Search Results (3,068)

The development of sustainable encapsulation materials with tunable thermomechanical properties remains a critical challenge for photovoltaic reliability. Currently, the mainstream encapsulant for polycrystalline silicon solar cells is crosslinked EVA (Ethylene-Vinyl Acetate), which complicates the end-of-life recycling and reuse of modules. There is an urgent need to develop a novel encapsulant that combines excellent barrier properties with thermoplastic recyclability. Herein, we report a novel series of thermally decomposable CO₂-based thermoplastic polyurethane (PPC-TE) films engineered through the rational design of soft and hard segments. Utilizing polycarbonate diol (PPCDL) and polyether glycol (PEG) as soft segments, we systematically tailor material properties by modulating PEG-to-PPCDL ratios (5–20 wt%) and PEG molecular weights (1000–4000 g/mol). The optimized PPC-TE films exhibit excellent transmittance (>90%), adjustable glass transition temperature (T_g: 35.1 °C~11.6 °C), and remarkable mechanical adaptability (51~92 HA). The PPC-TE films exhibit water vapor permeability (WVP) as low as 14.8 g·mm·m⁻²·day⁻¹ and oxygen permeability (OP) of 4.13 cc·mm·m⁻² day⁻¹ at 15 wt% PEG content, surpassing commercial ethylene–vinyl acetate (EVA) encapsulants. Notably, these films demonstrate fully thermal decomposition above 350 °C, facilitating eco-friendly photovoltaic device recycling. Superior adhesion to glass substrates is evidenced by peel strengths up to 37 N/cm (PPC-TE2000-20) and the shrinkage rate is as low as 3%. This work contributes to improving the long-term stability of solar cells and has the potential for large-scale production. Full article

Phase change material (PCM)-based latent heat storage (LHS) systems help address the mismatch between renewable energy supply and thermal demand. However, their practical implementation is constrained by the strongly nonlinear and multiphysics nature of phase change, which makes high-fidelity simulations and real-time applications computationally expensive. This review examines mathematical reduced-order modeling (ROM) as an effective strategy to overcome this limitation by combining physics-based simplifications, projection methods, interpolation techniques, and data-driven models for PCM-based LHS systems. While physical simplifications (such as dimensional reduction and effective property approximations) represent an important first layer of model reduction, the primary focus of this work is on the mathematical ROM methodologies that operate on the governing equations after such physical simplifications have been applied. The review covers approaches including two-temperature non-equilibrium and analytical thermal-resistance models, Proper Orthogonal Decomposition (POD), CFD-derived look-up tables, kriging and ε-NTU grey/black-box metamodels, and machine-learning methods such as artificial neural networks and gradient-boosted regressors trained from CFD data. These ROM techniques have been applied to packed beds, PCM-integrated heat exchangers, finned enclosures, triplex-tube systems, and solar thermal components, achieving speed-ups from tens to over 80,000 times faster than full CFD simulations while maintaining prediction errors typically below 5% or within sub-Kelvin temperature deviations. A critical comparative analysis exposes the fundamental trade-off between interpretability, data dependence, and computational efficiency, leading to a practical decision-making framework that guides method selection for specific applications such as design optimization, real-time control, and system-level simulation. Remaining challenges—including accurate representation of phase change nonlinearity, moving phase boundaries, multi-timescale dynamics, generalization across geometries, experimental validation, and integration into industrial workflows—motivate a structured roadmap for future hybrid physics–machine learning developments, standardized validation protocols, and pathways toward industrial deployment. Full article

Flunarizine is a calcium channel blocker widely used in neurological disorders; however, its low aqueous solubility may influence formulation stability and drug dispersion in polymer-based systems. The present study aimed to evaluate the compatibility of flunarizine with selected excipients and to investigate its incorporation into polymeric hydrogel matrices. Binary mixtures of flunarizine with excipients such as hydroxypropyl-β-cyclodextrin, polyethylene glycol (PEG 6000), Tween 20, gelatin, and citric acid were prepared and characterized using Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TG/DTG), and high-performance liquid chromatography (HPLC). The FTIR spectra of the analyzed samples do not reveal the appearance of new absorption bands that may indicate chemical interactions; instead, minor spectral variations were observed due to weak intermolecular interactions within the polymer network. Thermal analysis revealed decomposition patterns consistent with those of the individual components, suggesting the absence of significant incompatibilities. A validated RP-HPLC method enabled sensitive and reliable quantification of flunarizine in the analyzed systems, with a limit of detection (LOD) of 0.05 µg/mL and a limit of quantitation (LOQ) of 0.16 µg/mL. Accuracy testing showed average recovery rates of 100% across 80–120% spiking levels. Overall, the results support the compatibility of flunarizine with the investigated excipients and the suitability of the studied hydrogels as potential drug delivery matrices. Full article

