Prediction Of Phase Equilibria Research Articles

Optimizing phase equilibrium predictions for the liquefaction of supercritical water gasification products: Enhancing energy storage solutions through advanced thermodynamic modeling

Supercritical water gasification products typically consist of a vapor mixture consisting of H2 and CO2 with high pressure. Liquefaction of supercritical water gasification products not only allows the vapor mixture to be reduced in volume for easy transportation, but also allows liquid CO2 to be obtained from it, and also serves as a form of energy storage. Under the existing thermodynamic model, the prediction of the liquefaction dew point under high pressure is easily diverged and the accuracy is not enough. In this paper, we obtain the value of CO2+H2 binary interaction coefficient under high pressure kij=0.146 by the fitting method and, which improves the convergence of the predicted phase equilibrium data at high pressure and obtains the results with higher accuracy. In the prediction of dew point of supercritical water gasification products, the fluctuation of H2 content has little effect on the liquefaction pressure, and more significant is the effect of the liquefaction temperature, and it is more economical to carry out the liquefaction work within the range of −30 °C to −5 °C. At the same time, in the liquefaction products lower than −10 °C, the liquid CO2 with the mole fraction of more than 0.9 can be obtained.

Phase equilibrium data prediction and process optimizationin butadiene extraction process

In response to the lack of reliable physical parameters in the process simulation of the butadiene extraction, a large amount of phase equilibrium data was collected in the context of the actual process of butadiene production by acetonitrile. The accuracy of five prediction methods, UNIFAC, UNIFAC-LL, UNIFAC-LBY, UNIFAC-DMD, and COSMO-RS, applied to the butadiene extraction process was verified using partial phase equilibrium data. The results showed that the UNIFAC-DMD method had the highest accuracy in predicting phase equilibrium data for the missing system. COSMO-RS predicted multiple systems showed good accuracy. And a large number of missing phase equilibrium data were estimated using the UNIFAC-DMD method and COSMO-RS method. The predicted phase equilibrium data were checked for consistency. The NRTL-RK and UNIQUAC thermodynamic models were used to correlate the phase equilibrium data. Industrial device simulations were used to verify the accuracy of the thermodynamic model applied to the butadiene extraction process. The simulation results showed that the average deviations of the simulated results using the correlated thermodynamic model from the actual values were less than 2% compared to that using the commercial simulation software Aspen Plus and its database. The average deviation was much smaller than that of the simulations using the Aspen Plus database (>10%), indicating that the obtained phase equilibrium data are highly accurate and reliable. The best phase equilibrium data and thermodynamic model parameters for butadiene extraction are provided. This improves the accuracy and reliability of the design, optimization and control of the process, and provides a basis and guarantee for developing a more environmentally friendly and economical butadiene extraction process.

A novel model to predict phase equilibrium state of hydrates from the relationship of gas solubility

The study of hydrate phase equilibrium is crucial for ensuring the safety of natural gas pipeline transportation and the process of hydrate recovery. While scientists typically focus on the chemical potential of hydrates, the role of gas solubility in hydrate phase equilibrium remains unclear, and this study fills this gap. This work investigated the solubility of gas at the equilibrium point of the hydrate phase through model calculations. Additionally, a new model of hydrate phase equilibrium is established based on the relationship between solubility. Firstly, a solubility model based on gas-liquid equilibrium theory showed higher prediction accuracy in comparison to the PR equation and Duan model and was then used to calculate gas solubility under hydrate phase equilibrium conditions. Afterwards, a novel model was developed to predict hydrate equilibrium state based on the relationship between gas solubility and hydrate phase equilibrium temperature, and it was further compared with the Chen–Guo model and CSMGem in terms of prediction accuracy under pure water and brine settings. The results showed: (a) The calculation deviation of the solubility model was 0.7–8.7% in pure water settings and 2.6–11.7% in brine settings; (b) A strong linear correlation between the phase equilibrium temperature of hydrates and gas solubility was also found; (c) This proposed model achieved over 10 times the accuracy of the Chen–Guo model and the CSMGem in predicting the phase equilibrium state of N2 and CO2 hydrates, and 3–10 times higher accuracy than that of the Chen–Guo model and CSMGem in brine. This work suggests that the gas solubility equilibrium theory can provide a more accurate prediction of hydrate states.

