deviation (MRD) as the primary performance metric. CatBoost (MRD = 6.9 %), the hybrid framework (MRD = 9.2 %), and XGBoost (MRD = 12.0 %) were identified as the top three models. In addition, their performances were comprehensively evaluated using a set of supplementary metrics to ensure robust comparative assessment. The findings highlight the superior predictive accuracy of data-driven algorithms, demonstrating their potential as robust tools for pharmaceutical development and the optimization of solvent systems.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"605 ","pages":"Article 114685"},"PeriodicalIF":2.7,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090661","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}
Pub Date : 2026-01-19DOI: 10.1016/j.fluid.2026.114675
Wen Hwa Siah, Marco Campestrini, Paolo Stringari
A precise understanding of the solubility limits of solids in methane-rich mixtures is essential for assessing crystallization risks in the production of liquefied natural gas (LNG). While recent studies have provided new experimental data and modelling approaches dealing with the solubility of heavy components (primarily aromatic compounds) in binary mixtures with methane, the phase equilibrium behavior of multi-component mixtures at cryogenic temperatures remains insufficiently understood.
Given its high solubility in methane, the presence of neopentane in the feed mixture may potentially reduce the crystallization risk of other heavy components (i.e., chemicals having a triple-point temperature above the LNG temperature like carbon dioxide), either by enhancing their solubility at specific temperature and pressure conditions or by extending the pressure range over which the fluid phase remains stable.
This study presents new insights into the thermodynamic behavior of systems comprised of methane, carbon dioxide, and neopentane, with the aim of investigating the effect of neopentane on the solubility of carbon dioxide in methane. New experimental data were determined for: (1) the binary carbon dioxide + neopentane system, including both liquid-vapor equilibrium (VLE) and solid-fluid equilibrium (SFE) measurements down to 170 K, and (2) the ternary methane + carbon dioxide + neopentane system, with SFE measurements down to 120 K. Both systems were studied using two different static-analytic apparatuses.
The experimental results were compared with modelling results obtained by coupling the Peng-Robinson Equation of State (PR78 EoS) for the fluid phases with the Classical Approach for the solid phases.
{"title":"Solid-fluid equilibria of mixtures of interest in LNG production: Measurement and modelling of methane + carbon dioxide + neo-pentane systems","authors":"Wen Hwa Siah, Marco Campestrini, Paolo Stringari","doi":"10.1016/j.fluid.2026.114675","DOIUrl":"10.1016/j.fluid.2026.114675","url":null,"abstract":"<div><div>A precise understanding of the solubility limits of solids in methane-rich mixtures is essential for assessing crystallization risks in the production of liquefied natural gas (LNG). While recent studies have provided new experimental data and modelling approaches dealing with the solubility of heavy components (primarily aromatic compounds) in binary mixtures with methane, the phase equilibrium behavior of multi-component mixtures at cryogenic temperatures remains insufficiently understood.</div><div>Given its high solubility in methane, the presence of neopentane in the feed mixture may potentially reduce the crystallization risk of other heavy components (i.e., chemicals having a triple-point temperature above the LNG temperature like carbon dioxide), either by enhancing their solubility at specific temperature and pressure conditions or by extending the pressure range over which the fluid phase remains stable.</div><div>This study presents new insights into the thermodynamic behavior of systems comprised of methane, carbon dioxide, and neopentane, with the aim of investigating the effect of neopentane on the solubility of carbon dioxide in methane. New experimental data were determined for: (1) the binary carbon dioxide + neopentane system, including both liquid-vapor equilibrium (VLE) and solid-fluid equilibrium (SFE) measurements down to 170 K, and (2) the ternary methane + carbon dioxide + neopentane system, with SFE measurements down to 120 K. Both systems were studied using two different static-analytic apparatuses.</div><div>The experimental results were compared with modelling results obtained by coupling the Peng-Robinson Equation of State (PR78 EoS) for the fluid phases with the Classical Approach for the solid phases.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"605 ","pages":"Article 114675"},"PeriodicalIF":2.7,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036507","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}
Pub Date : 2026-01-19DOI: 10.1016/j.fluid.2026.114674
Shuo Wang , Jingjing Zhou , Jingjian Li , Yanmin Song , Bowen Zhang , Dandan Han , Junbo Gong
As a key intermediate in the synthesis of anticancer agents, 5′-O-Dimethoxytrityl-N-benzoyl-deoxycytidine (Bz-Dmt-dC) usually presents as a solvate and its purity plays a critical role in the production process. To obtain high purity products quickly and efficiently via crystallization, the solubility data of the compound must first be determined. Therefore, under the premise of ensuring no phase transitions during the measurement process, the solubility of solvates formed by Bz-Dmt-dC in three binary solvent systems (acetonitrile + water, acetone + water, and THF + water) were experimentally determined over the temperature range of 278.15 to 313.15 K at atmospheric pressure using the gravimetric method. The experimental results showed that, for a given solvent type and composition, the solubility of Bz-Dmt-dC increased with increasing temperature. The solubility data of Bz-Dmt-dC were correlated using the modified Apelblat, λh, and NRTL equations. Among these, the modified Apelblat model provided the best fitting result, as indicated by the lowest average relative deviation (ARD) values of 0.7%.
