Fluid Phase Equilibria最新文献

英文中文

Mastering carbon nanotube dispersion: A simplified model for industrial and environmental innovation 掌握碳纳米管分散：工业和环境创新的简化模型

IF 2.8 3区工程技术 Q3 CHEMISTRY, PHYSICAL

Fluid Phase Equilibria

Pub Date : 2025-07-23 DOI: 10.1016/j.fluid.2025.114534

Mohammad Hossein Keshavarz, Mojgan Fathi, Zeinab Shirazi

Carbon nanotubes (CNTs) are celebrated for their extraordinary mechanical, electrical, and thermal properties, yet their industrial adoption remains hindered by aggregation issues. Achieving stable dispersion in organic solvents is critical for unlocking their potential in advanced composites, flexible electronics, energy storage, and environmental remediation. Current quantitative structure-property relationship (QSPR) models for predicting CNT dispersibility rely on computationally intensive descriptors, such as quantum-chemical or topological parameters, which limit their practical accessibility. This study introduces a streamlined predictive model that uses only three intuitive solvent descriptors—hydrogen-bonding capacity, hydrophobicity, and a novel π-π interaction parameter—to achieve exceptional accuracy (training r² = 0.917, external validation r² = 0.963) and precision (RMSE = 0.236 vs. 0.337 for prior models). Innovations include leveraging amine/amide functional groups for stabilization and eliminating dependence on complex computational tools. The model’s robustness is validated through rigorous statistical testing (leave-many-out cross-validation q² = 0.823) and applicability domain analysis. By prioritizing simplicity without compromising performance, this work bridges the gap between lab-scale nanotechnology research and scalable industrial applications, such as water purification and pollution remediation, offering a user-friendly alternative to traditional QSPR frameworks.

碳纳米管（CNTs）以其非凡的机械、电气和热性能而闻名，但其工业应用仍然受到聚集问题的阻碍。在有机溶剂中实现稳定的分散对于释放它们在先进复合材料、柔性电子、能源存储和环境修复方面的潜力至关重要。目前用于预测碳纳米管分散性的定量结构-性质关系（QSPR）模型依赖于计算密集型描述符，如量子化学或拓扑参数，这限制了它们的实际可及性。本研究引入了一个简化的预测模型，该模型仅使用三个直观的溶剂描述符——氢键容量、疏水性和一个新的π-π相互作用参数——来实现出色的准确度（训练r²= 0.917，外部验证r²= 0.963）和精度（RMSE = 0.236，而先前模型的RMSE = 0.337）。创新包括利用胺/酰胺官能团来稳定和消除对复杂计算工具的依赖。通过严格的统计检验（留多交叉验证q²= 0.823）和适用性域分析验证了模型的稳健性。通过优先考虑简单性而不影响性能，这项工作弥合了实验室规模的纳米技术研究和可扩展的工业应用（如水净化和污染修复）之间的差距，为传统的QSPR框架提供了一个用户友好的替代方案。

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引用次数: 0

Solving the UVN-flash problem in TVN-space 解决了电视空间的uvd -flash问题

IF 2.8 3区工程技术 Q3 CHEMISTRY, PHYSICAL

Fluid Phase Equilibria

Pub Date : 2025-07-19 DOI: 10.1016/j.fluid.2025.114528

Pardeep Kumar , Patricio I. Rosen Esquivel

In this paper, we investigate the phase equilibrium problem for multicomponent mixtures under specified internal energy (

U

), volume (

V

), and mole numbers (

N_{1}, N_{2}, \dots, N_{n}

), commonly known as the UVN-flash problem. While conventional phase equilibrium calculations typically use pressure–temperature-mole number (

P T N

) specifications, the UVN formulation is essential for dynamic simulations of closed systems and energy balance computations. Existing approaches, including those based on iterative pressure–temperature updates and direct entropy maximization, can suffer from computational inefficiencies due to inner Newton iterations needed to solve for temperature

T

at specified internal energy

U

and volume

V

In this work, we present a reformulation of the UVN-flash problem that eliminates the need for the inner Newton iterations, addressing a computational bottleneck. We begin with stability analysis and discuss a strategy to generate the initial guess for the UVN-flash from the stability analysis results. We then reformulate the UVN-flash problem in TVN-space as constrained entropy maximization. We provide a detailed derivation of Michelsen’s Q-function using the method of Lagrange multipliers, illustrating its direct application in solving the UVN-flash problem. Furthermore, we discuss the numerical methods used, including gradient and Hessian computations. The reformulation is validated against benchmark cases, demonstrating improved efficiency.

