International Journal of Thermophysics最新文献

The experimental data of densities, ρ, speeds of sound, u, and refractive indices, n_D, are reported for pure compounds and their two binary mixtures of acetonitrile + aromatic hydrocarbons, namely: acetonitrile + n-propylbenzene and acetonitrile + iso-propyllbenzene, at five temperatures, in the range of T = (298.15 to 318.15) K with ΔT = 5 K, on the entire composition range and under atmospheric pressure, p = 0.1 MPa. The values obtained from experimental measurements have been correlated by the Jouyban-Acree model with good accuracy. Based on the experimental data, the excess and deviation quantities, as: excess molar volumes, (V_{m}^{E}), partial/ apparent molar volumes, deviation in speeds of sound, Δu, excess isentropic compressibilities, ({kappa_{S}^{E} }), excess molar isentropic compressibilities, (K_{S,m}^{E}), refractive index deviations, Δn_D, and excess molar refractions, ({R_{m}^{E} }), respectively, have been calculated. For each of the studied mixtures, all these excess properties have been correlated with the Redlich–Kister polynomial equation and the coefficients of correlations were reported. In addition, in this paper, the Perturbed Chain Statistical Associating Fluid Theory Equation of State (PC-SAFT EoS) was used for modeling the density as predictive approach. On the other hand, PC-SAFT + two models were used for calculate the speed of sound of binary mixtures, and PC-SAFT + four mixing rules were used for compute the refractive index of binary mixtures.

This investigation examined the density and viscosity of five binary mixtures of propyl butyrate with 1-alkanols (C₅–C₁₀). The properties were measured across the complete composition range at temperatures from 293.15 to 323.15 K. Experimental analysis showed positive excess molar volumes, and the magnitude of these values increased with both temperature and the chain length of the 1-alkanol. These results are consistent with volume expansion upon mixing for the systems studied. A Physics-Informed Neural Network (PINN) was also developed to predict the excess molar volumes. This model, which incorporates thermodynamic constraints, was applied to the mixtures. For the datasets in this study, the model yielded an Average Absolute Deviation (AAD) of 0.0053 cm³/mol and a mean relative error of 3.23 %. Furthermore, R² values for the model’s predictions exceeded 0.99 for all tested systems. This indicates a strong correlation between the predicted and experimental data under these specific conditions, particularly for the longer-chain alkanols and at higher temperatures.

The high-temperature sensitivity of the mechanical properties of composite ice and pure ice materials makes thermal risk prediction and careful thermal management essential for ensuring the stability and durability of composite ice shell buildings. Based on previous studies on the radiation spectra of composite ice and pure ice, this study established two dynamic solar radiation and heat transfer models for composite ice and pure ice structures. Compared with temperature data from previous field tests, the average root mean square errors for the composite ice structure model and pure ice structure model were 0.86 °C and 0.91 °C, with mean absolute errors of 0.74 °C and 0.79 °C, respectively. In addition, the degree of influence of four meteorological parameters on the surface temperature of both ice structures was investigated, covering indoor and outdoor air temperatures, outdoor wind speed, and solar irradiance. The application of the two models was further extended through response surface methodology experiments to investigate the variations in the surface temperature and thermal risk of ice structures under the simultaneous effects of meteorological parameters with significant impacts, the addition ratio of reinforcing materials, and the structural thickness. Multivariate regression prediction models for the surface temperatures of ice structures were subsequently established. The results provide a method for simulating the dynamic solar radiation and heat transfer in spectrally selective ice structures in real time, as well as directly predicting the thermal risk, thus providing important references for the future operation and maintenance of composite ice shell buildings.

