Fluid Phase Equilibria最新文献

{"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 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 &lt;4 % average deviation for the system. Notably, the PR-EoS outperformed the MFHEA-EoS, showing &lt;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 (&gt;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 &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}

{"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}

{"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}

{"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 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.</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}

{"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, 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.</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}

{"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}

{"title":"Methane/ethane adsorption behavior in shale nanopore systems with mesopores and micropores: Evaluating micropore contribution","authors":"Wuquan Li ,&nbsp;Jinrong Cao ,&nbsp;Yunfeng Liang ,&nbsp;Yoshihiro Masuda ,&nbsp;Takeshi Tsuji ,&nbsp;Kohei Tamura ,&nbsp;Tomoaki Ishiwata ,&nbsp;Daisuke Kuramoto ,&nbsp;Toshifumi Matsuoka","doi":"10.1016/j.fluid.2024.114323","DOIUrl":"10.1016/j.fluid.2024.114323","url":null,"abstract":"<div><div>Shale gas has garnered significant attention as a clean and high-quality fuel resource. Shale formations exhibit broad pore size distributions, with micropores (&lt; 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.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"592 ","pages":"Article 114323"},"PeriodicalIF":2.8,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143155491","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}

{"title":"Can MOF — Isobutane integration enhance adsorption refrigeration cycle? An accelerated approach using active learning and Monte Carlo simulations","authors":"S. Muthu Krishnan ,&nbsp;Jayant K. Singh","doi":"10.1016/j.fluid.2024.114315","DOIUrl":"10.1016/j.fluid.2024.114315","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"592 ","pages":"Article 114315"},"PeriodicalIF":2.8,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143155492","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}

{"title":"Bubble point pressure measurement and prediction of VLE and VLLE for dimethyl ether - 2-butoxyethanol and dimethyl ether - water - 2-butoxyethanol at (293.15 to 313.15) K","authors":"Tomoya Tsuji ,&nbsp;Masaki Okada ,&nbsp;Aoi Enokido ,&nbsp;Taka-aki Hoshina","doi":"10.1016/j.fluid.2024.114320","DOIUrl":"10.1016/j.fluid.2024.114320","url":null,"abstract":"<div><div>Bubble point pressure was measured for a binary, dimethyl ether – 2-butoxyethanol, and a ternary, dimethyl ether – water – 2-butoxyethanol, by use of a static apparatus with a glass cell up to 837.0 kPa at (293.15 to 313.15) K. The mole ratios of water: 2-butoxyethanol were set to 50.0:50.0, 90.0: 10.0 and 95.0: 5.0 in the liquid phase for the ternaries. The phase behavior was visually observed through the glass cell at the pressure measurements, because the vapor-liquid-liquid equilibria (VLLE) have been reported for dimethyl ether -water. The binary showed the vapor-liquid equilibrium (VLE), which almost followed an ideal solution. 2-Butoxyethanol enhanced the miscibility range for dimethyl ether – water. Only the VLE was observed in the two ternaries with water: 2-butoxyethanol = 50.0: 50.0 and 90.0:10.0. The VLLE was partly observed in the ternary with water: 2-butoxyethanol = 95.0: 5.0. The NRTL equation was employed to correlate the VLE and the VLLE not only for dimethyl ether – 2-butoxyethanol but also for the other constituent binaries, dimethyl ether - water and water – 2-butoxyethanol. The NRTL equation provided good reproducibilities for dimethyl ether - 2-butoxyethanol with the average value of the absolute relative deviations (AARDs) of 0.90 % for the pressure. Using the parameters fitted with the constituent three binary data, the AARDs were 5.04 %, 6.80 % and 12.21 % for the pressure of dimethyl ether – water – 2-butoxyethanol with water: 2-butoxyethanol = 50.0: 50.0, 90.0: 10.0 and 95.0: 5.0, respectively. The experimental data and the prediction will contribute to design the sprays using water-based solvents for color paints, disinfectants, cleaning agents, cosmetics, pharmaceuticals and so on.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"592 ","pages":"Article 114320"},"PeriodicalIF":2.8,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154557","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}

{"title":"Characteristic curves of the stockmayer fluid: Molecular simulation and equation of state modeling","authors":"Jens Staubach,&nbsp;Simon Stephan","doi":"10.1016/j.fluid.2024.114314","DOIUrl":"10.1016/j.fluid.2024.114314","url":null,"abstract":"<div><div>Molecular-based equation of state (EOS) models are an important tool for modeling thermophysical properties of fluids. Many fluids exhibit dipolar interactions for which Helmholtz energy models have been developed. The extrapolation behavior of these dipole contributions is critical for the extrapolation behavior of the total EOS model. In this work, nine dipole contribution models from the literature were examined regarding their performance on Brown’s characteristic curves. The zero-density limit of Brown’s curves are directly related to the second virial coefficients. Therefore, also the second virial coefficient was evaluated. The evaluation of the dipole contribution models was carried out using the Stockmayer model fluid. Therefore, all considered dipole contribution models were combined with an accurate Lennard-Jones EOS. Molecular simulations were used for determining reference data for the characteristic curves. Important differences are obtained for the extrapolation behavior of the different dipole contribution models. For low dipole moments, all studied dipole contribution models yield correct characteristic curves. With increasing dipole moment, some dipole contribution models yield unphysical artifacts.</div></div>","PeriodicalId":12170,"journal":{"name":"Fluid Phase Equilibria","volume":"592 ","pages":"Article 114314"},"PeriodicalIF":2.8,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143155497","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}