本文研究了给定内能(U)、体积(V)和摩尔数（N1,N2，…，Nn）条件下多组分混合物的相平衡问题，即通常所说的uvn闪蒸问题。虽然传统的相平衡计算通常使用压力-温度-摩尔数（PTN）规格，但UVN公式对于封闭系统的动态模拟和能量平衡计算至关重要。现有的方法，包括基于迭代压力-温度更新和直接熵最大化的方法，由于在特定内能U和体积v下求解温度T需要内牛顿迭代，可能会导致计算效率低下。在这项工作中，我们提出了一种重新表述的UVN-flash问题，消除了对内牛顿迭代的需要，解决了计算瓶颈。我们从稳定性分析开始，讨论了一种从稳定性分析结果中产生uvn闪光初始猜测的策略。然后，我们将tvn空间中的UVN-flash问题重新表述为约束熵最大化问题。我们用拉格朗日乘子法给出了Michelsen q函数的详细推导，说明了它在解决UVN-flash问题中的直接应用。此外，我们讨论了所使用的数值方法，包括梯度和Hessian计算。通过对基准案例的验证，证明了改进的效率。

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引用次数: 0

Thermodynamic modeling CO2 absorption in semi-aqueous monoethanolamine with N-methyl-2-pyrrolidone using electrolyte NRTL model 利用电解质NRTL模型模拟n -甲基-2-吡咯烷酮在半水单乙醇胺中的CO2吸收

IF 2.8 3区工程技术 Q3 CHEMISTRY, PHYSICAL

Fluid Phase Equilibria

Pub Date : 2025-07-18 DOI: 10.1016/j.fluid.2025.114532

Yi-Min Chen, Yu-Fan Chen, Yu-Jeng Lin

Partially replacing water with N-methyl-2-pyrrolidone (NMP) in aqueous monoethanolamine (MEA) solutions has been shown to reduce the energy demand of CO₂ capture. However, the absence of rigorous thermodynamic models for semi-aqueous MEA-NMP solvents hinders process design and optimization. This study develops a thermodynamic model for CO₂ absorption in NMP–H₂O–MEA–CO₂ mixtures using the electrolyte NRTL framework. The model extends the established H₂O–MEA–CO₂ system by incorporating NMP-specific parameters while preserving accuracy in the aqueous regime. A sequential regression approach is applied to correlate key properties relevant to CO₂ capture, including CO₂ solubility, excess enthalpy, heat of absorption, and liquid heat capacity across binary to quaternary systems. Viscosity and density are also modeled to support mass transfer calculations. To improve model accuracy, new CO₂ solubility data are measured for NMP–H₂O–MEA–CO₂ mixtures at 313–393 K. The model accurately represents CO₂ solubility across a wide range of CO₂ loadings, temperatures, and NMP contents, revealing a decrease in solubility and a 10–25 kJ/mol CO₂ increase in heat of absorption with NMP addition. The developed model enables rigorous process simulation and facilitates the design of energy-efficient CO₂ capture using semi-aqueous MEA-NMP solvents.

在单乙醇胺（MEA）水溶液中用n -甲基-2-吡咯烷酮（NMP）部分取代水已被证明可以减少二氧化碳捕获的能源需求。然而，缺乏严格的半水MEA-NMP溶剂热力学模型阻碍了工艺设计和优化。本研究利用电解质NRTL框架建立了NMP-H2O-MEA-CO2混合物中CO₂吸收的热力学模型。该模型通过纳入nmp特异性参数扩展了已建立的H2O-MEA-CO2系统，同时保持了水态的准确性。序列回归方法应用于关联与CO2捕获相关的关键特性，包括CO2溶解度、过剩焓、吸收热和跨二元到四元体系的液体热容。粘度和密度也建模，以支持传质计算。为了提高模型精度，在313-393 K下测量了NMP-H₂- mea - CO2混合物的新的CO2溶解度数据。该模型准确地代表了二氧化碳在广泛的二氧化碳负荷、温度和NMP含量范围内的溶解度，揭示了加入NMP后，二氧化碳的溶解度降低，吸收热增加10-25 kJ/mol。开发的模型能够进行严格的过程模拟，并促进使用半水MEA-NMP溶剂的节能CO2捕获设计。

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引用次数: 0

Adsorption of tetracycline using aspartic acid and polypyrrole-functionalized multiwalled carbon nanotubes: Kinetic, isotherm, and thermodynamic analysis 天冬氨酸和聚吡咯功能化多壁碳纳米管对四环素的吸附：动力学、等温线和热力学分析