γ-Butyrolactone (GBL) and 1,4-butanediol (BDO) represent a promising liquid organic hydrogen carrier (LOHC) system, for which a lack of thermophysical property data at process-relevant conditions exists. For this LOHC system, the Fick diffusivity D₁₁, thermal diffusivity a, thermal conductivity λ, and density ρ were investigated at about 0.1 MPa as a function of temperature T and mixture composition at GBL amount fractions x_GBL = (0.00, 0.25, 0.50, 0.75, and 1.00) using light scattering and conventional techniques. Vibrating U-tube densimetry and a guarded parallel-plate instrument were employed to determine ρ between T = (283 and 473) K and λ between T = (283 and 363) K. Dynamic light scattering allowed simultaneous access to a and D₁₁ between T = (298 and 473) K in macroscopic thermodynamic equilibrium, while polarization-difference Raman spectroscopy was applied after calibration to monitor the composition. The onset of a certain decomposition or structural rearrangement was observed above about T = 398 K, depending on the sample composition and experimental boundary conditions. When such effects are small, the data for ρ, a, and D₁₁ increase with increasing x_GBL at a given T, whereas λ has the opposite trend. With the help of the results for ρ, a, and λ, values for the specific isobaric heat capacity c_p could be derived. The present measurement results agree with the few experimental data for ρ and λ available in the literature for the pure mixture components and contribute to a significant extension of the thermophysical property database for this highly promising LOHC system.

This study evaluates the energy performance, operational carbon emissions, and energy autonomy of electrified residential buildings compared to a conventional gas-based Zero-Energy Building (ZEB) under Korea’s ZEB certification framework. A detached single-family house was modeled with three configurations: a gas-based ZEB, a Packaged-Terminal Heat Pump (PTHP) ZEB, and an Air-to-Water Heat Pump (AWHP) ZEB. A 3-kW rooftop photovoltaic (PV) system was applied to all cases, representing a typical residential-scale installation for energy self-sufficiency. The results show that full electrification increases primary energy consumption—from 148.3 to 201.6 kWh/m²·yr—under the current source energy conversion factor (2.75 for electricity), making it difficult for electrified ZEBs to satisfy the present 90 kWh/m²·yr threshold. Although the electricity emission factor (EF) of the Korean grid is projected to decline significantly from 0.4781 to 0.0480 kgCO₂eq/MWh by 2050, this reduction reflects grid decarbonization, not changes in building performance. When building operational emissions are recalculated using the future EF values, electrified ZEBs show substantially lower annual emissions than the gas-based case, highlighting the long-term benefits of electrification under a decarbonized power system. PV-based energy autonomy analysis reveals that the load cover ratio (LCR) and self-consumption ratio (SC) remain within 38–67%, while the self-sufficiency ratio (SS) exceeds the 20% threshold required for ZEB certification. Nevertheless, the high loss of power supply probability (63–78%) underscores the necessity of storage or load-shifting strategies. Overall, electrification represents a viable transition pathway toward carbon–neutral ZEBs, contingent upon continued grid decarbonization and expanded renewable integration.

Passive radiative cooling performance is influenced by material properties and meteorological conditions. A more transparent atmospheric window reduces downwelling longwave radiation, thereby increasing cooling power and reducing surface temperature. Atmospheric emissions can be quantified using sky emissivity or sky temperature, both of which can be parameterized by ambient temperature, humidity, and cloudiness. This study first reviews the historical development of clear-sky and cloudy-sky temperature models, highlighting the challenges in establishing a universal sky temperature model. It then examines state-of-the-art meteorological remote sensing technologies and assesses their roles in monitoring and acquiring radiative cooling data. As radiative cooling materials and systems hold strong potential for building energy conservation and their effectiveness is highly weather-dependent, this study investigates how radiative cooling informatics enhances quantitative building energy simulations, assessments, and management.

We numerically and experimentally investigate the impact of photogenerated minority excess carriers on the plasma–elastic and total photoacoustic response of semiconductors. The frequency domain behavior of photoacoustic signals is examined as a function of the surface conditions, optical absorbance, and material thickness. For a visible-light excitation, distinct peak-like features in the plasma–elastic amplitude emerge at high modulation frequencies and for thin enough samples. These trends are attributed to carrier density asymmetries between the illuminated and non-illuminated surfaces. These findings highlight the key role of carrier dynamics in shaping plasma–elastic coupling to optimize and interpret photoacoustic measurements in semiconductor characterization.

