Perturbed-chain Statistical Associating Fluid Theory Research Articles

Modeling the solubility of oxaprozin and irbesartan in biorelevant complex solutions based on a combination of pH-dependent and micellar solubilization models

Biological solubility is one of the important basic parameters in the development process of poorly soluble drugs, but the current measurement methods are mainly based on a large number of experiments, which are time-consuming and cost-intensive. There is still a lack of effective theoretical models to accurately describe and predict the biological solubility of drugs to reduce costs. Therefore, in this study, osaprazole and irbesartan were selected as model drugs, and their solubility in solutions containing surfactants and biorelevant media was measured experimentally. By calculating the parameters of each component using the perturbed-chain statistical associating fluid theory (PC-SAFT) model, combined with pH-dependent and micellar solubilization models, the thermodynamic phase behavior of the two drugs was successfully modeled, and the predicted results were in good agreement with the experimental values. These results demonstrate that the model combination used provides important basic parameters and theoretical guidance for the development and screening of poorly soluble drugs and related formulations.

Evaluation of the perturbed hard-sphere-chain equation of state for calculations of methane hydrate formation condition in the presence of ionic liquids

This work aims to evaluate the performance of the Perturbed Hard-Sphere-Chain (PHSC) equation of state (EoS) for the calculation of methane hydrate formation in the presence of ionic liquids (ILs). The van der Waals and Platteeuw model is utilized to calculate the hydrate dissociation pressure. The performance of the PHSC model is compared to cubic EoSs and the Perturbed Chain Statistical Associating Fluid Theory (PC-SAFT) model. Two activity coefficient models are used to estimate the water activity in the presence of ILs. The results show that PHSC EoS with an activity coefficient model provides lower average error values (lower than 2%) and changing the activity coefficient models does not have a great effect on reducing the error. Also, the results of cubic-based EoSs are quite remarkable considering their simplicity. The PHSC model can be utilized as a robust and efficient thermodynamic model for hydrate dissociation pressure calculation in the presence of IL.

Predicting Solvation Free Energies from the Minnesota Solvation Database Using Classical Density Functional Theory Based on the PC-SAFT Equation of State.

We critically assess the capabilities of classical density functional theory (DFT) based on the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state to predict the solvation free energies of small molecules in various hydrocarbon solvents. We compare DFT results with experimental data from the Minnesota solvation database and utilize statistical methods to analyze the accuracy of our approach, as well as its weaknesses. The mean absolute error of the solvation free energies is 3.7 kJ mol-1 for n-alkane solvents, ranging from pentane to hexadecane, with 473 solute-solvent systems. For solvents consisting of cyclic hydrocarbons (cyclohexane, benzene, toluene, and ethylbenzene) with 245 solute-solvent systems, we report a slightly larger mean absolute error of 4.2 kJ mol-1. We identify three possible sources of errors: (i) the neglect of solute-solvent and solvent-solvent Coulomb interactions, which limits the applicability of PC-SAFT DFT to nonpolar and weakly polar molecules; (ii) the solute's Lennard-Jones parameters supplied by the general AMBER force field, which are not parametrized toward solvation free energies; and (iii) the application of the Lorentz-Berthelot combining rules to the dispersive interactions between a segment of the PC-SAFT solvent and a Lennard-Jones interaction site of the solute. The approach is more accurate than standard implementations of phenomenological models in common chemistry software packages, which exhibit mean absolute errors larger than 9.12 kJ mol-1, even though newer phenomenological models achieve a mean absolute error of about 2 kJ mol-1. PC-SAFT DFT is more computationally efficient than state of the art explicit molecular simulations in combination with free energy perturbation methods. It is predictive with respect to solvation free energies, i.e., the input for the model is the (element-specific) molecular force field, the solute configuration from molecular dynamics simulations, and the (substance-specific) PC-SAFT parameters. The PC-SAFT parametrization uses pure-component data and does not require experimental solvation free energies. The PC-SAFT equation of state, without applying a DFT formalism, can also be used to calculate solvation free energies, provided that the PC-SAFT parameters for the solute are available. A large number of substances was recently parametrized by members of our group (Esper, T.; Bauer, G.; Rehner, P.; Gross, J. Ind. Eng. Chem. Res. 2023, 62), which enables a comparison to the DFT approach for 103 substances. Accurate results are obtained from the PC-SAFT equation of state with an MAE below 2.51 kJ mol-1. The DFT approach does not require PC-SAFT parameters for the solute and can be applied to all solutes that can be represented by the molecular force field.