EXPERIMENTAL STUDY AND THERMODYNAMIC SIMULATION OF CO2 HYDRATE PHASE EQUILIBRIUM CONDITIONS IN POROUS MEDIA

The phase equilibrium of CO<sub>2</sub> hydrates on various types of porous media is studied by experiment and model. The experiments are conducted under controlled conditions to measure the hydrate equilibrium conditions. The proposed model is based on the Chen-Guo theory and incorporates the surface property parameters for each type of porous media. The predictions of model are validated by comparing them to experimental data, and the predicted temperature deviation is within 0.25 K. Furthermore, the accuracy of model is compared with other existing models, and the calculation accuracy of this model in glass beads with weak water absorption is 0.05 K higher than that of the existing model, and 0.09 K higher in sand with strong water absorption. The study contributes to a better understanding of CO<sub>2</sub> hydrate formation on different porous media and provides a reliable model for predicting phase equilibrium conditions in such systems.

Multipolar SAFT-VR Mie Equation of State: Predictions of Phase Equilibria in Refrigerant Systems with No Binary Interaction Parameter.

An extension of the SAFT-VR Mie equation of state is proposed to predict the properties of multipolar fluids. The new model, referred to as multipolar M-SAFT-VR Mie, incorporates the general multipolar term developed by Gubbins and co-workers, which accounts for dipole-dipole, quadrupole-quadrupole, and dipole-quadrupole interactions. A modification of the third order terms in the perturbation theory results in an accurate description of the simulation data for multipolar Lennard-Jones fluids. Both the M-SAFT-VR Mie and polar soft-SAFT models are extended to account for polarizability, and a good agreement is obtained with molecular simulation data. The M-SAFT-VR Mie model is applied to refrigerant systems, and it is found that including both dipole and quadrupole moments in molecular models leads to more accurate results than using only a dipole moment. The new model provides excellent predictions of the vapor-liquid equilibria of zeotropic and azeotropic refrigerant mixtures without the need for binary interaction parameters, making it a valuable tool for formulating low-GWP working fluids.

Correlating Pure Component Properties with MOSCED Solubility Parameters: Enthalpy of Vaporization and Vapor Pressure

Tools to predict vapor–liquid phase equilibria are indispensable for the conceptualization and design of separation processes. Modified separation of cohesive energy density (MOSCED) is a solubility-parameter-based method parameterized to make accurate predictions of the limiting activity coefficient. As a solubility-parameter-based method, MOSCED can not only make quantitative predictions, but can shed light on the underlying intermolecular interactions. In the present study, we demonstrated the ability of MOSCED to correlate the enthalpy of vaporization and vapor pressure at a specific temperature using multiple linear regression. With this addition, MOSCED is able to predict vapor–liquid phase equilibria in the absence of reference data. This was demonstrated for the prediction of the Henry’s constant and solvation free energy of organic solutes in water, which was found to be superior to mod-UNIFAC. In addition to being able to make phase equilibrium predictions, the ability to correlate the enthalpy of vaporization and vapor pressure offers the opportunity to include additional properties in the regression of the MOSCED parameters. Given this success, we additionally attempted to correlate a wide range of physical properties using a similar expression. While, in some cases, the results were reasonable, they were inferior to the correlations of the enthalpy of vaporization and vapor pressure. Future efforts will be needed to improve the correlations.