5′- o -二甲氧基三烷基- n -苯甲酰脱氧胞苷（Bz-Dmt-dC）作为抗癌药物合成的关键中间体，通常以溶剂形式存在，其纯度在生产过程中起着至关重要的作用。为了通过结晶快速有效地获得高纯度产品，必须首先确定化合物的溶解度数据。因此，在保证测量过程无相变的前提下，在278.15 ~ 313.15 K的大气压温度范围内，用重量法实验测定了Bz-Dmt-dC形成的溶剂化物在乙腈+水、丙酮+水、THF +水三种二元溶剂体系中的溶解度。实验结果表明，在一定溶剂类型和组成下，Bz-Dmt-dC的溶解度随温度升高而增大。利用修正后的Apelblat、λh和NRTL方程对Bz-Dmt-dC的溶解度数据进行相关性分析。其中，修正Apelblat模型拟合效果最好，平均相对偏差（ARD）值最低，为0.7%。
{"title":"Solubility measurement and data correlation of 5′-O-Dimethoxytrityl-N-benzoyl-deoxycytidine solvate in three binary solvent systems from 278.15 to 313.15 K","authors":"Shuo Wang , Jingjing Zhou , Jingjian Li , Yanmin Song , Bowen Zhang , Dandan Han , Junbo Gong","doi":"10.1016/j.fluid.2026.114674","DOIUrl":"10.1016/j.fluid.2026.114674","url":null,"abstract":"<div><div>As a key intermediate in the synthesis of anticancer agents, 5′-O-Dimethoxytrityl-N-benzoyl-deoxycytidine (Bz-Dmt-dC) usually presents as a solvate and its purity plays a critical role in the production process. To obtain high purity products quickly and efficiently via crystallization, the solubility data of the compound must first be determined. Therefore, under the premise of ensuring no phase transitions during the measurement process, the solubility of solvates formed by Bz-Dmt-dC in three binary solvent systems (acetonitrile + water, acetone + water, and THF + water) were experimentally determined over the temperature range of 278.15 to 313.15 K at atmospheric pressure using the gravimetric method. The experimental results showed that, for a given solvent type and composition, the solubility of Bz-Dmt-dC increased with increasing temperature. The solubility data of Bz-Dmt-dC were correlated using the modified Apelblat, <em>λ</em>h, and NRTL equations. Among these, the modified Apelblat model provided the best fitting result, as indicated by the lowest average relative deviation (ARD) values of 0.7%.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"605 ","pages":"Article 114674"},"PeriodicalIF":2.7,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036505","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}
Pub Date : 2026-01-16DOI: 10.1016/j.fluid.2026.114673
Maurício Prado de Omena Souza , Diego Tavares Volpatto , Antonio Marinho Barbosa Neto , Mariana Conceição da Costa
The flash point (FP) is an essential property for assessing flammability and ensuring safety in combustion processes. However, its experimental measurement is resource-intensive and data in the literature remains limited, especially for biofuel mixtures. To address this, predictive modeling has emerged as a promising alternative. This study investigates the capability of thermodynamically consistent neural network models to estimate FP, as well as hybrid approach that embeds a neural network constrained by Gibbs-Duhem equation within a thermodynamic model. The performance of these models was compared with that of a purely data-driven model and a widely used thermodynamic approach. The evaluation was conducted using a dataset comprising binary mixtures of 1-butanol and fatty acid ethyl esters (FAEEs). The data-driven and physically constrained neural network approaches achieved RMSE (Root Mean Squared Error) values of 2.518 K, 1.975 K, 2.798 K, and 2.470 K, while the thermodynamic model using NRTL providing a RMSE of 0.587 K, as expected given that its binary interaction parameters were fitted to the experimental FP data. In addition, incorporating physical constraints into the neural network models for FP prediction did not improve RMSE performance compared to the purely data-driven model, despite achieving improved consistency for the embedded physics equations as expected.