Density and viscosity measurement of R513A and a modified residual entropy scaling model for predicting the viscosity of HFC/HFO refrigerants

Liquid density and viscosity of alternative refrigerants R513A were measured with a vibrating-wire viscosimeter in the temperature of 253 K to 363 K when pressure changes from 1 MPa to 12 MPa. The combined expended uncertainties with a confidence level of 0.95 (k=2) of density and viscosity are 0.2% and 2%, respectively. In addition, a viscosity model of HFCs (fluorocarbons)/, HFOs (hydro-fluoroolefins) and their mixtures was provided by coupling the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) equation of state and a modified residual entropy scaling (RES) method. Obvious quasi-linear relation between the proposed entropy variable and the modified residual viscosity has been confirmed. The overall average absolute percentage deviations between the calculated results with the proposed RES model and the literature experimental data of pure and mixture refrigerants are 2.63% and 2.05, respectively.

Viscosities of inhomogeneous systems from generalized entropy scaling

This study extends entropy scaling to inhomogeneous fluids by using the classical density functional theory together with a new viscosity reference that takes into account the influence of solid–fluid interactions on the fluid viscosity. The density functional theory uses a Helmholtz energy functional based on the perturbed-chain statistical associating fluid theory; the local residual entropy per particle is determined from the temperature derivative of the Helmholtz energy functional in combination with an appropriate weighted density profile. The weighted density calculation requires a single transferable parameter, which is adjusted to a reference molecular dynamics simulation. In particular, local viscosity values for fluids under nanoconfinement near solid–fluid interfaces are predicted using the same entropy scaling parameters as for homogeneous fluids. We validate the model by comparing viscosity and velocity profiles with results from non-equilibrium molecular dynamics simulations of a Couette flow in a slit pore. Good agreement is found between the entropy scaling model and the non-equilibrium molecular dynamics results for both the viscosity and velocity profiles of the Lennard–Jones truncated and shifted fluid. The proposed model extrapolates well to systems with different temperatures, fluid densities, and shear forces as well as to systems with different wetting behaviors. These results demonstrate that entropy scaling can be generalized to inhomogeneous fluids using an appropriate combination of residual entropy profile and viscosity reference.

Thermodynamic analysis of a dual-pressure evaporation high-temperature heat pump with low GWP zeotropic mixtures for steam generation

High-temperature heat pumps (HTHPs) have gained attention due to their economic and environmental benefits in utilizing industrial waste heat for steam generation. This study focuses on improving the HTHPs’ performance by employing two-stage separation and dual-pressure evaporation technology in the auto-cascade heat pump cycle. Additionally, binary zeotropic refrigerant mixtures with low-GWP are selected using the polar perturbed-chain statistical associated fluid theory (PC-SAFT) equation of state. The findings indicate that the R1234ze(E)&R1233zd(E) refrigerant mixture outperforms other potential alternatives, exhibiting a thermodynamic effectiveness 0.85%–1.86% higher than the benchmark mixture, R134a&R245fa. The improved cycle demonstrates significant enhancements, achieving a 45.17% increase in heat source utilization efficiency and a 24.48% improvement in COP compared to the basic auto-cascade cycle. Effective temperature matching between refrigerant mixtures and heat sources/sinks is guaranteed in the improved cycle. Moreover, a parameter analysis reveals that increasing the subcooling degree of the cascaded heat exchanger and the separation dryness fraction at separator 2 enables improvements in both COP and heat source utilization efficiency. These findings provide valuable insights into the design of steam generation heat pumps and the selection of refrigerant mixtures.

Dissolution Mechanisms of Amorphous Solid Dispersions: Application of Ternary Phase Diagrams To Explain Release Behavior.