IF 2.8 3区工程技术 Q3 CHEMISTRY, PHYSICAL

Fluid Phase Equilibria

Pub Date : 2025-07-17 DOI: 10.1016/j.fluid.2025.114531

Amirhossein Khazaie , Amir Hessam Hassani , Elham Moniri , Mahsasadat Miralinaghi

This study investigates the adsorption of tetracycline from aqueous solutions using a novel nanocomposite adsorbent composed of multi-walled carbon nanotubes functionalized with aspartic acid and poly-pyrrole. Batch adsorption experiments were conducted to evaluate the effects of pH, contact time, temperature, and initial concentration on adsorption efficiency. The maximum adsorption capacity was found to be 38.08 mg/g at pH 5, 25 °C, and an initial TC concentration of 100 mg/L. Kinetic data were best described by the pseudo-second-order model, indicating chemisorption, while equilibrium data fit well with the Langmuir isotherm model, confirming monolayer adsorption. Thermodynamic parameters revealed that the adsorption process is spontaneous and exothermic, with ΔG° values ranging from –11.9 to –11.11 kJ/mol and ΔH° = -21.34 kJ/mol. These findings suggest that MWCNT-Asp-PPy is an efficient, high-capacity adsorbent for TC removal, with promising applications in water treatment.

研究了一种由多壁碳纳米管组成的新型吸附剂对四环素的吸附性能，该吸附剂由天冬氨酸和聚吡咯功能化组成。通过批量吸附实验，考察了pH、接触时间、温度和初始浓度对吸附效率的影响。在pH为5，温度为25℃，初始TC浓度为100 mg/L时，最大吸附量为38.08 mg/g。动力学数据最好用拟二阶模型描述，表明是化学吸附，而平衡数据与Langmuir等温线模型吻合较好，证实是单层吸附。热力学参数表明，吸附过程为自发放热过程，ΔG°的取值范围为-11.9 ~ -11.11 kJ/mol， ΔH°= -21.34 kJ/mol。这些发现表明MWCNT-Asp-PPy是一种高效、高容量的TC吸附剂，在水处理中具有广阔的应用前景。

引用次数: 0

Molecular dynamics simulation study on the selective extraction of 1,3 propanediol from fermentation broth using imidazolium-based hydrophobic ionic liquids 咪唑基疏水离子液体选择性提取发酵液中1,3丙二醇的分子动力学模拟研究

IF 2.8 3区工程技术 Q3 CHEMISTRY, PHYSICAL

Fluid Phase Equilibria

Pub Date : 2025-07-11 DOI: 10.1016/j.fluid.2025.114530

Raj Akshat , Anand Bharti , Padmini Padmanabhan

Selective extraction of dilute 1,3 propanediol (1,3-PDO) (<20 wt %) from the fermentation broth is challenging via conventional distillation as the process becomes energy-intensive. Liquid-liquid extraction (LLE) using solvents such as ionic liquids (ILs) may significantly reduce costs. Therefore, this study explored the potential of imidazolium-based hydrophobic ILs for the selective extraction of 1,3-PDO from a fermentation broth containing 1,3-PDO, 2,3-butanediol (2,3-BDO), glycerol (Gly), and water using molecular dynamics simulations. Three ILs, having the same cation, 1‑butyl‑3‑methylimidazolium ([Bmim]⁺), but different anions-hexafluorophosphate ([PF₆]⁻), bis(trifluoromethylsulfonyl)imide ([NTF₂]⁻), and trifluoromethanesulfonate ([TFO]⁻)-were investigated. The local mass density profiles confirmed a well-defined biphasic system for all ILs. [Bmim][PF₆] and [Bmim][TFO] showed excellent results, with 1.3-PDO distribution coefficients ranging from 2.53 to 6.71 and 4.12 to 15.40, respectively. The selectivity towards 1.3-PDO relative to water ranged from 50.6 to 192.50, while selectivity relative to glycerol (2.88–13.83) and 2,3-BDO (4.59–25.67) was also notably high. [Bmim][TFO] exhibited the strongest affinity for 1,3-PDO, with the highest binding energies and more favorable hydrogen bonds. Furthermore, diffusion coefficient analysis indicated that PDO exhibited lower diffusion rates in the extraction phase. Radial distribution function (RDF), spatial distribution function (SDF), and coordination number (CN) analyses confirmed a compact solvation shell and higher 1,3-PDO density around [Bmim][TFO]. Supported by COSMO-SAC thermodynamic model predictions, the study demonstrated that the anion plays a critical role in IL performance. Overall, the results established the extraction performance trend as [Bmim][TFO] > [Bmim][PF₆] > [Bmim][NTF₂], highlighting [Bmim][TFO] as a promising candidate for selective PDO recovery.