{"title":"Modeling flash points of biofuels using thermodynamically consistent neural networks","authors":"Maurício Prado de Omena Souza , Diego Tavares Volpatto , Antonio Marinho Barbosa Neto , Mariana Conceição da Costa","doi":"10.1016/j.fluid.2026.114673","DOIUrl":"10.1016/j.fluid.2026.114673","url":null,"abstract":"<div><div>The flash point (FP) is an essential property for assessing flammability and ensuring safety in combustion processes. However, its experimental measurement is resource-intensive and data in the literature remains limited, especially for biofuel mixtures. To address this, predictive modeling has emerged as a promising alternative. This study investigates the capability of thermodynamically consistent neural network models to estimate FP, as well as hybrid approach that embeds a neural network constrained by Gibbs-Duhem equation within a thermodynamic model. The performance of these models was compared with that of a purely data-driven model and a widely used thermodynamic approach. The evaluation was conducted using a dataset comprising binary mixtures of 1-butanol and fatty acid ethyl esters (FAEEs). The data-driven and physically constrained neural network approaches achieved RMSE (Root Mean Squared Error) values of 2.518 K, 1.975 K, 2.798 K, and 2.470 K, while the thermodynamic model using NRTL providing a RMSE of 0.587 K, as expected given that its binary interaction parameters were fitted to the experimental FP data. In addition, incorporating physical constraints into the neural network models for FP prediction did not improve RMSE performance compared to the purely data-driven model, despite achieving improved consistency for the embedded physics equations as expected.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"605 ","pages":"Article 114673"},"PeriodicalIF":2.7,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036503","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}
The efficient separation of aromatics from fluid catalytic cracking light cycle oil is crucial for improving oil quality and realizing the high-value utilization of aromatics. In this study, a two-step extraction-stripping high-efficiency separation method was developed, which successfully achieved the separation of nearly 99.99% pure aromatics. Focusing on the separation characteristics of polymethyl monocyclic aromatics, the extraction performances of sulfolane, dimethyl sulfoxide, and N, N-dimethylformamide was analyzed by GC-MS. Under the conditions of 318.15 K and 101.325 kPa, the liquid-liquid equilibrium (LLE) data of the extractant-p-xylene-heptane ternary system were determined. The results of the separation factor and distribution coefficient showed that sulfoxide had the best selectivity for polymethyl monocyclic aromatics, making it a potential high-efficiency extraction solvent. Furthermore, combined with density functional theory, the mechanism of solvent extraction of p-xylene from heptane was explored at the molecular level. Analyses of electrostatic potential, interaction energy, and reduced density gradient revealed that the main interaction was the van der Waals force. The LLE data were accurately correlated using the NRTL and UNIQUAC thermodynamic models, with the root-mean-square deviation values all below 0.0098. This study not only provides an efficient process for separating but also clarifies the structure-activity relationship between solvent molecular structure and extraction performance from both experimental and theoretical perspectives, providing a theoretical basis for the design and selection of high-performance separation solvents.
{"title":"Study on solvent extraction separation of polymethyl-substituted monocyclic aromatics from FCC LCO and its interaction mechanism","authors":"Qi Li, Jie Li, Hongli Chen, Weihua Xing, Jingxian Wang, Yingyun Qiao, Yuanyu Tian","doi":"10.1016/j.fluid.2026.114672","DOIUrl":"10.1016/j.fluid.2026.114672","url":null,"abstract":"<div><div>The efficient separation of aromatics from fluid catalytic cracking light cycle oil is crucial for improving oil quality and realizing the high-value utilization of aromatics. In this study, a two-step extraction-stripping high-efficiency separation method was developed, which successfully achieved the separation of nearly 99.99% pure aromatics. Focusing on the separation characteristics of polymethyl monocyclic aromatics, the extraction performances of sulfolane, dimethyl sulfoxide, and N, N-dimethylformamide was analyzed by GC-MS. Under the conditions of 318.15 K and 101.325 kPa, the liquid-liquid equilibrium (LLE) data of the extractant-p-xylene-heptane ternary system were determined. The results of the separation factor and distribution coefficient showed that sulfoxide had the best selectivity for polymethyl monocyclic aromatics, making it a potential high-efficiency extraction solvent. Furthermore, combined with density functional theory, the mechanism of solvent extraction of p-xylene from heptane was explored at the molecular level. Analyses of electrostatic potential, interaction energy, and reduced density gradient revealed that the main interaction was the van der Waals force. The LLE data were accurately correlated using the NRTL and UNIQUAC thermodynamic models, with the root-mean-square deviation values all below 0.0098. This study not only provides an efficient process for separating but also clarifies the structure-activity relationship between solvent molecular structure and extraction performance from both experimental and theoretical perspectives, providing a theoretical basis for the design and selection of high-performance separation solvents.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"605 ","pages":"Article 114672"},"PeriodicalIF":2.7,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036504","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}
Recent publications have reported phase equilibrium data for CO₂ + methylcyclopentane (MCP) and CO2 + 2,2-dimethylbutane using static-analytical sampling methods that are inconsistent with previously published synthetic-method data. To verify the reliability of our earlier measurements, we have repeated vapor–liquid equilibrium (VLE) experiments for both CO₂ + MCP and CO₂ + 2,2-dimethylbutane in the range 20–90 °C using a high-pressure variable-volume PVT cell with visual observation. Our new data agree within 1–2 bar with the values previously reported by our group, confirming the reproducibility of the synthetic method. To further validate our methodology, we also investigated the CO₂ + toluene system, which has been extensively studied in the literature. Our experimental results are in agreement with reference data, thereby confirming the accuracy of the synthetic technique and of the procedures used for mixture preparation and bubble-point detection. These results support the conclusion that the discrepancies between our data and those obtained by static-analytical methods cannot be attributed to errors inherent to the synthetic technique.