The use of amorphous solid dispersions (ASDs) in commercial drug products has increased in recent years due to the large number of poorly soluble drugs in the pharmaceutical pipeline. However, the release behavior of ASDs is complex and remains not well understood. Often, the drug release from ASDs is rapid and complete at lower drug loadings (DLs) but becomes slow and incomplete at higher DLs. The DL where release becomes hindered is termed the limit of congruency (LoC). Currently, there are no approaches to predict the LoC. However, recent findings show that one potential cause leading to the LoC is a change in phase morphology after water-induced phase separation at the ASD/solution interface. In this study, the phase behavior of ASDs in contact with aqueous solutions was described thermodynamically by constructing experimental and computational ternary phase diagrams, and these were used to predict morphology changes and ultimately the LoC. Experimental ternary phase diagrams were obtained by equilibrating ASD/water mixtures over time. Computational ternary phase diagrams were obtained by Perturbed Chain Statistical Associating Fluid Theory (PC-SAFT). The morphology of the hydrophobic phase was studied with fluorescence confocal microscopy. It was demonstrated that critical point (plait point) composition approximately corresponded to the ASD DL, where the hydrophobic phase, formed during phase separation, became interconnected and hindered ASD release. This work provides mechanistic insights into the ASD release behavior and highlights the potential of in silico ASD design using phase diagrams.

Prediction of water anomalous properties by introducing the two-state theory in SAFT.

Water is one of the most abundant substances on earth, but it is still not entirely understood. It shows unusual behavior, and its properties present characteristic extrema unlike any other fluid. This unusual behavior has been linked to the two-state theory of water, which proposes that water forms different clusters, one with a high density and one with a low density, which may even form two distinct phases at low temperatures. Models incorporating the two-state theory manage to capture the unusual extrema of water, unlike traditional equations of state, which fail. In this work, we have derived the framework to incorporate the two-state theory of water into the Statistical-Associating-Fluid-Theory (SAFT). More specifically, we have assumed that water is an ideal solution of high density water molecules and low density water molecules that are in chemical equilibrium. Using this assumption, we have generalized the association term SAFT to allow for the simultaneous existence of the two water types, which have the same physical parameters but different association properties. We have incorporated the newly derived association term in the context of the Perturbed Chain-SAFT (PC-SAFT). The new model is referred to as PC-SAFT-Two-State (PC-SAFT-TS). Using PC-SAFT-TS, we have succeeded in predicting the characteristic extrema of water, such as its density and speed of sound maximum, etc., without loss of accuracy compared to the original PC-SAFT. This new framework is readily extended to mixtures, and PC-SAFT-TS manages to capture the solubility minimum of hydrocarbons in water in a straightforward manner.

Solubility of digitoxin in supercritical CO2: Experimental study and modeling

In this communication, the solubility of digitoxin drug in supercritical CO2 was studied at different operating conditions (311 < T (K) < 343, 120 < P (bar) < 300). The results revealed digitoxin drug solubility (in mole fraction) was between 0.095 × 10−5 to 1.12 × 10−5. In the case of thermodynamic solubility modeling, cubic and non-cubic equation of states i.e. SAFT (statistical associating fluid theory), SRK (Soave-Redlich-Kwong) and sPC-SAFT (simplified perturbed chain SAFT) EoSs and six density-based correlations (Chrastil, Kumar-Johnston (KJ), Mendez-Santiago-Teja (MST), Garlapati and Madras (GM), Bartle et al. and Sung-Shim models) were considered. All used equations indicated reasonable behavior with appropriate accuracy for the solubility of the digitoxin drug. Meanwhile, sPC-SAFT EoS and Kumar-Johnston correlation with AARD% set to 8.96 % and 6.25 %, respectively exhibited greater accuracy in fitting the solubility data. Moreover, total, solvation and vaporization enthalpies of the digitoxin/supercritical carbon dioxide binary mixture were calculated based on KJ, Chrastil and Bartle et al. models.

CO2 solubility and absorption rate analysis of a mixed poly(oxymethylene) dimethyl ethers (PODE3–5) solution

Efficient and economical carbon capture is critical to counteract the diverse problems of global warming. In this work, the solubility of carbon dioxide (CO2) in different poly(oxymethylene) dimethyl ethers (PODE) solutions was experimentally investigated at temperatures from 278.15 to 308.15 K and pressures up to 1.2 MPa. The Henry's law constants of CO2 in the PODE system were determined and compared with other types of physical absorbents, which revealed PODE3–5 has great CO2 absorption ability in terms of molar and mass fraction. Meanwhile, the initial absorption rate of the physical absorption process of PODE3–5 was calculated and compared with commercially available absorbents using a gas absorption rate relationship. It was shown that the absorption rate of PODE3–5 in the CO2 absorption process is faster than that of other commercial absorbents. The CO2 solubility data of PODE3–5 were also correlated using the Jou-Mather model and the perturbed-chain statistical association fluid theory (PC-SAFT) equation of state model, and the recycling performance of the PODE3–5 absorbent was tested.

