Journal of Thermal Analysis and Calorimetry最新文献

Nano-encapsulated phase change materials (NEPCMs) have advantages of both phase change materials as well as the proficiencies of nanoparticles, and they play a crucial role in enhancing thermal management across multiple industries. Polyethylene glycol + N-Nonadecane/Ethylene glycol-based nano-encapsulated phase change materials (left( {{text{NEPCMs}}} right)) flow and heat transport efficiencies within a permeable enclosure with magnetic parameter, activation energy, radiation parameter, and Christov–Cattaneo heat flux are numerically scrutinized in this investigation. Finite element technique is implemented to solve the fluid equations along with boundary conditions. Patterns of motile and oxygen microorganisms, heat capacity ratio, temperature patterns, and velocity patterns for different influencing parameters are plotted and analyzed in detail. The values of Nusselt number are also scrutinized and illustrated for various parameters. Important findings of this analysis reveal that higher values of Cattaneo–Christov heat flux parameter leads to stronger velocity vortices inside the cavity. Rising values of porous parameter weakens the vortex circulation which leads to reduction in flow strength. As fusion parameter (left( {{uptheta }_text{f} } right)) intensifies from 0.1 to 0.9, the phase transition zone shrinks, accelerating the melting process of NEPCMs. Higher bio-convection Rayleigh number (Rb) enhances microorganism concentration patterns and introduces complex flow structures. Increasing Stefan number (left( {{text{Ste}}} right)) broadens the transition zone, indicating stronger latent heat effects.

Sutterby fluid rheology and electroosmotic phenomena combine the modern electrokinetic transport technologies with the realistic fluid behavior. This enhances predictions that are more accurate, improved designs, and greater performance of a wide array of applications in areas such as process engineering, biotechnology, and so on. In order to capture bioconvective effects, this work models the radiative electroosmotic flow (EOF) of a ternary hybrid nanofluid (TiO₂–Al₂O₃–Fe₃O₄ in a 50:50 propylene glycol–water base) as a non-Newtonian Sutterby fluid which incorporates gyrotactic microorganisms. For sophisticated heat transfer applications, the framework provides a realistic model by taking into account viscous dissipation, chemical processes, nonlinear radiation, porous media, and Joule heating. The objective of this research is to evaluate and improve the heat transfer performance of a ternary hybrid Sutterby nanofluid by modeling and examining its radiative electroosmotic flow, which incorporates bioconvection, porous media, nonlinear radiation, and various thermophysical factors. The governing partial differential equations are reduced via similarity transformations and solved numerically using a sixth-order Runge–Kutta method coupled with the Nachtsheim–Swigert shooting technique. To enhance predictive capability, an artificial neural network (ANN) based on the backpropagated Levenberg–Marquardt algorithm (ANN-BLMS) is implemented. The ANN model exhibits outstanding accuracy, achieving a perfect correlation coefficient (R = 1.0), thereby validating its robustness in modeling nonlinear electroosmotic heat transfer phenomena. Results reveal that for 0 < η < 1.6, the trihybrid PGW fluid velocity increases with magnetic force and then declines, while it consistently rises with Helmholtz, electroosmotic, and Sutterby parameters. Additionally, increasing electroosmotic and Helmholtz parameters tends to suppress heat transfer, while thermal radiation significantly improves it. The Sutterby fluid parameter exhibits a non-monotonic influence on temperature, and microorganism concentration decreases with elevated electroosmotic and Peclet numbers. These findings underscore the utility of ANN as a reliable surrogate modeling tool and highlight the potential of trihybrid nanofluids in applications such as microfluidic drug delivery, advanced cooling technologies, and catalytic systems where precise thermal control and bioconvection are critical.

The present study examines the changes in the viscosity of graphite nanoparticles (GNPs) with distinct insights. The temperature range of the nanofluid (NF) from 20 to 50 °C and the volume fraction (VF) of GNP, as compared with the fluid, varying from 0.1 to 0.5%, are the two key variables to achieve optimal NF characteristics. The experimental results confirm that the viscosity of the NF is inversely proportional to the temperature changes, whereas GNP VF follows a direct trend upon changes in viscosity. The intermolecular attraction forces decreased with an increase in temperature, helping to dilute the fluid. At high concentrations, the inhibitory role is lost, and the nanoparticles themselves contribute to the increase in yield stress by coagulation. The optimal condition corresponds to 0.5% VF of GNP at 20 °C. Under such conditions, a 22.6% increase in viscosity was achieved compared to the water-based fluid. Utilizing varying NF temperature and GNP VF (as input), a set of experimental viscosity data (as the target function) was primarily collected. A curve-fitting technique was then employed to develop a theoretical correlation based on the input and target functions. The obtained correlation coefficient (R), i.e., 0.99753, indicates a strong correlation between the experimental data and the proposed relation. In the present study, the perceptron neural network, the Purelin, and the tangent sigmoid functions were used. The algorithm considered was the Levenberg–Marquardt (LM) algorithm, and 32 neurons were used for both optimization and prediction. The root mean squared error (RMSE), mean squared error (MSE), correlation coefficient (R), and mean absolute error (MAE) for the proposed relation, as well as artificial neural network (ANN) data, are shown. These values for the proposed relation data are reported as follows: 0.00782, 0.00000342, 0.997, and 6.25 × 10⁻⁷. Accordingly, the ANN is: 8.74 × 10⁻³), 7.6 × 10⁻⁵, 0.998, and 6.939 × 10⁻¹⁸, respectively. The margin of deviation (MOD) was calculated as -2.1831 < MOD < 3.1420.