In the context of new-type power system construction, digital twin has become the core technology for power transformers, supporting their full-life cycle intelligent operation and maintenance. The real-time, high-precision calculation of the internal temperature field serves as the core supporting element for realizing the real-time mapping between the physical transformer entity and its virtual twin. Aiming at the inherent defects of traditional temperature rise calculation methods, such as insufficient accuracy and an excessively long computation time, this paper proposes a simplified calculation model for the transformer temperature field. In this model, the transformer oil tank is simplified into a two-dimensional axisymmetric thermal–fluid coupled field model solved by the finite volume method (FVM). The Proper Orthogonal Decomposition (POD) technique is adopted to perform order reduction on the matrices involved in the governing equations, so as to reduce the computational degrees of freedom. Meanwhile, the radiator is equivalent to a one-dimensional thermal circuit model, and the field–circuit coupled solution is achieved through bidirectional data mapping. Temperature field calculation is carried out for a 220 kV oil-immersed transformer based on the proposed model. The results show that the average relative error between the calculated results and the experimental data is around 0.86%, while the computation time is merely 0.04% of that of the traditional three-dimensional full-scale model. Furthermore, taking the real-time overload capacity evaluation of the transformer as a case, it is verified that the proposed model can successfully support the requirements of practical engineering applications. Full article

The non-thermal plasma (NTP) process is a promising advanced oxidation process (AOP) for removing non-biodegradable organics from wastewater, owing to the efficient formation of reactive chemicals. Despite its effective oxidizing capability, the decomposition mechanism of organic pollutants is not well understood. This study evaluates NTP for two representative sulfonamides (SMZ and STZ) and reports on (i) time-resolved removal to the method detection limit, (ii) transformation mapping using LC-ESI/MS/MS, which confirmed previously proposed hydroxylation and bond-cleavage pathways and further identified additional hydroxylated intermediates formed on the thiazole and benzene rings under NTP conditions, and (iii) energy evaluation through energy per order (EEO) within a single, reproducible operating window. The EEO values for SMZ and STZ degradation via NTP were calculated at 22.4 and 7.5 kWh/m³/order, respectively. These values are up to 37- and 118-fold lower than those reported for comparable AOPs, quantitatively confirming that the proposed NTP process achieves superior energy efficiency for sulfonamide degradation. Degradation is primarily attributed to reactive oxygen species (ROS) generated by plasma, which initiate the breakdown of the antibiotic structure. Overall, this study demonstrates that NTP is a highly effective AOP for driving the rapid primary degradation and intermediate structural transformation of recalcitrant sulfonamide antibiotics. Full article

Landfills are a significant source of atmospheric emissions associated with the decomposition of organic waste; however, conventional monitoring methods typically have limited spatial coverage. This study evaluates the use of an UAV-based system for the spatial characterization of gases associated with biogas emissions at a municipal landfill. A DJI Matrice 350 RTK platform equipped with a Sniffer4D Mini2 multi-gas station and a Zenmuse H20T thermal camera were used. Four flight campaigns were conducted at an altitude of 20 m, with an acquisition frequency of approximately 1 Hz, recording total hydrocarbons (C_xH_y) as an indirect indicator of methane (CH₄), carbon dioxide (CO₂), carbon monoxide (CO), nitrogen dioxide (NO₂), ozone (O₃), sulfur dioxide (SO₂), oxygen (O₂), temperature, and relative humidity. The results showed a marked transition around 13:10 h, characterized by a simultaneous increase in CH₄ equivalent and CO₂, along with a decrease in NO₂, O₃, and SO₂. Furthermore, CH₄ equivalent and CO₂ showed the highest positive correlation among the variables (r = 0.96). Spatial maps generated using ordinary kriging revealed more heterogeneous patterns, while the qualitative thermal orthophoto confirmed the site’s surface variability. Overall, the results demonstrate that the integration of multi-gas sensors and aerial thermography on UAVs is viable for the spatial monitoring of landfills. Full article

