International Journal of Thermophysics最新文献

The current research examines the thermophysical behavior of systems involving propyl methanoate (PM) and a homologous series of 1-alkanol from 1-hexanol to 1-decanol within the temperature interval 293.15–323.15 K. The primary objective was to elucidate the intermolecular forces and the extent of non-ideality in these systems. The results demonstrate that across all binary systems, the excess molar volume maintained positive values over the entire concentration range. Moreover, these positive deviations in volume become more pronounced with both increasing temperature and elongation of the alcohol’s carbon chain. A consistent negative trend in viscosity deviations was observed for every system, with the deviation magnitude rising as the carbon chain extended. To interpret the volumetric behavior more comprehensively, the PC-SAFT model was employed to model liquid densities. The calculated densities exhibited excellent agreement with the corresponding experimental values across the studied mixtures. Among all investigated mixtures, the propyl methanoate with 1-decanol pair showed the maximum density deviation of 0.81% between experiment and model. The close match between calculated and experimental data attests to the strength of the PC-SAFT formulation in modeling non-ideal interactions in binary mixtures.

This study evaluates the performance of three reference equations of state (EoS), AGA8-DC92, GERG-2008, and SGERG-88, in predicting the density of regasified liquefied natural gas (RLNG) mixtures. A synthetic nine-component RLNG mixture was gravimetrically prepared. High-precision density measurements were obtained using a single-sinker magnetic suspension densimeter over a temperature range of (250 to 350) K and pressures up to 20 MPa. The experimental data were compared with EoS predictions to evaluate their accuracy. AGA8-DC92 and GERG-2008 showed excellent agreement with the experimental data, with deviations within their stated uncertainty. In contrast, SGERG-88 exhibited significantly larger deviations for this RLNG mixture, particularly at low temperatures of (250 to 260) K, where discrepancies reached up to 3 %. Even at 300 K, deviations larger than 0.4 % were observed at high pressures, within the model’s uncertainty, but notably higher than those of the other two EoSs. The analysis was extended to three conventional 11-component natural gas mixtures (labeled G420 NG, G431 NG, and G432 NG), previously studied by our group using the same methodology. While SGERG-88 showed reduced accuracy for the RLNG mixture, it performed reasonably well for these three mixtures, despite two of them have a very similar composition to the RLNG. This discrepancy is attributed to the lower CO₂ and N₂ content typical in RLNG mixtures, demonstrating the sensitivity of EoS performance to minor differences in composition. These findings highlight the importance of selecting appropriate EoS models for accurate density prediction in RLNG applications.

The present work introduces a modification to the expanded fluid-based viscosity correlation (originally proposed by Yarranton and Satyro in 2009 for hydrocarbons) in order to obtain improved representations of the dynamic viscosity of several representative modern ionic fluids: pure ionic liquids (ILs) and deep eutectic solvents (DESs). The strong non-linearity introduced by the two-nested exponential form in the original Yarranton–Satyro correlation has been presently simplified by expressing the argument of the outer exponential as a linear combination of inverse powers of the reduced temperature and a logarithmic term involving the compressed state density in a vacuum ρ_s⁰, the fluid density ρ, and the pressure. The resulting modified Yarranton–Satyro (MYS) correlation thus contains two key thermodynamic potentials (ρ_s⁰ and ρ) which in turn were estimated via the use of two simple cubic equations of state of the van der Waals type: Soave–Redlich–Kwong or Peng–Robinson. The present MYS approach was successfully verified during the correlation and prediction of experimental dynamic viscosities of 3 families of imidazolium-based ILs ([C_Xmim][BF₄], [C_Xmim][PF₆], and [C_Xmim][Tf₂N]), one pyridinium-based IL ([b3mpy][BF₄]), one pyrrolidinium-based IL ([P14][Tf₂N]), one ammonium-based IL ([N1114][Tf₂N]), and four ILs having non-fluorinated anions ([dmim][MeSO₄], [bmim][EtSO₄], [bmim][Ac], and [b3mpy][dca]) over a temperature range varying from 273.15 K to 438.15 K and at pressures from 1 to 3000 bar. We also considered three archetypal choline chloride-based DESs for model validation: Reline, Ethaline, and Glyceline within a temperature range varying from 293.15 K to 373.15 K and at pressures from 1 to 1000 bar.