Developing efficient and adaptive photothermal materials is crucial for advancing solar steam generation (SSG) technologies for sustainable water purification. Here, we investigate the influence of an external magnetic field on the spatial reconfiguration and evaporation performance of Fe₃O₄-decorated carbon dots (CDs) photothermal membrane. We show that moderate magnetic field strengths (~0.2 T) induce the formation of 3D needle-like architectures, enhancing solar absorption, thermal localization, and evaporation efficiency. Conversely, excessive field strengths (>0.3 T) lead to structural instability, reducing photothermal performance. The maximum evaporation rate of the Fe₃O₄@CDs-based photothermal membrane reaches 1.502 kgm⁻²h⁻¹ under 1 sun irradiation and 0.2 T. These findings highlight the role of magnetic field-induced structural evolution in optimizing solar-driven water evaporation, offering new strategies for the design of reconfigurable, high-performance photothermal materials.

Gas extraction is a crucial measure to solve the coal mine gas disaster, but the broken coal body near the extraction borehole is easily oxidized naturally in the process of gas extraction, resulting in the continuous development of the internal pores of the fractured coal body, which further exacerbates the intensity of air leakage and the degree of ignition. To improve the gasification efficiency of coal seams and predict the dangerous area of gas spillage, this paper profoundly investigates the evolution law of different pore sizes, functional pores, and fracture development laws of the coal body around the reaction area during the spontaneous combustion of coal. The investigation uses the coal spontaneous combustion (CSC) simulation experimental system and nuclear magnetic resonance porosimetry technology. Additionally, it reveals the inner mechanism of pore evolution using the CSC simulation experimental system coupled with gas chromatography. The study shows that the internal pores of coal bodies with a low degree of metamorphism are more developed, and these pores develop faster during the CSC process. The development of micropores and mesopores is dominant in the low-temperature stage (30 ~ 110 ℃) of coal body combustion, while mesopores and macropores dominate in the high-temperature stage (> 110 °C). The adsorption capacity and seepage capacity of the coal body to the generated gas are enhanced as the combustion process advances. However, the enhancement of seepage capacity lags behind the adsorption capacity, which may lead to difficulties in gas extraction during the initial oxidation stage. In the initial stage of the coal combustion process, pore development mainly relies on decomposing water-containing compounds. However, with the increase in oxidation temperature, the oxidation of organic matter inside the coal gradually becomes the main factor for pore development.

This study investigates the coupled mechanisms of bioconvection and phase-change heat transfer in a porous chamber saturated with Nano-Encapsulated Phase-Change Material (NEPCM)–water nanofluid containing oxytactic microorganisms. The chamber is bounded by a sinusoidally heated, oxygen-permeable bio-coated left wall and a cooled, oxygen-permeable bio-coated right wall, while the horizontal walls are adiabatic and impermeable. This configuration enables simultaneous analysis of latent-heat exchange by NEPCM capsules, microorganism-induced buoyancy, and momentum resistance within the porous matrix. A Galerkin finite-element formulation is employed to solve the coupled nonlinear equations derived from the Darcy–Brinkman–Forchheimer model and bio-convective transport theory. The effects of the Rayleigh number (Ra), bioconvection Rayleigh number (Rb), Darcy number (Da), Lewis number (Le), Peclet number (Pe), Stefan number (Ste), and fusion temperature (θ_f) are examined to characterize flow, heat, and mass-transfer behavior. The results indicate that heat and mass transfer intensify significantly with increasing Ra, Rb, and Da, with Da exerting the dominant influence, enhancing the average Nusselt number by over 380%. Optimal ranges of Le and Pe are identified for maximizing oxygen diffusion and microorganism transport. The findings provide new physical insight into biothermally active porous systems and offer design guidance for hybrid bio-nanofluidic and thermal-energy-storage devices employing NEPCM-based suspensions.