To elucidate the influence of water on terahertz (THz) spectral responses, terahertz time-domain spectroscopy (THz-TDS) was employed to monitor the thermal decomposition of copper(II) sulfate pentahydrate in this study. Continuous dehydration of the hydrate induces pronounced variations in the THz signal. At the initial stage of thermal decomposition, these changes primarily originate from the evolving state and amount of water confined within the CuSO₄·5H₂O lattice. After detaching from the crystalline framework, the released water molecules do not evaporate immediately; instead, they transiently reside near the copper sulfate as free water. When the temperature reaches approximately 60 °C, a dynamic equilibrium is established between crystalline water and free water. The THz spectral data reveal that the sample exhibits its strongest THz absorption at this temperature. Consequently, the THz signal during decomposition displays a characteristic trend: an initial decrease followed by an enhancement. These findings demonstrate that THz-TDS represents a promising approach for probing the state and content of water, thereby contributing to the development of a powerful analytical tool for fundamental studies in mineralogy. Full article

To address the inverse identification of contact-related thermal faults in gas-insulated switchgear (GIS), this study proposes a method for contact resistance inversion and internal temperature field reconstruction. The proposed method enables the estimation of faulty internal contact resistance using external enclosure temperature data, while simultaneously reconstructing the internal temperature field. First, a forward numerical model of GIS is established, and a POD-Kriging surrogate model is developed to achieve second-level rapid prediction of the forward problem. Based on this surrogate model, the thermal fault inversion problem is formulated as an optimization problem of fault parameters and solved using the Grey Wolf Optimizer. GIS temperature-rise experiments are performed to validate the numerical model, and a real GIS contact fault case is further analyzed. The results indicate that the proposed method yields an average inversion error of 9.5% for degraded contact resistance, with the maximum error at internal temperature monitoring points remaining below 8%. The total inversion time is approximately 30 s. These findings demonstrate that the proposed method is capable of effective online inversion and diagnosis of contact-related thermal faults in GIS equipment. Full article

Mn₅₄Al₄₆ alloys with τ-phase as their main component were successfully obtained in a reproducible processing window combining melt-spinning, annealing at intermediate temperatures (450 °C) and low-energy milling. The complete ε → τ phase transformation was driven by thermal decomposition of ε-phase and favored by high grain boundary density inherent to the melt-spun microstructure. An improved magnetic response of the melt-spun Mn₅₄Al₄₆ alloys was observed, as they exhibited saturation magnetization values between 80 and 90 emu/g, together with intrinsic coercivities around 2000 Oe and Curie temperatures between 640 and 648 K. Significant coercivity enhancement over 6000 Oe was predicted, by means of micromagnetic calculations, for alloys with grain size refinement below 100 nm. The efficient, single-step experimental phase transformation with no additional stabilizers for the τ-phase was explained in terms of microstructural features, whereas magnetic enhancement was attributed to lattice distortions promoted by the milling process. This integrated approach introduces a pathway to achieve τ-phase Mn-Al with tunable magnetic performance useful for applications. Full article

The poor thermal stability of commercial polyethylene (PE) separators hinders the further application of lithium-ion batteries (LIBs), yet previous modifications struggle to balance between safety and electrochemical performance. This study proposes an interface modification strategy by forming a poly(melamine terephthalamide) (PTM) coating on the PE separator surface, constructing a “thermal–mechanical–electrochemical synergistic barrier”. The PTMs@PE separator achieves synergistic improvements in thermal shutdown behavior, thermal stability, mechanical strength, and electrochemical compatibility by taking advantage of the temperature-sensitive response of the PE separator, the flame-retardants of the rigid conjugated skeleton with the high nitrogen of PTM, and the electrolyte-affinity of its functional groups. Importantly, the principles between the molecular structure of the PTM coating and the thermal behavior is verified. The results demonstrate that PTM participates in the decomposition process of the PE separator and slows down the degradation rate of the PE chain structure, thereby resulting in a wide-temperature-range thermal shutdown temperature. The PTMs@PE effectively reduces the risk of runaway. The PTMs@PE separator achieves outstanding electrochemical compatibility, achieving a capacity retention rate of 99.27% at 2 C for 500 cycles. Notably, the separator shows high potential for scalable fabrication. This work provides a novel material system and technical pathway for developing highly safe and high-performance LIB separators. Full article