通过传统蒸馏从发酵液中选择性提取稀1,3丙二醇（1,3- pdo）（< 20wt %）是具有挑战性的，因为该过程是能源密集型的。采用离子液体等溶剂进行液液萃取（LLE）可以显著降低成本。因此，本研究通过分子动力学模拟探索了咪唑基疏水il从含有1,3- pdo、2,3-丁二醇（2,3- bdo）、甘油（Gly）和水的发酵液中选择性提取1,3- pdo的潜力。研究了三种具有相同阳离子的il - 1 -丁基- 3 -甲基咪唑（[Bmim]+），但阴离子不同的il -六氟磷酸盐（[PF₆]毒发展），二（三氟甲基磺酰）亚胺（[NTF₂]毒发展）和三氟甲烷磺酸（[TFO]毒发展）。局部质量密度分布证实了所有il都是一个定义良好的双相系统。[Bmim][PF6]和[Bmim][TFO]表现优异，其1.3-PDO分布系数分别为2.53 ~ 6.71和4.12 ~ 15.40。对1.3-PDO的选择性为50.6 ~ 192.50，对甘油（2.88 ~ 13.83）和2,3- bdo（4.59 ~ 25.67）的选择性也非常高。[Bmim][TFO]对1,3- pdo的亲和力最强，具有最高的结合能和更有利的氢键。扩散系数分析表明，PDO在萃取相中具有较低的扩散速率。径向分布函数（RDF）、空间分布函数（SDF）和配位数（CN）分析证实了[Bmim][TFO]周围存在致密的溶剂化壳和较高的1,3- pdo密度。在cosmos - sac热力学模型预测的支持下，该研究表明阴离子在IL性能中起着关键作用。总体而言，结果确定了提取性能趋势为[Bmim][TFO] >；[Bmim] [PF₆]比;[Bmim][NTF₂]，突出了[Bmim][TFO]作为选择性PDO回收的有希望的候选物。

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引用次数: 0

Experimental determination and correlation of solubility for R1234ze(E) in POE, PVE, and PAG base oils R1234ze(E)在POE、PVE和PAG基础油中溶解度的实验测定和相关性

IF 2.8 3区工程技术 Q3 CHEMISTRY, PHYSICAL

Fluid Phase Equilibria

Pub Date : 2025-07-10 DOI: 10.1016/j.fluid.2025.114529

Tao Jia , Jinpeng Yang , Jia Yu

Detailed knowledge about the solubility of refrigerant in oil is essential for the design, operation, and long-term reliability of HVAC and refrigeration systems. Herein, as the leading candidates, the solubilities of R1234ze(E) in polyol ester (POE), polyvinylether (PVE), and polyalkylene glycol (PAG) base oils were investigated using the isochoric saturation method at temperatures from 283 K to 353 K. The viscosity grade of the three base oils is ISO VG 68. Additionally, the Peng-Robinson (PR) + Wilson model was successfully applied to correlate the experimental data. The absolute average relative deviations between the experimental and calculated pressures for R1234ze(E) in POE, PVE, and PAG base oils were 1.56 %, 0.91 %, and 1.46 %, respectively. These results provide valuable physical property data for the selection of suitable oils in vapor compression refrigeration systems.

详细了解制冷剂在油中的溶解度对于暖通空调和制冷系统的设计、运行和长期可靠性至关重要。本文以R1234ze(E)为主要候选物，在283 ~ 353 K的温度范围内，采用等向饱和方法研究了R1234ze(E)在多元醇酯（POE）、聚乙烯醚（PVE）和聚烷基二醇（PAG）基础油中的溶解度。三种基础油的粘度等级为ISO VG 68。此外，还成功地应用了Peng-Robinson (PR) + Wilson模型来关联实验数据。POE、PVE和PAG基础油中R1234ze(E)的实验压力与计算压力的绝对平均相对偏差分别为1.56%、0.91%和1.46%。这些结果为在蒸汽压缩制冷系统中选择合适的油提供了有价值的物理性质数据。