Prediction method for methane solubility in high-temperature and high-pressure aqueous solutions in ultra-deep drilling

During ultra-deep oil and gas exploration and development, overflow can easily occur when drilling in high-temperature (≤473.15 K) and high-pressure (≤150 MPa) reservoirs. The invaded methane gas is more soluble in the drilling fluid under high temperature and pressure, and the concealment is enhanced. Low temperature and pressure at the wellhead cause rapid expansion and precipitation of the dissolved gas, thereby increasing the risk of blowout. Therefore, the safe development of the ultra-deep oil and gas drilling process is critical to accurately determine the solubility of natural gas under alternating high- and low-temperature and high-pressure conditions in ultra-deep drilling wellbores. In this study, considering the presence and absence of hydrates at low temperature, and the conditions of high temperature and high pressure, the phase equilibrium prediction fugacity–fugacity model of methane and the aqueous solution is established. At the same time, the solubility experimental data of existing CH4 in aqueous solution are counted. The prediction model is established according to the particle swarm optimization support vector machine (PSO–SVM) algorithm. The new thermodynamic fugacity–fugacity model can be applied to predict the methane solubility and water content in the gas phase under the following ultra-deep drilling conditions: temperature from 273.15 to 473.15 K, pressure up to 150 MPa, and salinity from 0 to 5.4 mol kg−1. The prediction errors for the presence and absence of hydrate at 273.15–293.15 K and 273.15–473.15 K are within 8%. The calculation error from the PSO–SVM machine learning model for the interactive solubility of methane and water is maintained within 10%, but the prediction error at atmospheric pressure exceeds 10%. The machine learning model strongly depends on abundant statistical experimental data. The prediction of gas dissolution in ultra-deep oil and gas development should be based on thermodynamic models.

Energy landscape analysis for two-phase multi-component NVT flash systems by using ETD type high-index saddle dynamics

With the increasingly accurate modeling and simulation demands and techniques, obtaining the knowledge of the multi-component phase equilibrium states holds the bottleneck challenge in the study of multi-phase fluid flow. In order to resolve the shortages in computational efficiency and stability in the conventional iterative flash calculation, a new phase equilibrium prediction method is proposed by solving the saddle point of the multi-phase system. In this paper, the HiSD (High-index saddle point dynamics) algorithm is used for the first time to calculate the saddle points on the energy landscape of the two-phase two-component NVT flash model based on the Peng-Robinson equation of state, and the up-down search algorithm of HiSD is applied to generate the solution landscape of the flash system. The Rosenbrock-Euler ETD (exponential time differencing) format is involved to reduce the interference of system rigidity to the calculation. It can be referred from the numerical analysis that there are at most the 1st-order saddle points in the energy landscape of the two-component two-phase NVT flash system, and all these saddle points are located on one straight line of the hyperplane, where the energy is equal everywhere. All these 1st-order saddle points can converge to the same or equivalent local minima, which indicates that the two-component two-phase flash system is a system with only one single solution with physical meanings. In addition, the saddle points also obey a linear relationship and the energy remains the same at different temperatures. Therefore, using the method proposed in this paper, the conventional two-step efforts of phase stability test and phase separation calculation can be simplified. The 1st-order saddle points of the system can be directly calculated, reducing the need for an initial guess. The local minima can be directly searched through the downward direction of the saddle point, which greatly reduces the calculation amount of phase equilibrium calculations. Furthermore, the minimum states at different temperatures can be calculated in batch by using one certain initial value, which significantly improves the adaptability and reliability for complex engineering problems with drastic temperature changes.