Thin coatings have emerged as a critical component of advanced nuclear fuels. Located in the path of heat dissipation, a thorough investigation of coating thermal conductivity is imperative. The spatial-domain thermoreflectance (SDTR) technique is ideally suited for characterizing their thermal conductivity due to its high spatial resolution. However, applying SDTR to cross-sectional samples is complicated by their asymmetric geometry and layered structure, which preclude analytical heat transfer solutions and introduce significant uncertainty in the data analysis. Here, we employ finite element modeling, validated by experiments, to quantify the size effects that govern SDTR measurements on cross-sectional coating samples. We determine the minimal coating dimensions required for accurate, artifact-free measurement and reveal how these dimensions are influenced by the thermal property mismatch between the coating, substrate, and transducer film. We further quantify the measurement error induced by off-center laser positioning. Through systematic investigation of progressively complex scenarios, analytical expressions for rapid determination of minimum dimensions free from boundary artifacts are derived. Our framework establishes practical guidelines for accurate thermal characterization of coatings by SDTR for energy materials research.

Novel nano-enhanced phase change materials (NEPCMs) for vaccine storage applications have been developed for vaccine transportation. Phase change materials (PCMs) are highly regarded due to their excellent heat storage capacities and their ability to operate within a limited temperature range. Nonetheless, their low thermal conductivity restricts their applicability. A binary mixture of caprylic acid (CL) and capric acid (CA) with a weight fraction of 58:42 was developed for the passive cooling application. The CL–CA binary mixture exhibits a melting enthalpy (H_m) of 119.07 Jg⁻¹ and a melting temperature (T_m) of 7.66 °C. Boron nitride (BN) was used as a thermal conductivity enhancer for the above binary mixture. BN was added in various weight percentages of 0.5 %, 1 %, 1.5 %, and 2 % in the binary mixture to develop NEPCMs. There was an improvement of 12.1 % in thermal conductivity for 2 % BN from the base binary mixture. Furthermore, thermal cycling has been done and the samples have maintained stability and phase change characteristics as confirmed using FTIR (Fourier transform infrared spectroscopy), thermal conductivity, and DSC (differential scanning calorimetry).

Carbon dioxide (CO₂), as a natural working fluid, is blended with hydrofluorocarbons (HFCs) or hydrofluoroolefins (HFOs) that exhibit favorable thermodynamic properties. By modifying the mixture composition, the performance of the refrigeration system can be optimized in terms of efficiency and operational conditions. However, comprehensively evaluating the thermodynamic properties of CO₂-based mixtures through experimental measurements alone remains challenging due to the complexity, expense, and time involved. This highlights the critical necessity for advanced computational methods to enhance and extend experimental research. In this study, molecular dynamics (MD) simulations were employed to comprehensively investigate the vapor–liquid phase behaviors and surface tension properties of CO₂, R32, and R134a in their pure, binary, and ternary components, respectively. The MD results show good agreement with our previous Gibbs Ensemble Monte Carlo (GEMC) simulations and the experiment-derived correlations from REFPROP program, demonstrating the precision and dependability of the employed force field and molecular methodology. These findings validate that molecular simulation, when coupled with a well-parameterized potential energy function, can effectively characterize essential thermophysical properties and fill data gaps where experimental measurements are limited. The methodology provides a solid foundation for subsequent research on refrigerant mixture behavior and offers valuable insights for the optimization and design of thermal cycle systems.

By the measurement of frequency and damping time of surface oscillations, excited by a short pulse on a freely floating liquid droplet, the surface tension and viscosity of the liquid can under certain conditions contactlessly be determined. The conventional physical models connecting these material properties with the corresponding measurement quantities are the well-known Rayleigh and Lamb formula. However, the use of these formulas in oscillating drop experiments does not always deliver physically reasonable results especially in the case of thin fluid liquids. Among others, this is due to the fact that both equations result from calculations of the fluid flow inside the oscillating liquid droplet which are based on the simplified linearized Navier–Stokes equation neglecting its substantially appertaining nonlinear convective term. In the following, the theoretical basis of the Rayleigh and Lamb formulae is investigated in more detail. Furthermore, criteria are derived to provide limits for the reasonable application of these equations.