Reliable temperature distribution measurement in ultra-low temperature (ULT) chest freezers is crucial for preserving biospecimen integrity in cryopreservation, but dense sensor arrays required for accuracy are often impractical due to space constraints and cost limitations. To address this critical challenge, this work presents a systematic data-driven framework for optimal sensor placement in large-scale (3 m³) ULT chest freezers under stable operating conditions. To our knowledge, it is the first realization of high-fidelity cryogenic temperature field reconstruction coupled with sparse sensor layout optimization tailored to large-volume ULT chest freezers. First, high-resolution reference temperature fields were constructed via universal kriging interpolation, validated with leave-one-out cross-validation (LOOCV) to achieve mean absolute error (MAE) $\le 0.67 °\mathrm{C}$ and coefficient of determination $R^2>0.92$. Principal component analysis (PCA) was then applied to training data to extract a tailored proper orthogonal decomposition (POD) basis. The first three principal components captured 99.8% of cumulative energy. Optimal sensor locations were determined via QR-column pivoting on the rank-3 POD basis, converging to a minimal configuration of 3 sensors (a 94% reduction from the 48-sensor full-scale setup). This sparse sensor network achieved exceptional reconstruction performance: grid-level MAE $\le 0.079 °\mathrm{C}$ and root mean squared error (RMSE) $\le 0.093 °\mathrm{C}$ against reference fields ($R^2\ge 0.999$), while point-level validation against experimental measurements yielded MAE $\le 0.502 °\mathrm{C}$ and RMSE $\le 0.842 °\mathrm{C}$ ($R^2\ge 0.971$). The results demonstrate that, for large-scale ULT chest freezers, the proposed data-driven approach is capable of automatically determining an optimal sparse sensor subset and enabling reliable 3D cryogenic temperature field reconstruction for efficient thermal monitoring. By resolving the trade-off between monitoring accuracy, space efficiency, and cost-effectiveness, this framework provides a scientifically rigorous alternative to empirical sensor deployment standards, offering practical scalability for cryogenic biobanking applications. Full article

The paper presents the synthesis of new naphthyl-containing derivatives of thiosemicarbazide and thiourea, their water-soluble inclusion complexes with β-cyclodextrin, as well as an assessment of their potential antiviral and hemorheological activity. As a criterion for the specific antiviral effect of new compounds, their chemotherapeutic indices were calculated using predictive analytics tools driven by artificial intelligence and molecular docking methods. Molecular docking studies with three protein targets PknB (2FUM), DprE1 (6HEZ), and InhA (1ENY) confirmed strong and specific ligand–protein interactions. The effects of structural features of new compounds on the rheological characteristics of blood were considered, and the most promising samples were identified for further in-depth in vitro study of their specific biological activity. The performed thermoanalytical study showed that the structure of the included ligand, as well as the shape of the receptor, significantly affect the thermal stability and kinetic parameters of the decomposition of the inclusion complex. In silico evaluation of the newly synthesized compounds revealed promising biological activity profiles, with all compounds demonstrating predicted antimycobacterial and antituberculosis potential. In silico analysis of the newly synthesized compounds revealed favorable biological activity profiles, with all candidates demonstrating predicted antimycobacterial and antituberculosis potential. Full article

