International Journal of Thermophysics最新文献

Experimental densities (ρ) and sound speeds (u) have been reported for the first time for the ternary system (propan-1-ol + cyclohexane + benzene) at six temperatures, T = (293.15, 298.15, 303.15, 313.15, 323.15, and 333.15) K, and at atmospheric pressure, covering the full composition range. The corresponding binary subsystems were also studied systematically. From these data, excess molar volumes (({V}_{m}^{E})​) and excess isentropic compressibilities (({kappa }_{S}^{E})​) were derived and correlated using the Redlich-Kister and Cibulka equations for binary and ternary systems, respectively. The composition and temperature dependence of the excess properties provided insight into molecular interactions and structural effects within the mixtures. Densities were modeled with the Perturbed-Chain Statistical Associating Fluid Theory equation of state, while sound speeds were estimated using Schaaff’s Collision Factor Theory and Nomoto’s relation. In addition, the Jouyban-Acree model was applied to represent the composition and temperature dependence of densities and sound speeds, and their related properties, namely thermal expansivities ({alpha }_{p}) and isentropic compressibilities ({kappa }_{S}) of both binary and ternary mixtures. Ternary excess properties were further compared with values predicted by symmetric (Kohler, Muggianu) and asymmetric (Hillert, Toop) geometric models. The performance of all theoretical and empirical approaches was assessed by statistical indicators, demonstrating their respective strengths and limitations in describing the thermophysical behavior of these complex mixtures.

Molten salt eutectic FLiNaK containing lanthanide fluorides (LnF₃) is widely used in various industrial applications and research projects, so knowledge of the physicochemical properties of such complex ionic melts is crucial. The dynamic viscosity of the FLiNaK-LnF₃ (Ln = La, Ce, Nd) molten salt mixtures with content of LnF₃ 3, 7 and 15 mol% was studied by rotational viscometry using rheometer FRS 1600 (Anton Paar). Viscosity measurements were carried out in the temperature range from 1023 K to a temperature close to the liquidus of each composition. The viscosity of the FLiNaK-LnF₃ melts increases significantly both with decreasing temperature and with increasing LnF₃ content. The viscosity values of molten mixtures with the same content of LaF₃, NdF₃ or CeF₃ do not differ insignificantly. However, a tendency for a more substantial decrease in viscosity is observed when introducing the LnF₃ additives in the sequence CeF₃ > NdF₃ > LaF₃. This tendency is violated for the dependence of viscosity on the superheating temperature (20, 100, 200 degrees above the liquidus): the viscosity of molten mixtures with any lanthanide fluoride in an amount greater than 7 mol% does not change. For the FLiNaK-NdF₃ melts, the dependence of the fluidity on the molar volume was determined using the available data on the density of these melts. The fluidity of the FLiNaK-NdF3 decreases with increasing NdF₃ concentration. However, when comparing the fluidity values versus the relative molar volume, it turns out that it stops changing in melts with an NdF₃ content of more than 7 mol%. Such a change in the viscosity and fluidity of FLiNaK-LnF₃ melts is explained by their complex ionic structure.

This study presents an integrated assessment of traditional bioresource construction materials used by indigenous communities in the Nilgiris district, Tamil Nadu, focusing on their thermophysical properties, environmental benefits, and cultural relevance within the region’s unique subtropical highland climate. Samples were collected from tribal settlements of the Toda, Kattunayakans, Kurumba, Kota, and Irula communities, spanning altitudes from 900 m to 2636 m, where temperatures range between 0 °C and 25 °C. Key materials studied include bamboo, wood species (teak, eucalyptus, silver oak, white Naga tree), grass, calcareous binder, and bark skin. Thermal characterization using differential scanning calorimetry revealed specific heat (Cp) capacities ranging from 2.224 kJ∙(kg⁻¹∙K⁻¹) (Toda bamboo) to 2.435 kJ∙(kg⁻¹∙K⁻¹) (Kurumba bamboo), with roofing grass thatch exhibiting a notably high Cp of 4.543 kJ∙(kg⁻¹∙K⁻¹) and calcareous binder reaching 4.703 kJ∙(kg⁻¹∙K⁻¹). Thermal conductivity values for bamboo were found between 0.17 W∙(m⁻¹∙K⁻¹) and 0.23 W∙(m⁻¹∙K⁻¹), yielding thermal resistance (R-values) of approximately 2.86 (m²∙K)∙W⁻¹ to 5.00 (m²∙K)∙W⁻¹ per meter thickness, significantly outperforming conventional concrete (R ≈ 0.71 (m²∙K)∙W⁻¹). Straw and reed materials demonstrated exceptionally high R-values up to 15.38 (m²∙K)∙W⁻¹ and 30.13 (m²∙K)∙W⁻¹, respectively, confirming their superior insulation capabilities. Environmental analysis highlighted bamboo’s rapid growth rate (30 cm∙day⁻¹ to 100 cm∙day⁻¹), low embodied energy (30 % to 40 % less than concrete), and carbon sequestration potential (up to 17 tons CO₂/ha/year). These bio-based materials offer thermal comfort enhancements of 4 °C to 6 °C above ambient in cold conditions and contribute to reducing construction-related carbon emissions by nearly 50 %.