Artificial neural network models for phase equilibrium predictions under engine trans/supercritical spray conditions

Engine spray models based on phase equilibrium have made great progress in simulating trans/supercritical engine spray processes, but there are inherent weaknesses in terms of efficiency and stability for the conventional phase equilibrium algorithm due to the iterative schemes for solving complex nonlinear equations. The low efficiency of the conventional algorithm limits the amount of detail that can be considered in the simulation, while the instability may lead to unphysical results or even simulation divergence. In this work, a method based on artificial neural networks (ANNs) was developed as a potential alternative to the conventional algorithm applied in the engine spray models to achieve fast and robust phase equilibrium calculations. Three ANNs were constructed, including isothermal-isobaric-ANN (TPn-ANN), isenthalpic-isobaric-ANN (HPn-ANN) and adiabatic-mixing-temperature-ANN (AMT-ANN). The latter two models combined with TPN-ANN can be applied to heat and mass transfer flow and adiabatic mixing problems, respectively, to achieve the prediction of phase equilibrium temperature, phase stability and phase splitting. The current work shows that the ANN method leads to significant efficiency improvements while maintaining almost the same accuracy as the conventional algorithm. Analysis of execution time for a high-fidelity n-dodecane spray simulation shows that the conventional phase equilibrium calculation can take up to 70% of total computational time, which can be reduced to negligible levels with the current proposed ANN approach.

Measurements and predictions of phase equilibria in the quaternary system KBr + MgBr2 + SrBr2 + H2O at 273 K and 308 K

The underground brines in Sichuan Basin of China are rich in potassium, magnesium, strontium, bromine. Consequently, the studies of phase equilibria for the underground brines are of great significance. The phase equilibria of the quaternary system KBr + MgBr 2 + SrBr 2 + H 2 O at 273 K and 308 K are determined by the isothermal dissolution equilibrium method in this work. Firstly, the equilibrium liquid phase compositions at two temperatures were measured by chemical analysis. Secondly, the corresponding solid phases were identified by X-ray powder diffraction method. As a result, the corresponding phase diagrams were drawn based on the obtained data. The equilibrium phase diagrams all include four crystallization fields (SrBr 2 ·6H 2 O, MgBr 2 ·6H 2 O, KBr·MgBr 2 ·6H 2 O and KBr), five isothermal solubility curves and two invariant points, which present the same trend at the two temperatures. Furthermore, the mixed ion interaction parameters ( θ Mg , Sr , φ K , Sr , Br , φ Mg , Sr , Br ) of Pitzer model, which have not been reported in the literatures, were obtained by using the solubility data of the ternary system and multiple linear regression. And Pitzer equation and particle swarm optimization algorithm were used to simulate and predict the solubility of salts in the quaternary system. By comparing the calculated phase diagrams at 273 K and 308 K, some obvious deviation in crystalline phase zone of MgBr 2 ·6H 2 O and KBr·MgBr 2 ·6H 2 O at 273 K have been found. And both of them are within the reasonable deviation range. The results show that the fitted parameters and the calculated model of the mixed ion interaction are reliable, and the calculated data agree well with the experimental data.

Thermodynamic modeling of gas solubility in ionic liquids using equations of state

This work aimed at the thermodynamic modeling of gas solubility in ionic liquids (ILs) using the Soave-Redlich-Kwong (SRK), cubic-plus-association (CPA), and perturbed-chain statistical associating fluid theory (PC-SAFT) equations of state. Wherefore, the routines were developed for the parameterization of ILs. Then, the ILs were implemented in the Aspen plus simulator to evaluate the equations of state and explore the phase equilibrium data with the predictive equations and the correlation of the binary interaction parameter. Hence, it was verified the correlation of the density and speed of sound curves presented limitations to correcting the slope of the curves of pure ILs. Nonetheless, the PC-SAFT with the 4C associative scheme demonstrated a better fit for the thermophysical properties. As for the prediction of phase equilibrium for the [EMIM][TfO], the PC-SAFT with the 2B scheme showed a better fit with CO2, while the CPA with the 2B scheme presented the best result for H2S. For [OMIM][NTf2], the PC-SAFT with the 1A scheme showed better results with CO2, and the CPA with the 2B scheme showed the lowest deviation with H2S.