Clathrate-hydrate-based tritium separation from isotope water is a promising process for removing tritium that is not effectively separated by conventional methods. Clathrate hydrates (hereafter hydrates) are crystalline compounds composed of water and guest molecules. Hydrate-based tritium separation utilizes the property that heavy water (D₂O) forms hydrates under milder temperatures than light water (H₂O). Efficient industrial operation requires a guest compound that forms hydrates at high temperatures and low pressures and has a large difference in phase equilibrium temperature between H₂O and D₂O hydrates (ΔT_DH). In this study, we measured the phase equilibrium conditions of D₂O hydrates formed with HFC-134a, HFC-32, and HFC-23. The formation of D₂O hydrates with these guests can be a route to tritium separation through co-precipitation of T₂O. HFC-134a formed hydrates under the mildest conditions, with ΔT_DH values of 2.8 K, 1.8 K, and 2.4 K for HFC-134a, HFC-32, and HFC-23. In addition to the three investigated guests, the potentials of propane, cyclopentane, and cyclopentane + CO₂ hydrate systems for hydrogen isotope separations were also compared, suggesting that HFC-134a and cyclopentane may be suitable guests for tritium separation. Present and previous studies have also shown a strong positive correlation between the hydration number and ΔT_DH (correlation coefficient = 0.76). This trend may be ascribed to the fact that a higher proportion of water molecules in the hydrate amplifies the effect of replacing H₂O with D₂O. These results indicate that the equilibrium conditions of D₂O hydrates may be approximately predicted to identify suitable guests for tritium separation.

This article main aim is to propose new heat transfer fluids having polyethylene glycol mixtures or PEG 200 as a base fluid. Polyethylene glycols were lately studied as possible heat transfer fluids and several encouraging results were highlighted in the open literature. One of the main concerns is related to their relatively low thermal conductivity (i.e., around 0.2 W·m⁻¹·K⁻¹) and this study aims to give a good referential in terms of thermal conductivity and effusivity at experimental level on a number of polyethylene glycol mixtures enhanced with two kinds of nanoparticles: MWCNT and MgO. The experiment was performed on 28 samples with different concentrations of nanoparticles and the results showed an increase in thermal conductivity when nanoparticles are added, upsurge that is correlated with the nanoparticle type, concentration, as well as the base fluid type. Nevertheless, the host fluid properties influence was found to be relevant when small fractions of nanoparticles are employed, regardless of the nanoparticle type. Both the thermal conductivity and effusivity augmentation were noticed to linearly depend with nanoparticle loading, while the temperature influence was a second-degree polynomial one.

For long-term sustainability, governments and industries worldwide are actively implementing innovative strategies to meet the growing energy demands across the globe simultaneously mitigating environmental impact. Effective energy storage offers a viable solution for supporting renewable resources and addressing the rising energy needs. The thermal storage capabilities of phase change materials (PCMs) for temperature regulation have garnered considerable attention from researchers. Yet, the practical use of PCMs is hindered by their poor thermal conductivity and leakage issue. Addressing this limitation through innovative enhancement methods can substantially improve heat transfer rates and overall system performance. This review article begins with a comprehensive examination and effect of the thermophysical properties of various PCMs. The different methods of heat transfer enhancement techniques of PCMs are explored broadly highlighting the importance of nano-enhanced PCMs (NePCMs) and shape-stabilized PCMs. This review aims to explore the current state of research and discuss future trends by offering readers valuable insights into Artificial Intelligence regarding the fundamental aspects of PCM heat transfer and applications. Finally, enhancing the properties of PCMs has a direct influence on temperature regulation and energy storage, thus promoting sustainable energy use. This review thoughtfully integrates both foundational concepts and practical applications, making it an excellent starting point for newcomers while also providing seasoned experts with a current and critical overview of the field.