Artificial intelligence plays a significant role in demonstrating nanofluidic systems through analysis of the large datasets for data-driven insights, improving prediction accuracy through iterative learning, aiding in design optimization, and the development of nanofluidic devices with superior thermal radiation heat transfer characteristics. This study investigates heat transport in the flow of unsteady squeezing nanofluidic model with stretchable rotating and oscillating disks mixed with kerosine oil as a base fluid by using artificial intelligence-based knacks through nonlinear autoregressive networks with Levenberg–Marquardt backpropagation. The partial differential equations are converted into ordinary types by changing multi class parameters, i.e., stretching, squeezing, and rotation, with fixed numbers, i.e., Hartmann, Eckert and Prandtl. The synthetic dataset is generated with Adams numerical method for unsteady squeezing flow and heat transport of Silicon oxide nanofluidic model and further this information is utilized for the execution of nonlinear exogenous networks for solving the unsteady squeezing nanofluidic model. The results are consistently aligned with numerical solutions for the system, demonstrating a substantially reduced error magnitude across several anticipated scenarios. The effectiveness of the proposed methodology is demonstrated through iterative convergence on mean square error, adaptive controlling metric of optimization with Levenberg–Marquardt algorithm, statistical distribution of error in histogram plots, and autocorrelation analysis on exhaustive numerical experimentation of the nanofluidic model.

The volumetric, optical, and acoustical properties of binary and ternary solutions of (3-amino-1-propanol + N,N-dimethylacetamide), (3-amino-1-propanol + cyclohexanone), (N,N-dimethylacetamide + cyclohexanone), and (3-amino-1-propanol + N,N-dimethylacetamide + cyclohexanone) were investigated in this study. Density (ρ), speed of sound (u), and refractive index (({n}_{text{D}})) were measured across the entire composition range at 298.15, 303.15, 308.15, 313.15, 318.15, and 323.15 K at ambient pressure (81.5 kPa). Excess molar volume({V}_{text{m}}^{text{E}}), excess partial molar volume ({overline{V} }_{i}^{E}), deviations in isentropic compressibility({Delta k}_{text{s}}), or refractive index ({Delta n}_{text{D}},) were also calculated. Binary mixtures of 3-amino-1-propanol + N,N-dimethylacetamide and N,N-dimethylacetamide + cyclohexanone showed positive ({V}_{text{m}}^{text{E}}) and ({Delta k}_{text{s}}) values, while 3-amino-1-propanol + cyclohexanone exhibited negative values. ({Delta n}_{text{D}}) values were negative for 3-amino-1-propanol + N,N-dimethylacetamide and positive for the other two binary mixtures.({V}_{text{m}}^{text{E}}),({Delta k}_{text{s}}), and ({Delta n}_{text{D}}) were correlated using the Redlich–Kister and Cibulka equations for binary and ternary mixtures, respectively. The Perturbed Chain Statistical Associating Fluid Theory (PC-SAFT) equation of state proved to be an effective tool for modeling the density of binary mixtures and ternary mixture. For modeling speed of sound as predictive approach in these mixtures, Schaaff’s Collision Factor Theory and Nomoto’s Relation were employed as theoretical models. Additionally, four mixing rules were successfully applied to predict the refractive index of the studied mixtures. These findings provide insights into intermolecular interactions, molecular size differences, and structural characteristics within the mixtures.