Improving water–hydrocarbon equilibrium calculations using multi objective optimization

The addition of chemical terms to Cubic Equations of State to improve polar components Vapor–Liquid Equilibrium prediction overestimates the critical point. In this paper, we analyze the mathematical behavior of these equations and propose a new methodology based on multi-objective optimization with four independent functions, saturation pressure, saturated liquid volume, and two critical points constraints to estimate the pure component parameters for the equation of state. The effect of different parameters sets on the phase equilibrium prediction and binary interaction coefficient for some binary water–hydrocarbon systems is presented and discussed, showing the improvement of the proposed technique.

Prediction of phase equilibria, density, speed of sound and viscosity of 2-alkoxyethanols mixtures: A comparison study between SAFT type EoSs and a modified PR EoS

In this work, a modified Peng-Robinson equation of state with the Huron-Vidal-NRTL mixing rule was used to describe complex polar phase equilibria, density, speed of sound and viscosity at low pressure of alkoxyethanols/alkane, alkoxyethanols/isoalkanes and 2-butoxyethanol/water mixtures. The experimental data is gathered from the literature of a selected alkoxyethanols/alkanes series with the aim of developed generalized expressions for the binary interaction parameters required in the mixing rule model as a function of the RTc/Pc ratio of alkanes. In total 19 mixtures were analyzed (6 used in correlation and 13 mixtures used in prediction processes). For each type of mixture, the generalized expressions were obtained by fitting experimental liquid-liquid equilibria (LLE) data of 3 different mixtures at 100 kPa and to validate them, LLE and vapor-liquid equilibria (VLE) predictions were performed. Adequate results were obtained in all cases. Also, the predictive capabilities of the generalized EoS model have been tested using density, and speed of sound estimations. The overall deviation is below 1.10% for density and 6.84% for speed of sound. Also, the viscosity is correlated and predicted using a simple mixing rule coupled with the generalized EoS model and the absolute deviation is below 3.86%. Finally, two cases of study have been implemented to analyze the possibility of the generalized model to predict other branched-chain alkanes and water systems. The overall results indicated a good agreement with experimental data and proved that the EoS coupled with the Huron-Vidal mixing rule can describe high polar systems and their properties with acceptable and low deviations in comparison to other EoS such as SAFT types or CPA approaches.

Measurements of mean activity coefficients and solubility prediction in ternary system KBr-K2SO4-H2O at 308.15 K and 288.15 K

In this work, the mean activity coefficients of KBr in KBr-H2O binary system and KBr-K2SO4-H2O ternary system were determined at 308.15 K and 288.15 K by the cell potential method. The potassium ion selective electrode and bromide ion selective electrode are used to measure the cell potential value of single salt electrolyte solution,and the standard potential value E0 and electrode response slope k of the binary system are obtained. The experimental results showed that ion selective electrodes of used in this work had a good Nernst response. The mean activity coefficients KBr in KBr-K2SO4-H2O system are also determined, the total ionic strength in the mixed solution ranging from (0.0100 to 1.0000) mol·kg−1, and ionic strength fractions yb of K2SO4 with yb=(0.8, 0.6, 0.4, 0.2 and 0.0). Using mean activity coefficients obtained in this work and Pitzer model, the Pitzer mixed ion interaction parameters θBr,SO4 and ψK,Br,SO4are fitted respectively. Furthermore, those osmotic coefficient Φ, water activity aw, excess Gibbs free energy GE were also calculated by Pitzer’s equations. The solubilities of salts in the KBr-K2SO4-H2O system at 308.15 K and 288.15 K are predicted by using Pitzer equations and ion interaction parameters fitted in this work, and phase diagrams of the ternary system are also plotted according to the calculated solubilities. The results show that the ion interaction parameters of Pitzer equations by fitting the activity coefficients can be used for calculation thermodynamic parameters and prediction of phase equilibria.