Investigating the properties of the water−vapor and water−graphite interfaces by PC-SAFT based density functional theory: A comparative study of different association functionals and PC-SAFT water parameter sets

In this work, we apply the perturbed-chain statistical associating fluid theory (PC-SAFT) based classical density functional theory to investigate the thermodynamics and structures of the water−vapor and water−graphite interfaces. For the water−vapor interface, we examine the surface tension as well as structural characteristics such as density profiles and hydrogen bonding distributions along the interface. For the water−graphite interface, we investigate these same structural features at a contact angle of 90° at 300 K. Specifically, we focus on comparing the results obtained from the three association functionals and six PC-SAFT water parameter sets from literature with experimental data and molecular simulation results. We find that the three association functionals exhibit qualitatively similar behavior in the calculation of surface tension, and it is more influenced by the parameter set rather than the association functional. The optimal functional or parameter set for the calculation of density profile of the vapor − liquid interface remains inconclusive, whereas preferable parameter sets and functionals have been identified for the water−graphite interface. Furthermore, the three functionals demonstrate a remarkably similar and qualitatively accurate depiction of the hydrogen bonding structures at both interfaces when compared with molecular simulation results. The level of quantitative accuracy, however, relies on whether the parameter set accurately reproduces the average number of hydrogen bonds of bulk water as observed in this particular set of molecular simulation results. The results of the present work offer valuable guidance for further investigation into the adsorption and wetting behavior of water on graphite-like surface, as well as the properties of water confined at the nanoscale.

Improving the estimation accuracy of confined vapor-liquid equilibria by fine-tuning the pure component parameter in the PC-SAFT equation of state.

We propose a thermodynamic model that combines the Young-Laplace equation and perturbed chain-statistical associating fluid theory (PC-SAFT) equation of state to estimate capillary condensation pressure in microporous and mesoporous sorbents. We adjust the PC-SAFT dispersion-energy parameter when the pore size becomes comparable to the molecular dimension. This modelling framework is applied to diverse systems containing associating and non-associating gases, various sorbents, and a wide range of temperatures. Our simulation results show that under extreme confinement, a higher value of the dispersion-energy parameter (ε) is required. Furthermore, using the experimental saturation pressure data for 18 different associating and non-associating confined fluids, we find that the shift in the PC-SAFT dispersion energy correlates with the ratio of the sorbent mean pore size to the PC-SAFT segment size (rp/σ). By fitting to the capillary condensation data, the relative deviation between the confined and bulk PC-SAFT dispersion energy parameter is only 0.1% at rp/σ = 15; however, this deviation starts to increase exponentially as rp/σ decreases. For a sorbent with large pores, when rp/σ > 15, the capillary condensation pressure results from our model are similar to the predictions from the Kelvin equation. Using a dataset containing 235 saturation pressure data points composed of 18 pure gases and 4 binary mixtures, the overall AARD% from our model is 12.26%, which verifies the good accuracy of our model. Because the mean sorbent pore radius (rp), the PC-SAFT energy parameter (ε), and segment size (σ) are known a priori, our model estimates the corrected energy parameter for small pores and, thus, extends its applicability.

Liquid to solid phase transition detection by using a vibrating tube densimeter along with densities up to 137 MPa of beef tallow fatty acid alkyl esters