Solar thermal collectors are a vital technology for the efficient utilization of solar energy. Their performance, however, is affected by complex heat transfer mechanisms and challenges associated with system integration. This review aims to provide a comprehensive analysis of recent advancements in heat transfer optimization for solar collectors, addressing a notable gap in the literature regarding systematic and multifaceted approaches to performance enhancement strategies. The manuscript discusses key technological innovations across various domains, including the application of nanofluids to improve thermal conductivity and optical properties, structural modifications such as optimized flow paths and fin configurations, the incorporation of phase change materials for thermal energy storage, advanced coating and filling techniques designed to minimize losses, algorithmic and machine learning models for performance prediction and control, and heat pipe technologies for efficient thermal transport. These innovations collectively lead to significant improvements in thermal efficiency, system stability, and operational flexibility. The review concludes that the synergistic integration of multiple technologies offers the greatest potential for next-generation solar thermal systems. Furthermore, future research should focus on intelligent control strategies, environmental adaptability, recyclable materials, and system-level lifecycle optimization to facilitate the transition of solar thermal energy from a supplementary to a primary energy source.

The present work reviews thermophysical property data such as density, surface tension, normal spectral emissivity, and molar heat capacity for liquid binary Al–Ti alloys measured by electromagnetic levitation (EML). The data are studied as functions of temperature and composition. In EML, forces generated by an inhomogeneous magnetic AC field stably position the specimen against gravity. Melting is achieved by inductive heating. Density (volume) is determined from the droplet’s edge curve in the shadow graph profile. Surface tension is determined from the frequency spectrum of the time-dependent radius. Normal spectral emissivity is determined by a direct radiance method, and the laser modulation calorimetry methods is used for the determination of the molar heat capacity. The results are discussed on the basis of thermodynamic solution models, and the obtained excess properties are compared with each other. A great similarity is hereby found demonstrating the pronounce non-ideality of the Al–Ti system.

The solubility of 2,4,6-trinitrotoluene in ethanol + water mixed solvents was systematically determined using the gravimetric method within the temperature range from 298.15 K to 338.15 K and under a pressure of 0.1 MPa. The experimental results indicate that in this binary solvent system, the solubility of 2,4,6-trinitrotoluene increases monotonically with the rise in the molar fraction of ethanol. Furthermore, over the investigated temperature range, the solubility also increases with temperature. To enhance the applicability of the solubility data, the experimental results were correlated using four thermodynamic models: the modified Apelblat model, the van’t Hoff model, the Yaws model, and the CNIBS/R–K model. The correlation performance of each model was evaluated based on relative deviation, average relative deviation, and root mean square deviation. The results demonstrate that all models exhibit satisfactory correlation accuracy in the selected solvent system, with the CNIBS/R–K model showing the best performance. This study provides important fundamental data for the optimization of the synthesis process of 2,2′4,4′6,6′-hexanitrostilbene.

This study experimentally investigates the intermolecular forces governing n-undecane +2-alkanol (C₃–C₇) at varying temperatures using density and viscosity measurements. Excess molar volumes (V^E) and viscosity deviations (Δη) were calculated to characterize the mixing behavior. Positive V^E values suggest that n-undecane disrupts the hydrogen bonding network within the 2-alkanols, leading to volumetric expansion. The trend of decreasing V^E with increasing alkanol chain length indicates improved molecular packing. Negative Δη values suggest a reduction in viscosity compared to ideal mixing, with longer alkanols exhibiting more negative deviations, implying a greater disruption of cohesive forces. The PC-SAFT equation of state was used to correlate the mixture densities, yielding results in excellent accord with the experimental data by optimizing the adjustable parameters (k_ij), as confirmed by small absolute average deviations. The highest observed deviation between experimental and predicted densities was 0.64%, which was found in the undecane +2-heptanol mixture. The results offer valuable insights into the thermodynamic properties of alkane–alcohol mixtures, with implications for fuel formulation and chemical process engineering.

Liposomal products enable new therapies through the protection and controlled release of encapsulated medicines. The diffusion coefficient of a liposome is associated with its size and surface properties, and its measurement is important in the evaluation of the product and design of new drug delivery systems. We propose a rapid and label-free diffusion sensing method using light-induced dielectrophoresis for high-throughput analysis of liposomal products. In this study, the diffusion coefficient of liposomes with a diameter of approximately 100 nm was measured by observing the mutual diffusion within a few seconds. Prior to the measurement, a parametric study of the excitation conditions was performed to achieve highly efficient manipulation of liposomes by light-induced dielectrophoresis. The validation of the proposed measurement method for liposomes was demonstrated by comparing the result of observation by the transmission electron microscope. The effect of the surface functional groups of the liposomes was quantitatively evaluated using diffusion coefficient measurements. Furthermore, the thermo-sensitive liposomes were measured to demonstrate their sensitivity to phase transition during temperature change.