Experimental and modeling investigations of hydrate phase equilibria in natural clayey-silty sediments

Rapid and accurate acquisition of hydrate phase equilibria in sediments is crucial for gas hydrate resource assessment and exploitation and hydrate-based technological applications. However, current models have significant limitations and deficiencies in predicting hydrate phase equilibria in sediments, especially clayey-silty sediments prevalent in nature. To this end, a unified hydrate phase equilibrium model was developed, which considers the combined inhibitions of surface adsorption, capillary effect, and salt solution. It is derived that water content and salinity can be used as direct input parameters to the model to estimate the hydrate dissociation temperature depression. Using the stepwise heating method, the hydrate dissociation conditions in various natural sediments were measured. It suggests that montmorillonite has the greatest dissociation temperature depression, followed by SA sediments and kaolin, while pore hydrates in silts exhibit almost the same thermodynamic equilibrium conditions as bulk hydrates unless the water content is below 15%. Special attention was also paid to the additional inhibition of surface adsorption on hydrate phase equilibria in sediments with salt solutions. This inhibition was found to be quite pronounced in clay-rich sediments, especially expansive clays, but essentially negligible in silty or sandy sediments. The maximum average error of 3.29% was observed between model predictions and measured data. Additionally, the amounts of clathrated water (CW), non-equilibrium unclathrated water (NEUW), and equilibrium unclathrated water (EUW) in sediments after the end of hydrate formation were determined using the model. It reveals that CW has the highest proportion in silts, reaching 68.9%, while only 0.231 in montmorillonite; in contrast, EUW is dominant in montmorillonite; NEUW seems to be independent of lithology but shows a strong dependence on the water content. It implies that silty sediments are more conductive to hydrate-based gas storage and CO2 sequestration than clayey sediments. This study provides some practical insights and implications for hydrate phase behaviors in natural sediments and can potentially be employed as a tool for phase equilibrium prediction with universality and accuracy.

Modeling vapor–liquid equilibrium and liquid–liquid extraction of deep eutectic solvents and ionic liquids using perturbed‐chain statistical associating fluid theory equation of state. Part II

AbstractThis study aims to use perturbed‐chain statistical associating fluid theory (PC‐SAFT) to describe the phase behavior of systems containing deep eutectic solvents (DESs) and ionic liquids (ILs). The DESs are based on tetrabutylammonium chloride and tetrabutylammonium bromide as hydrogen bond acceptors, and levulinic acid and diethylene glycol as hydrogen bond donors in the mole ratio of 1:2 and 1:4, respectively. Predictions of phase equilibria by PC‐SAFT were compared with the results of COnductor like Screening MOdel for Real Solvents (COSMO‐RS) and non‐random two‐liquid (NRTL). In this work, low viscosity ether‐ and pyridinium‐based ILs [EnPy][NTf2] and [CmPy][NTf2] were used for vapor–liquid equilibrium systems, while 1‐(2‐methoxyethyl)‐1‐methylpyrrolidinium bis(trifluoromethylsulfonyl)‐amide and 1‐propyl‐3‐methylimidazolium bis{trifluoromethylsulfonyl}imide with n‐heptane + thiophene and n‐hexane + ethylbenzene were used in the liquid–liquid extraction, respectively. In the last part, the phase behavior of the mixtures of perfluoroalkylalkanes with their linear alkane counterparts was studied and compared with the SAFT‐Mie pair potential.

Prediction of phase equilibrium between soybean biodiesel, alcohols and supercritical CO2 using artificial neural networks

In this paper, a non-conventional approach of modeling phase equilibrium was applied. An alternative tool, the artificial neural network (ANN) technique has been used for estimating transition pressures for two ternary systems at high pressures (CO2 + Biodiesel + Methanol) and (CO2 + Biodiesel + Ethanol). Temperatures, molar ratios, and compositions were utilized as input variables at ranges of 303.15 to 343.15 K, 4.30 to 15.62 MPa and 0.4 to 0.99, respectively. The databases taken from the literature were split into training, validating, and testing data. Multiple ANN structures were applied and the model with the lowest mean square error (MSE) was selected. The selected ANN model for the methanol system was a two-layered Feed-Forward Network and achieved a determination coefficient (R2) of 0.99878 and MSE of 0.01612. While the ethanol system was best described by an Elman Network presenting an R2 and MSE of 0.99359 and 0.06078, respectively. Results were then compared with Peng-Robinson models using van der Waals quadratic and Wong-Sandler mixing rules. The results showed a better agreement with experimental data than the thermodynamic models.