引用次数: 0

Editorial for Sabine Enders festschrift on her 60th birthday 萨宾·恩德斯60岁生日的社论

IF 2.8 3区工程技术 Q3 CHEMISTRY, PHYSICAL

Fluid Phase Equilibria

Pub Date : 2025-07-09 DOI: 10.1016/j.fluid.2025.114526

Tim Zeiner , Kai Langenbach , Michael Fischlschweiger , Ioannis G. Economou

引用次数: 0

Graph neural networks embedded into Margules model for vapor–liquid equilibria prediction 将神经网络嵌入marules模型，用于汽液平衡预测

IF 2.8 3区工程技术 Q3 CHEMISTRY, PHYSICAL

Fluid Phase Equilibria

Pub Date : 2025-07-08 DOI: 10.1016/j.fluid.2025.114520

Edgar Ivan Sanchez Medina , Kai Sundmacher

Predictive thermodynamic models are crucial for the early stages of product and process design. In this paper the performance of Graph Neural Networks (GNNs) embedded into a relatively simple excess Gibbs energy model, the extended Margules model, for predicting vapor–liquid equilibrium at low pressures (less than 5 bar) is analyzed. By comparing its performance against the established UNIFAC-Dortmund model it has been shown that GNNs embedded in Margules achieves an overall lower accuracy. However, higher accuracy is observed in the case of various types of binary mixtures. Moreover, since group contribution methods, like UNIFAC, are limited due to feasibility of molecular fragmentation or availability of parameters, the GNN in Margules model offers an alternative for VLE estimation. The findings establish a baseline for the predictive accuracy that simple excess Gibbs energy models combined with GNNs trained solely on infinite dilution data can achieve.

预测热力学模型对于产品和工艺设计的早期阶段至关重要。本文分析了嵌入相对简单的超额吉布斯能量模型（扩展Margules模型）的图神经网络（GNNs）在低压（小于5 bar）下预测汽液平衡的性能。通过将其性能与已建立的UNIFAC-Dortmund模型进行比较，表明嵌入在Margules中的gnn总体上达到了较低的精度。然而，在各种类型的二元混合物的情况下，观察到更高的精度。此外，由于像UNIFAC这样的群体贡献方法由于分子碎片化的可行性或参数的可用性而受到限制，Margules模型中的GNN为VLE估计提供了另一种选择。这些发现为简单的超额吉布斯能量模型与仅在无限稀释数据上训练的gnn相结合可以实现的预测准确性建立了基线。

引用次数: 0

A novel cubic equation of state of a flexible Zc 柔性Zc的一种新的三次状态方程

IF 2.8 3区工程技术 Q3 CHEMISTRY, PHYSICAL

Fluid Phase Equilibria

Pub Date : 2025-07-07 DOI: 10.1016/j.fluid.2025.114527

Lihang Bai , Yulong Ji , Haifeng Ma , Bohao Wu , Maogang He , Wenze Zhu

Classical cubic equations of state (EoSs) cannot produce satisfactory predictions for dense-state fluids because of the missing molecular repulsion effect. This work introduces a newly developed cubic EoS of a flexible critical compressibility Z_c by incorporating a repulsion term. Its α-function is redefined and capable of reliable extrapolation throughout the entire temperature range. As straightforward as the Soave-Redlich-Kwong (SRK) EoS, all the necessary parameters of the new EoS can be determined using the critical properties (T_c, p_c, v_c) and acentric factors. Tested upon pure and multi-component fluids, the new EoS demonstrates superior robustness and accuracy compared to the SRK EoS.

由于缺少分子斥力效应，经典的三次状态方程（eos）不能对密态流体产生令人满意的预测。本文通过引入排斥项，介绍了一个新开发的柔性临界压缩率Zc的三次方程。它的α-函数被重新定义，并能够在整个温度范围内可靠地外推。与Soave-Redlich-Kwong (SRK) EoS一样简单，新EoS的所有必要参数都可以使用临界性质（Tc, pc, vc）和离心因子来确定。在纯流体和多组分流体中进行的测试表明，与SRK EoS相比，新型EoS具有更高的稳健性和准确性。

引用次数: 0

Corrigendum to “Using Physical Property Models and Artificial Intelligence to Design Chemical Products in the journal Fluid Phase Equilibria” [Fluid Phase Equilibria 596 (2025) 114441] 《流体相平衡》杂志“使用物理性质模型和人工智能设计化学产品”的勘误表[流体相平衡596 (2025)114441]

IF 2.8 3区工程技术 Q3 CHEMISTRY, PHYSICAL

Fluid Phase Equilibria

Pub Date : 2025-07-07 DOI: 10.1016/j.fluid.2025.114505

Kevin G. Joback

引用次数: 0

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