Search Results (63)

Nutrition plays a fundamental role in promoting health and preventing chronic diseases, with bioactive food components offering a therapeutic potential in biomedical applications. Among these, edible oils are recognised for their functional properties, which contribute to disease prevention and metabolic regulation. The proposed study aims to evaluate the quality of four bioactive oils (olive oil, sunflower oil, tomato seed oil, and pumpkin seed oil) by analysing their thermal behaviour through infrared (IR) imaging. The study designed a customised electronic system to acquire thermographic signals under controlled temperature and humidity conditions. The acquisition system was used to extract thermal data. Analysis of the acquired thermal signals revealed characteristic heat absorption profiles used to infer differences in oil properties related to stability and degradation potential. A hybrid deep learning model that integrates Convolutional Neural Networks (CNNs) with Long Short-Term Memory (LSTM) units was used to classify and differentiate the oils based on stability, thermal reactivity, and potential health benefits. A signal analysis showed that the AI-based method improves both the accuracy (achieving an F1-score of 93.66%) and the repeatability of quality assessments, providing a non-invasive and intelligent framework for the validation and traceability of nutritional compounds. Full article

Background and Objective: Temperature management is key for reliable operation of permanent magnet synchronous motors (PMSMs). The lumped-parameter thermal network (LPTN) is fast and interpretable but struggles with nonlinear behavior under high power density. We propose OLTEM, a physics-informed deep model that combines LPTN with a thermal neural network (TNN) to improve prediction accuracy while keeping physical meaning. Methods: OLTEM embeds LPTN into a recurrent state-space formulation and learns three parameter sets: thermal conductance, inverse thermal capacitance, and power loss. Two additions are introduced: (i) a state-conditioned squeeze-and-excitation (SC-SE) attention that adapts feature weights using the current temperature state, and (ii) an enhanced power-loss sub-network that uses a deep MLP with SC-SE and non-negativity constraints. The model is trained and evaluated on the public Electric Motor Temperature dataset (Paderborn University/Kaggle). Performance is measured by mean squared error (MSE) and maximum absolute error across permanent-magnet, stator-yoke, stator-tooth, and stator-winding temperatures. Results: OLTEM tracks fast thermal transients and yields lower MSE than both the baseline TNN and a CNN–RNN model for all four components. On a held-out generalization set, MSE remains below 4.0 °C² and the maximum absolute error is about 4.3–8.2 °C. Ablation shows that removing either SC-SE or the enhanced power-loss module degrades accuracy, confirming their complementary roles. Conclusions: By combining physics with learned attention and loss modeling, OLTEM improves PMSM temperature prediction while preserving interpretability. This approach can support motor thermal design and control; future work will study transfer to other machines and further reduce short-term errors during abrupt operating changes. Full article

Ground temperature (GT) variation significantly affects the energy performance of ground source heat pump (GSHP) systems. Both long-term thermal accumulation and short-term dynamic responses contribute to the degradation of the coefficient of performance (COP), especially under cooling-dominated conditions. This study develops a mechanism-based TRNSYS simulation that integrates building loads, subsurface heat transfer, and dynamic heat pump operation. A 20-year case study in Shanghai reveals long-term performance degradation driven by thermal boundary shifts. Results show that GT increases by over 12 °C during the simulation period, accompanied by a progressive increase in ΔT by approximately 0.20 K and a consistent decline in COP. A near-linear inverse relationship is observed, with COP decreasing by approximately 0.038 for every 1 °C increase in GT. In addition, ΔT is identified as a key intermediary linking subsurface thermal disturbance to efficiency loss. A multi-scale response framework is established to capture both annual degradation and daily operational shifts along the Load–GT–ΔT–COP pathway. This study provides a quantitative explanation of the thermal degradation process and offers theoretical guidance for performance forecasting, operational threshold design, and thermal regulation in GSHP systems. Full article

Iraq’s extreme summer temperatures pose critical challenges to pavement durability, as conventional asphalt mixtures often fail under prolonged thermal stress. This paper provides a comparative evaluation of the high-temperature performance of unmodified (40/50 penetration grade) and polymer-modified (PG 76-10) asphalt mixtures for the asphalt course layer. Marshall stability, flow, and stiffness were measured at elevated temperatures of 60 °C, 65 °C, 70 °C, and 75 °C after short-term (30 min) and extended (24 h) conditioning. Results show that while both mixtures experienced performance degradation as the temperature increased, the polymer-modified mixture consistently exhibited superior thermal resistance, retaining approximately 9% higher stability and 28% higher stiffness, and displaying 18% lower flow deformation at 75 °C compared to the unmodified mixture. Stability degradation rate (SDR), stiffness degradation rate (SiDR), and flow increase rate (FIR) analyses further confirmed the enhanced resilience of PG 76-10, showing nearly 39% lower FIR under thermal stress. Importantly, PG 76-10 maintained performance within specification thresholds under all tested conditions, unlike the conventional 40/50 mixture. These findings emphasize the necessity of adapting mix design standards to regional climatic realities and support the broader adoption of polymer-modified asphalt binders to enhance pavement service life in hot-climate regions like Iraq. Full article