Molten salts play a crucial role in numerous industrial applications, including nuclear reactors, thermal energy storage, and high-temperature electrochemical processes. Their thermophysical properties, such as viscosity, surface tension, and molar volume, are essential for optimizing performance and ensuring operational safety, as they govern heat transfer, fluid flow, and interfacial behavior in high-temperature environments. The TCSALT Molten Salts Database (Version 2.0) provides critically assessed thermodynamic and thermophysical data for fluoride- and chloride-based salts with oxide additions: AlCl₃–AlF₃–Al₂O₃–CaCl₂–CaF₂–CaO–KCl–KF–K₂O–LiCl–LiF–Li₂O–MgCl₂–MgF₂–MgO–NaCl–NaF–Na₂O–SiCl₄–SiF₄–SiO₂–SrCl₂–SrF₂–SrO–ZnCl₂–ZnF₂–ZnO. The database employs the Ionic Two-Sublattice Liquid Model to describe the molten salt solutions, enabling accurate predictions of multicomponent phase diagrams together with both thermodynamic and thermophysical properties. Using this database, viscosity and surface tension can be directly predicted from the underlying ionic structure description of the melt, offering quantitative insights into species distribution, connectivity, and structural evolution across a wide range of temperatures and compositions. The database also includes molar volume descriptions for both liquid and solid phases, further enhancing its applicability in high-temperature material processing and engineering applications. The integration of these thermophysical properties within a unified computational thermodynamic framework provides a powerful tool for material design and process optimization.

New experimental data for squalane, including liquid densities, liquid heat capacities, and saturated vapor pressures, are presented together with their respective uncertainties. Liquid densities were determined from 293.15 K to 453.15 K at pressures up to 20 MPa using an accurate single-sinker magnetic suspension densimeter. Auxiliary measurements were performed with a vibrating tube densimeter from 273.15 K to 363.15 K at ambient pressure, including the correction for sample viscosity. Heat capacities were measured using two differential scanning calorimeters, covering a temperature range from 260 K to 518.6 K. Vapor pressures in the range from 0.21 Pa to 49 Pa were acquired by the static method, spanning a temperature interval from 388 K to 462 K. Correlations for density and heat capacity of liquid squalane developed within this work are discussed and compared to the literature data. A correlation for saturated vapor pressure in the form of the Wagner equation, covering a wide temperature range, was obtained by simultaneously correlating vapor pressures and the relevant caloric data. The choice of exponents used in the Wagner equation is discussed.

Given the high cost and time demands associated with experimental thermodynamic measurements, the development of reliable, theory-based equations of state (EOSs) is crucial for the accurate prediction of refrigerant behavior in practical thermal systems. Such predictive capabilities are essential for optimizing the design, efficiency, and energy performance of refrigeration and heat pump technologies. In this study, a novel two-parameter cubic EOS was developed within a simplified statistical mechanical perturbation theory framework. The temperature-dependent parameters of the proposed model were optimized using saturated property data for 35 refrigerants, covering a wide range of industrially relevant compounds including chlorofluorocarbons, hydrochlorofluorocarbons, hydrofluorocarbons, hydrocarbons, and natural inorganic refrigerants. Comparative evaluations were conducted for vapor–liquid equilibrium (VLE), saturated and high-pressure liquid densities, normal boiling points, enthalpies of vaporization, pressure–enthalpy (P–H) diagrams, pressure–pressure (P–S) diagrams, isochoric specific heat capacities (C_v), isobaric specific heat capacities (C_p), speed of sound (u), and the coefficient of performance for selected refrigerants, employing the proposed EOS alongside other widely adopted two-parameter models. Furthermore, the new EOS was applied to mixture systems, including isothermal VLE calculations for azeotropic and non-azeotropic binary mixtures, liquid density predictions, thereby demonstrating its versatility and applicability to chemical and process engineering refrigerant systems. The results of the comparative analyses consistently highlight the superior predictive performance of the proposed simple cubic EOS relative to commonly used existing models.