Fast prediction of phase equilibrium at varying temperatures for use in multi-component phase field models

A new method for temperature-dependent phase equilibrium prediction for use in multi-component phase field models of solidification is proposed. The method consists of two parts. First, the convex hull method is applied to predict the phase equilibrium at a single temperature. Second, a set of linear equations is developed to extend the equilibrium calculation over a range of temperatures. These linear equations are derived as an extension of the equation used for solidification of binary alloys in approximating the equilibrium state of multi-component systems. Phase field simulations of solidification of a Ti-Al-V-Fe alloy are performed to demonstrate the effectiveness of the present approach under isothermal and continuous cooling conditions. The results are compared against Thermo-Calc calculations, and indicate that a high accuracy of equilibrium prediction is achieved at a single and multiple temperatures, thus demonstrating that this approach can be successfully applied to the multi-component phase field models.

Predictive molecular thermodynamic models for ionic liquids

AbstractPredictive molecular thermodynamic models can bridge the gap between the microscopic molecular level and macroscopic system scale. Over the past few decades, ionic liquids (ILs), as a class of green solvents and functional materials, have received widespread research interest in the field of chemical processing owing to their unique physicochemical merits. This review aims to provide an easy‐to‐read and exhaustive reference regarding state‐of‐the‐art predictive thermodynamic models for ILs, with more focuses on UNIFAC‐ and COSMO‐based models and various applications involving phase equilibrium prediction, guidance for IL screening and design, and building equilibrium stage models for separation processes. This review provides a theoretical perspective on the structure–property relationships between molecular structures and phase behaviors for the systems and the constituted components covering a multi‐scale viewpoint from molecular level to industrial scale. Moreover, the predictive capacities of different thermodynamic models are comprehensively compared.

Vapor-liquid equilibrium (VLE) prediction for dimethyl ether (DME) and water system in DME injection process with Peng-Robinson equation of state and composition dependent binary interaction coefficient

Dimethyl ether (DME) is arousing attention as a novel water-soluble additive in oil industry. The accurate prediction of phase behavior of DME and water system is crucial important for DME-based research. An equation of state has been a powerful tool for solving phase equilibrium problem, which is based on an ideal molecular force model with binary interaction coefficients reflecting the deviation of a non-ideal system. However, the current knowledge of interaction coefficient is limited by obtaining from backward by using phase equilibrium data. This leads to the unclear meaning of the interaction coefficients, insufficient response to the molecular force interaction relationship at the molecular level and no ability to predict phase equilibrium properties without primary use of experimental data. To overcome this, in this study a correction by combining an activity coefficient and a linear solvation energy relationship (LSER) has been proposed to address the solubility deviation from an idealized model. This deviation at the micro level indicates the deviation of nonideal molecular forces from the ideal Raoult's law. Based on this novel correction, binary interaction coefficients have been obtained with a more practical molecular interaction relationship, which leads to more consistent results with experimental data from the literature. Moreover, in asymmetric phase systems, concentration-dependent binary interaction coefficients have been proposed based on previous discussion to represent intermolecular forces in non-ideal phase systems. Furthermore, partitioning coefficients, which lead to a potential criterion for solvent selection for heavy oil recovery, have been discussed from the perspective of intermolecular forces. This study provides new insights into non-ideal phase behavior. By combining a LSER and activity coefficients, a quantitative analysis on non-ideal molecular behavior and related complex phase problems becomes possible.