Phase behavior and thermophysical properties of biodiesel at high pressure and high temperature are limited in the literature. These are useful to develop models and to understand their behavior having in mind the use of biodiesel in engines. Liquid to solid phase transitions, by using a vibrating tube densimeter, along with densities of three beef tallow fatty acid alkyl esters were studied in this work. Measurements of the oscillating period for each biofuel were carried out in a modular array constituted by two vibrating tube densimeters coupled in series and connected to a single loading cell. The oscillating period was converted to density by the forced path mechanical calibration (FPMC) method. Experimental liquid density sets for three beef tallow biodiesel samples based on fatty acid alkyl esters (FAAEs) are reported for the first time for pressures up to 137 MPa. These biofuels, named fatty acid methyl esters (FAMEs), fatty acid ethyl esters (FAEEs) and fatty acid butyl esters (FABEs), were measured in the temperature range of 286–393 K. The detection procedure for the beginning of the high-pressure solidification was focused on the beef tallow FABEs sample based upon its lower cloud point (CPFABEs = 281.15 K) in comparison with the reported property for the other esters (CPFAEEs = 289.15 K, CPFAMEs = 291 K) with the same feedstock; therefore, the conditions for the metastable liquid to solid phase transition associated to the effect of high pressure was detailed for waste beef tallow butyl ester biodiesel by performing step-by-step compressions in the interval of 286.20–298.13 K and with the help of the vibrating tube densimeters. FABEs had the lower density in contrast with FAEEs and FAMEs, this one being the denser biofuel. Modeling of liquid density data was performed by the perturbed-chain statistical associating fluid theory (PC-SAFT) Equation of State and the Tammann-Tait equation with maximum absolute average deviations of 0.15 % and 0.05 %, respectively. Both models were applied for correlating the thermodynamic derived properties of the fluid phase: isobaric thermal expansivity and isothermal compressibility.

Predicting PC‐SAFT parameters based on COSMO‐RS

AbstractTo predict the size (m, σ) and energy (ε) parameters of the perturbed‐chain statistical associating fluid theory (PC‐SAFT) based on the conductor‐like screening model for realistic solvents (COSMO‐RS), in this work, the PC‐SAFT model parameters of 304 substances were reviewed and summarized, their COSMO‐RS results linked to the size and energy were predicted, and the relationships between the PC‐SAFT parameters and COSMO‐RS results were obtained in 3 cases (Case 1: relationships based on n‐alkanes, Case 2: category‐specific relationships, Case 3: generic relationships for 138 substances). Case 2 (including Case 1) shows the lowest average absolute relative deviations (AARDs) of 7.63% (m), 3.05% (σ), and 9.05% (ε), while Case 3 provides the prediction capacity with AARDs of 10.00% (m), 4.05% (σ), and 13.21% (ε), which is better than those developed by others. Finally, the new PC‐SAFT parameters were used to predict the densities and vapor pressures of 8 representative substances and compared with the results using the original PC‐SAFT parameters, showing that the parameters in Case 3 can be used to reproduce densities and the parameters in Case 2 (including Case 1) can be used to reproduce both densities and vapor pressures.

Influence of polymers on oxaprozin dissolution kinetics and mechanisms

In this work, the influences of polymers (HPMC E3, PEG 6000, PVP K25, PVP K30), temperature, stirring speed and polymer mass fraction on the oxaprozin (OXA) dissolution profiles were measured by a United States Pharmacopeia (USP) Ⅱ dissolution apparatus. The two-step chemical potential gradient model combined with the interfacial steady-state mass transfer model as well as PC-SAFT (perturbed-chain statistical associating fluid theory) were used to analyze the dissolution mechanism of OXA under different conditions. The presence of polymer could promote the surface reaction of OXA while temperature and stirring speed have different influences on the surface reaction and diffusion. The diffusion boundary layer thickness δ of OXA tablets increases with the increase of temperature and decreases with the increase of stirring speed. Based on the obtained surface reaction rate constant ks and diffusion rate constant kd, the dissolution profiles with high accuracy compared with the experimental data.

The step-wise dissolution method: An efficient DSC-based protocol for verification of predicted API–polymer compatibility

The development of an amorphous solid dispersion (ASD) is a promising strategy for improving the low bioavailability of many poorly water-soluble active pharmaceutical ingredients (APIs). The construction of a temperature–composition (T–C) phase diagram for an API–polymer combination is imperative as it can provide critical information that is essential for formulating stable ASDs. However, the currently followed differential scanning calorimetry (DSC)-based strategies for API solubility determination in a polymer at elevated temperatures are inefficient and, on occasions, unreliable, which may lead to an inaccurate prediction at lower temperatures of interest (i.e., T = 25 °C). Recently, we proposed a novel DSC-based protocol called the “step-wise dissolution” (S-WD) method, which is both cost- and time-effective. The objective of this study was to test the applicability of the S-WD method regarding expeditious verification of the purely-predicted API–polymer compatibility via the perturbed chain-statistical associating fluid theory (PC-SAFT) equation of state (EOS). Fifteen API–polymer T–C phase diagrams were reliably constructed, with three distinct API–polymer case types being identified regarding the approach used for the S-WD method. Overall, the PC-SAFT EOS provided satisfactory qualitative descriptions of the API–polymer compatibility, but not necessarily accurate quantitative predictions of the API solubility in the polymer at T = 25 °C. The S-WD method was subsequently modified and an optimal protocol was proposed, which can significantly reduce the required experimental effort.