{"title":"Validation of synthetic method for phase equilibria measurements: Re-examination of CO₂ + methylcyclopentane, CO₂ + 2,2-dimethylbutane, and benchmarking with CO₂ + toluene","authors":"Jean-Luc Daridon , Jean-Patrick Bazile , Jean-Noël Jaubert , Stéphane Vitu","doi":"10.1016/j.fluid.2026.114664","DOIUrl":"10.1016/j.fluid.2026.114664","url":null,"abstract":"<div><div>Recent publications have reported phase equilibrium data for CO₂ + methylcyclopentane (MCP) and CO<sub>2</sub> + 2,2-dimethylbutane using static-analytical sampling methods that are inconsistent with previously published synthetic-method data. To verify the reliability of our earlier measurements, we have repeated vapor–liquid equilibrium (VLE) experiments for both CO₂ + MCP and CO₂ + 2,2-dimethylbutane in the range 20–90 °C using a high-pressure variable-volume PVT cell with visual observation. Our new data agree within 1–2 bar with the values previously reported by our group, confirming the reproducibility of the synthetic method. To further validate our methodology, we also investigated the CO₂ + toluene system, which has been extensively studied in the literature. Our experimental results are in agreement with reference data, thereby confirming the accuracy of the synthetic technique and of the procedures used for mixture preparation and bubble-point detection. These results support the conclusion that the discrepancies between our data and those obtained by static-analytical methods cannot be attributed to errors inherent to the synthetic technique.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"605 ","pages":"Article 114664"},"PeriodicalIF":2.7,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976676","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}
Pub Date : 2026-01-10DOI: 10.1016/j.fluid.2026.114662
Ziyi Zhou, Nefeli Novak, Georgios M. Kontogeorgis, Xiaodong Liang
Electrolyte solutions are central to many industrial, geochemical, and biological processes, yet their thermodynamic modeling remains challenging. This work assesses the predictive performance of the eSAFT-VR Mie equation of state by focusing on two key modeling parameters: (i) the distance of closest approach, comparing the ion segment diameter () with the effective hard-sphere diameter (), and (ii) the choice of ion–ion combining rules, both dispersion-energy-based formulations, namely the Hudson–McCoubrey (CR1) and the modified Lennard-Jones (CR2) rules. Predictions of mean ionic activity coefficients (MIAC) and liquid densities were evaluated for 57 aqueous salts without additional parameter fitting. Results show that density is relatively insensitive to the choice of parameters, whereas MIAC exhibits salt- and concentration-dependent sensitivity, particularly for multivalent systems. The comparison of CR1 and CR2 highlights that no single combining rule performs universally best, with accuracy depending on the ion type and charge density. These findings provide guidance for selecting the parameters and improving predictive electrolyte models.
{"title":"Evaluation of the effect of segment diameter and combining rules in eSAFT-VR Mie modeling of aqueous electrolyte solutions","authors":"Ziyi Zhou, Nefeli Novak, Georgios M. Kontogeorgis, Xiaodong Liang","doi":"10.1016/j.fluid.2026.114662","DOIUrl":"10.1016/j.fluid.2026.114662","url":null,"abstract":"<div><div>Electrolyte solutions are central to many industrial, geochemical, and biological processes, yet their thermodynamic modeling remains challenging. This work assesses the predictive performance of the eSAFT-VR Mie equation of state by focusing on two key modeling parameters: (i) the distance of closest approach, comparing the ion segment diameter (<span><math><mi>σ</mi></math></span>) with the effective hard-sphere diameter (<span><math><mi>d</mi></math></span>), and (ii) the choice of ion–ion combining rules, both dispersion-energy-based formulations, namely the Hudson–McCoubrey (CR1) and the modified Lennard-Jones (CR2) rules. Predictions of mean ionic activity coefficients (MIAC) and liquid densities were evaluated for 57 aqueous salts without additional parameter fitting. Results show that density is relatively insensitive to the choice of parameters, whereas MIAC exhibits salt- and concentration-dependent sensitivity, particularly for multivalent systems. The comparison of CR1 and CR2 highlights that no single combining rule performs universally best, with accuracy depending on the ion type and charge density. These findings provide guidance for selecting the parameters and improving predictive electrolyte models.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"605 ","pages":"Article 114662"},"PeriodicalIF":2.7,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036502","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}
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