This research investigates the mechanical, thermal and interfacial properties of natural fiber-reinforced polymer composites emphasizing the effects of alkali and silane fiber treatments. Untreated fiber composites (F, FL0 – FL2) exhibited enhanced mechanical properties with tensile strength increasing from 82.7 MPa (F) to 137.7 MPa (FL1) and flexural strength from 121.3 to 151.1 MPa, although thermal stability slightly decreased due to the presence of thermally labile fiber constituents. Alkali–silane treated composites (FLT0 – FLT2) showed further improvement in mechanical performance, with tensile strength reaching 164.2 MPa (FLT1), flexural strength of 176.3 MPa and ILSS of 40.7 MPa along with higher thermal conductivity and elevated decomposition temperatures. The combined alkali–silane treatment enhances fiber–matrix bonding, removes impurities and reduces hydrophilic surface groups resulting in improved load transfer and thermal resistance. These finding highlight the potential of treated natural fiber composites for structural, automotive and thermally demanding applications.

This study investigates the explosion suppression mechanism of a novel composite deflagration inhibitor (SK), synthesized from industrial waste blast furnace slag (S105) and KH₂PO₄, for the suppression of aluminum dust explosions. By employing a liquid-phase chemical coating method, SK integrates S105 (a low-cost, high-strength matrix) and KH₂PO₄ (a chemically active carrier) into a core–shell structure, achieving synergistic suppression effects. Explosion suppression effect were evaluated using a dual-channel 20 L spherical explosion vessel and a Hartmann tube, revealing that SK reduced the maximum explosion pressure by 23.9%, the pressure rise rate by 70.7%, and the flame propagation speed by 67.3%. These results indicate that SK outperforms individual components (S105 and KH₂PO₄) as well as conventional inhibitors (e.g., NaHCO₃). Thermogravimetry–differential scanning calorimetry (TG–DSC) and microstructure characterization techniques, such as scanning electron microscopy (SEM) and X-ray diffraction (XRD), elucidate the dual inhibition mechanisms: (1) Physical inhibition, through endothermic decomposition and release of H₂O to dilute oxygen and form a physical barrier; (2) Chemical inhibition, which suppresses explosions by scavenging radicals and terminating chain reactions. S105 is more cost-effective than its components, primarily due to the ultra-low cost of slag. This work not only promotes the sustainable use of industrial waste resources but also provides a scalable and efficient solution for industrial explosion safety, aligning with global circular economy goals.

Metal friction is ubiquitous in engineering applications, and its effects on energy dissipation, interface damage, and structural failure have a significant impact on the performance and reliability of engineering systems. This paper systematically reviews recent advances in the thermo-mechanical analysis of metallic friction interfaces. Based on the interaction between thermodynamics and mechanics, it analyses the theoretical framework of multi-physics coupling analysis of metallic friction interfaces and presents the development history of thermo-mechanical coupling models. By deconstructing the fundamental theoretical framework of tribology, this study focuses on revealing the dynamic evolution laws of thermal effects at interfaces, summarising the microscopic mechanisms of friction-induced heat generation, the influence patterns of heat conduction mechanisms, and the distribution characteristics of three-dimensional temperature fields. Furthermore, by integrating the theory of elastic–plastic mechanics, this study characterises the distribution of thermal stresses and the dynamic response characteristics of thermal deformation, elucidating the regulatory mechanisms of the temperature field-stress field coupling effect on interface mechanical properties. Through critical analysis, this study identifies the limitations of current models in characterising dynamic loads and phase transition effects, and explores the synergistic application of multi-scale simulation and intelligent sensing technologies to provide new insights for optimising interface performance.

Graphical abstract

The escalating demand for nonrenewable energy resources has significantly contributed to environmental degradation, making the transition to renewable energy sources indispensable. Solar energy, in particular, stands out as a sustainable alternative, as it can be harnessed in both thermal and electrical forms simultaneously through photovoltaic/thermal (PV/T) collectors. This study emphasizes the advances in PV/T technologies, presenting a comprehensive synthesis of strategies that have been independently explored in the literature, while reformulating them into a coherent framework with a special focus on emerging approaches.

One of the most effective techniques involves the integration of phase change materials (PCM), which enhance system performance by improving thermal efficiency by 3–5% and electrical efficiency by 20–30%, while also alleviating uneven temperature distribution. The incorporation of nanofluids into the flow channel further improves heat transfer characteristics, resulting in greater overall efficiency. Additional structural modifications, such as the insertion of fins, thin metallic sheets, and porous media within the air channel, have been shown to enhance electrical efficiency by 7.7% and thermal efficiency by 17.6%. Equally critical is the role of material selection in determining PV/T performance. Prior research highlights the potential of innovative solar cell technologies, particularly amorphous silicon, for further efficiency improvements. Moreover, PV panels equipped with parallel cooling channels have demonstrated efficiencies reaching 18.92%. The optical and thermal characteristics of cover glass are also decisive, with 4 mm thick glass identified as optimal for maximizing solar transmission while minimizing thermal losses through radiation and convection. However, its fragile nature necessitates careful handling to avoid additional costs due to breakage.

Among the various approaches reviewed, the combination of PCM with hybrid nanomaterials has emerged as the most promising solution, particularly from an economic perspective. The stored thermal energy not only enhances system reliability but also enables extended operation beyond sunlight hours, thereby reducing electricity consumption and contributing to more sustainable energy utilization.