Search Results (3,072)

This study proposes a sustainable, integrated biorefinery approach to valorize mussel shell waste into high-value products, including chitin, chitosan, and calcium formate. Formic acid was employed as an effective demineralizing agent, enabling not only efficient mineral removal but also the direct conversion of the demineralization effluent into value-added calcium formate. The sequential extraction processes, demineralization, deproteinization, and decolorization, successfully yielded purified chitin (PCH), which was subsequently deacetylated to produce chitosan (CTS) with a degree of deacetylation of 85% and a molecular weight of 75 kDa. The physicochemical properties of all products were characterized using Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM). FTIR and XRD analyses confirmed the successful extraction of chitin and chitosan, demonstrating the feasibility of mussel shells as an alternative biopolymer source. In parallel, calcium formate (CCF) was obtained from the demineralization effluent with a yield of 94.19%, and its formation was verified by FTIR and XRD. Elemental analysis by XRF exhibited 98.3% CaO with minimal non-toxic impurities. The TGA/DTG profiles of CCF exhibited a well-defined two-step thermal decomposition, confirming its anhydrous form. Overall, this environmentally benign process enables the simultaneous production of multiple value-added products while significantly improving resource utilization and reducing waste generation. The proposed integrated biorefinery model offers a promising, economically viable pathway for marine biomass valorization, aligned with the Bio-Circular-Green (BCG) economy concept. Full article

Mechanically activated pyrite plays an important role in gold extraction and coal utilization, but its reactivity may change markedly during storage. This study investigates how air deactivation during storage affects the crystal structure and subsequent thermal decomposition behavior of mechanically activated pyrite. Pyrite was mechanically activated and then stored in air for 0, 7 and 180 days. X-ray diffraction (XRD) combined with Rietveld refinement was used to characterize variations in lattice parameters and unit-cell-related structural features, while non-isothermal thermogravimetric–differential scanning calorimetry (TG-DSC) under an argon atmosphere, together with the Flynn–Wall–Ozawa (FWO) method, was applied to evaluate the decomposition kinetics. Air deactivation induced a non-monotonic evolution of lattice parameters and unit-cell volume, which is attributed to combined effects of residual stress relaxation and air-induced surface-related modification during storage. All samples exhibited two mass-loss stages during heating, reflecting stepwise thermal decomposition, and their decomposition behavior varied systematically with deactivation time. The apparent activation energy depended on both conversion fraction and deactivation degree, and nucleation-and-growth-type mechanisms were found to dominate the decomposition process, with their relative contributions evolving with storage time. These results clarify how prior air-deactivation history influences the structural evolution and subsequent thermal decomposition behavior of mechanically activated pyrite and provide useful insight for its storage and utilization in related processes. Full article

As a key type of precursor material in the nuclear fuel cycle process, plutonium oxalate has long played a critical role in the purification and conversion of plutonium. Its crystallization behavior directly affects the subsequent production process and properties of plutonium oxide. This review systematically summarizes the research progress of plutonium oxalate crystals in thermodynamics, crystallization kinetics, and crystal morphology. It introduces the structural characteristics of plutonium oxalate crystals, their solubility in nitric acid-oxalic acid mixed systems, and the thermodynamic properties such as the redox stability of plutonium oxalate crystals of different valence states. It also summarizes the nucleation, growth, and coprecipitation kinetics of plutonium oxalate crystals. The diversity of plutonium oxalate crystal morphologies and their influence on subsequent thermal decomposition are discussed. Full article

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

As the global demand for lithium-ion batteries (LIBs) continues to rise, battery recycling has become a critical strategy for mitigating resource depletion, minimising environmental impact, and advancing a circular economy. However, recycled electrode materials, particularly cathode and anode powders, often contain residual impurities such as transition metals (e.g., Cu, Fe, Al), polymeric binders (e.g., PVDF), and electrolyte decomposition products. These contaminants can significantly impair the electrochemical performance, thermal stability, and overall safety of newly manufactured cells. This study aims to systematically investigate the nature, origin, and impact of impurities in recycled cathode and anode materials. A suite of analytical techniques, including inductively coupled plasma mass spectrometry (ICP-MS), infrared spectroscopy (IR), scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS), and thermogravimetric analysis (TGA), will be employed to quantify impurity levels and assess material integrity across various recycling streams. The findings are expected to inform the establishment of impurity threshold limits for battery-grade recycled materials and guide the development of enhanced purification protocols. Ultimately, this research will support the production of safer and more reliable second-life batteries, offering valuable insights to recyclers, manufacturers, and regulatory bodies committed to sustainable energy storage technologies. 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