Galactic cosmic rays (CRs) are a fundamental non-thermal component of the interstellar medium (ISM). Understanding the transport of super-high-energy particles is essential for interpreting observations of Galactic PeVatrons. Classical diffusion models assuming a homogeneous and isothermal medium oversimplify the multiphase ISM. We utilize high-resolution three-dimensional magnetohydrodynamic simulations to self-consistently generate a multiphase ISM—comprising the warm (WNM), unstable (UNM), and cold neutral medium (CNM)—and investigate 1.5–15 PeV particle transport using a test-particle approach. We find that thermal phase transitions induce steep magnetic field strength gradients at phase boundaries, creating localized magnetic fluctuations that act as efficient sites for adiabatic mirror reflections and non-adiabatic pitch-angle scattering, strongly enhancing cross-field transport at these interfaces. However, because phase boundaries occupy only a small volume fraction and particles spend most of their trajectory in the weakly scattering WNM and UNM, the global pitch-angle scattering coefficient in the multiphase ISM is smaller than in an equivalent isothermal medium. This locally strong scattering nevertheless drives both parallel and perpendicular spatial diffusion coefficients to ∼${10}^{30}$ cm² s⁻¹ at 1.5 PeV, with the perpendicular component exceeding its isothermal counterpart (∼${10}^{28}$ cm² s⁻¹) by two orders of magnitude. Using a phase–phase diffusion matrix decomposition, we show that global CR transport is governed by the volume-filling, trans-Alfvénic WNM and UNM, where particles stream along stochastically wandering field lines. Cross-phase displacement correlations are universally positive, indicating cooperative transport between thermal phases. In contrast, the super-Alfvénic CNM acts as an efficient confinement that substantially suppresses local diffusion. Full article

Accurate prediction of transient melt pool thermal fields in Laser Powder Bed Fusion (LPBF) is essential for understanding melt pool geometry and defect formation mechanisms, yet conventional finite element methods (FEM) impose prohibitive computational costs for parametric process exploration. A variational physics-informed neural network (VPINN) framework is presented for 3D transient thermal modeling of a GH3536 single-track LPBF scan. The framework incorporates a continuously differentiable Goldak double-ellipsoid moving heat source, temperature-dependent thermophysical property surrogates, and an effective heat-capacity treatment of latent heat associated with solid–liquid phase change and vaporization. These components are embedded in a weak-form residual-minimization scheme with octree-adaptive domain decomposition, hierarchical Legendre test functions, and sequential sliding-window time marching. Effective absorptivity is inferred jointly with the network parameters, using sparse experimental melt pool profiles as supervision. Within a parametric study covering laser powers from 100 to 140 W and scan speeds from 1000 to 1500 mm/s, the predicted melt pool width, depth, and aspect ratio agree closely with FEM benchmarks and cross-sectional optical micrograph measurements across both supervised and held-out interpolation conditions, with total relative L₂ nodal temperature errors ranging from 3.23% to 6.75%. Following a one-time offline training investment of 15,323 s that simultaneously resolves the full parametric space, surrogate inference reduces per-condition query time from 3000–4000 s (FEM) to merely 4–5 s, delivering a speedup of two to three orders of magnitude and making the framework increasingly cost-effective for high-throughput parametric studies and digital-twin integration as the number of queried conditions grows. Full article

To overcome the low strength of conventional polytetrafluoroethylene/aluminum (PTFE/Al) reactive materials and the insufficient reaction efficiency of aluminum, this study introduces highly reactive aluminum–cerium alloys (Al-Ce-1#, -2#, and -3#, with Ce contents of 30, 50, and 70%, respectively; the primary phase in Al-Ce-3# is Al₂Ce) with a multiscale structural design (comprising both micron-sized and nano-sized particles) into an ammonium perchlorate (AP) matrix. Al/AP reactive materials and Al-Ce/AP reactive materials with varying Ce contents were prepared. The thermal decomposition characteristics, dynamic mechanical properties, and impact ignition behavior were systematically investigated using differential scanning calorimetry (DSC) and split Hopkinson pressure bar (SHPB) experiments. The results demonstrate that the addition of Al₂Ce significantly alters the thermal decomposition process of AP, substantially lowering its decomposition temperature (by approximately 69 °C) and promoting concentrated exothermic decomposition. SHPB tests reveal that Al₂Ce/AP composites exhibit higher dynamic yield strength and flow stress than the Al/AP, accumulating faster strain energy density under impact loading, which indicates a more violent fragmentation failure mode. This enhanced mechanical failure behavior, which provides highly reactive interfaces and promotes hotspot formation, synergizes with the catalytic effect of Al₂Ce on AP decomposition. Together, these mechanisms jointly improve the impact ignition sensitivity of the material, significantly lowering its ignition threshold and shortening its combustion duration. This study confirms that Al₂Ce/AP is a novel reactive material combining excellent dynamic mechanical properties with outstanding impact reactivity, providing theoretical and technical support for the application of highly reactive rare-earth aluminum alloys in aluminum-based reactive materials. Full article