Critical points calculation of CO2-based binary mixture working fluids: evaluation of PC-SAFT equation of state

Critical point is basic and important thermophysical property of CO2 mixtures, which determines the parameter design of power cycle and the optimization of its operating conditions. In this work, the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state is used to calculate the critical point of CO2 mixture working fluids of the power cycle. To tackle the challenge of the original PC-SAFT in quantitatively representing of critical point of pure substance, the deviation between calculation results and experimental data was reduced by using the refitted pure-component parameters, so as to realize the effective increase of accuracy and representation the critical loci of the CO2 mixtures. By comparing with the classical cubic equation of state (Peng-Robinson and Soave-Redlich-Kwong), the results of PC-SAFT are effectively improved with relative deviation close to that of the cubic equation of state. The results show that the refitting of pure-component parameters can effectively help the accurate calculation of the critical point of CO2 mixtures, especially for the mixture containing hydrofluoroolefins with more complex molecular structure. This work provides an important reference for predicting the critical point of other potential CO2 mixtures.

Machine learning with active pharmaceutical ingredient/polymer interaction mechanism: Prediction for complex phase behaviors of pharmaceuticals and formulations

The high throughput prediction of the thermodynamic phase behavior of active pharmaceutical ingredients (APIs) with pharmaceutically relevant excipients remains a major scientific challenge in the screening of pharmaceutical formulations. In this work, a developed machine learning model efficiently predicts the solubility of APIs in polymers by learning the phase equilibrium principle and using a few molecular descriptors. Under the few-shot learning framework, thermodynamic theory (Perturbed-Chain Statistical Associating Fluid Theory, PC-SAFT) was employed for data augmentation, and computational chemistry was applied for molecular descriptors screening. The results showed that the developed machine learning model can predict the API-polymer phase diagram accurately, broaden the solubility data of APIs in polymers, and reproduce the relationship between API solubility and the interaction mechanisms between API and polymer successfully, which provided efficient guidance for the development of pharmaceutical formulations.

Leveraging liquid-liquid phase separation and volume modulation to regulate the enzymatic activity of formate dehydrogenase

Engineering of reaction media is an exciting alternative for modulating kinetic properties of biocatalytic reactions. We addressed the combined effect of an aqueous two-phase system (ATPS) and high hydrostatic pressure on the kinetics of the Candida boidinii formate dehydrogenase-catalyzed oxidation of formate to CO2. Pressurization was found to lead to an increase of the binding affinity (decrease of KM, respectively) and a decrease of the turnover number, kcat. The experimental approach was supported using thermodynamic modeling with the electrolyte Perturbed-Chain Statistical Associating Fluid Theory (ePC-SAFT) equation of state to predict the liquid-liquid phase separation and the molecular crowding effect of the ATPS on the kinetic properties. The ePC-SAFT was able to quantitatively predict the KM-values of the substrate in both phases at 1 bar as well as up to a pressure of 1000 bar. The framework presented enables significant advances in bioprocess engineering, including the design of processes with significantly fewer experiments and trial-and-error approaches.

P[formula omitted]T measurements of Glycols (Mono-, Di- and Triethylene glycol) up to 423.15 K and 140.0 MPa and their aqueous solutions at atmospheric pressure

The density of three glycols, namely Monoethylene glycol (MEG), Diethylene glycol (DEG), and Triethylene glycol (TEG) was measured in the temperature range from 298.15 K to 423.15 K and pressures up to 140.0 MPa using a vibrating tube density meter Anton Paar DMA-HPM, coupled with a high-pressure mPDS 5 unit. The modified Tait-Tammann equation was used to correlate the experimental density, which gave an absolute average relative deviation (AARD) of less than 0.2 %. Derived properties such as isobaric thermal expansion and isothermal compressibility coefficients were estimated and discussed. Furthermore, the density of the binary systems composed by the aforementioned glycols (1) + water (2) was also measured in the (273.15, 373.15) K temperature range at atmospheric pressure. The Cubic-Plus-Association (CPA) and the simplified version of the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) equations of state were used to correlate the newly measured data, with deviations less than 3.7 % for pure component and 12.0 % for the binary systems.