The load spectrum serves as the foundation for the life analysis of aero-engine turbine disks. To enhance the accuracy of life assessments for turbine disks, this study compiles a time-varying load spectrum for turbine disks. Firstly, a surrogate model for transient processes at the critical points of turbine disks is established, enabling the rapid evaluation of the transient temperature and thermal stress at these points under complex loading histories. Secondly, a performance degradation model is established based on real engine test data, explicitly describing the general trend of performance degradation characteristics with respect to the cycle number and engine power. Finally, a time-varying load spectrum for turbine disks is compiled, considering both short-term transient processes and long-term performance degradation. The life of turbine disks at the fir-tree slot root and disk bore is assessed using the Manson–Coffin equation, Wilshire equation, and linear damage accumulation rule. The results indicate that neglecting transient processes leads to conservative life assessment results while neglecting performance degradation leads to dangerous life assessment results. Compared with traditional methods, the time-varying load spectrum significantly improves the accuracy and scientific nature of turbine disk life assessment. Full article

This study focuses on the internal temperature field of lithium-ion batteries, aiming to address the temperature variation issues arising from complex operating conditions in new energy batteries. To cope with unpredictable temperature fluctuations and long delay times, we propose an enhanced Convolutional Bidirectional Long Short-Term Memory Neural Network (CNN-Bi-LSTM-AM) model for temperature field prediction. The model integrates CNN for spatial feature extraction, Bi-LSTM for capturing temporal characteristics, and an attention mechanism to enhance the identification of key time-series features. By simulating temperature variations through a lumped model and thermal runaway model, we generate temperature field data, which are then utilized by the deep learning model to effectively capture the complex nonlinear relationships between temperature, voltage, state of charge (SOC), insulation resistance, current, and the internal temperature field. Performance evaluation using accuracy metrics and validation under various environmental conditions demonstrates that the model improves prediction accuracy by 1.2–2.3% compared to traditional methods (e.g., ARIMA, LSTM) with only a slight increase in testing time. Comprehensive evaluations, including ablation studies, thermal runaway tests, and computational efficiency analysis, further validate the robustness and applicability of the model. Furthermore, this study contributes to the optimization of battery life and safety by enhancing the prediction accuracy of the internal temperature field, thereby reducing resource waste caused by battery performance degradation. The findings provide an innovative approach to advancing new energy battery technology, promoting its development toward greater safety, stability, and environmental sustainability, which aligns with global sustainable development goals. Full article

2-acrylamido-2-methylpropane sulfonic acid (AMPS) based copolymer fluid loss agent is a kind of widely utilized additive in oil-well cement. However, when applied in ultra-high temperature (UHT) formation environment, its fluid loss control efficiency is significantly declined due to the thermal degradation behavior, and corresponding mechanism study is still lacking. Regarding the above issue, this work synthesized one representative copolymer fluid loss agent PADIM and investigated its thermal degradation mechanism in UHT aqueous environment, which was polymerized by AMPS, N, N-dimethylacrylamide (DMAA), itaconic acid (IA) and methacryloxyethyltrimethyl ammonium chloride (MTC). The aim of this paper was to provide a theoretical guidance for the futural structural design of the fluid loss agents for oil well cement slurry at UHTs. The copolymer solution was subjected to isothermal aging at 180–240 °C for 1.5 h or 6.0 h (to simulate short-period and long-period aging, respectively), and the aged products were further analyzed. It was found that the thermal decomposition onset temperature of the copolymer solid was 294.6 °C. However, its thermal stability in aqueous solution was significantly lower, with substantial main chain breakage and functional group transformations occurring below 240 °C. As a result, the apparent viscosity and average molecular weight were significantly reduced from 4216 mPa·s and 31,666 Da before aging to 107.4 mPa·s and 8590 Da after aging at 240 °C for 6.0 h. Meanwhile, the side groups (-SO₃⁻ and -COO⁻) were removed and the unsaturated alkenes were produced due to main chain degradation. In terms of application performance, the fluid loss control ability of the aged product diminished gradually from 22 mL to 196 mL as the aging temperature increased from room temperature to 210 °C. This decline was attributed to a reduction in molecular weight and a decrease in product adsorption capacity caused by the removal of side groups. Full article

Polyamide-based glass fibre-reinforced composites are extensively used in electrical and automotive applications due to their excellent mechanical, thermal, and electrical properties. However, prolonged exposure to high temperatures can lead to significant degradation, affecting their long-term performance and reliability. This study investigates the thermal ageing behaviour of polyamide 6,6 composites containing halogenated flame retardants used for electrical applications. The objective of this research is to evaluate the extent of degradation through accelerated ageing tests and to develop an Arrhenius-type ageing model to predict the long-term performance of these materials. This study examines the effects of thermal ageing at temperatures between 160 and 210 °C on flexural properties and explores the underlying degradation mechanisms. Results indicate that short-term exposure to high temperatures can enhance flexural strength due to annealing effects, which are eventually outweighed by thermal oxidation and increased crystallinity, leading to an increase in brittleness. The derived Arrhenius model, with an activation energy of 93 kJ/mol, predicts a service life of approximately 25 years at 80 °C, but a significantly shorter one at 130 °C. These findings underscore the importance of considering thermal ageing effects in the design and application of PA66 composites in high-temperature environments. Full article

Hexagonal boron nitride (h-BN) has emerged as a promising dielectric material for protecting metallic substrates such as copper and steel under ambient conditions. The layered structure of h-BN offers significant potential in preventing the oxidation and corrosion of these substrates. Due to their impermeability, boron nitride nanosheets (BNNSs) do not form a galvanic cell with the underlying metals, enhancing their effectiveness as protective coatings. BNNSs are both thermally and chemically stable, making them suitable for coatings that protect against environmental degradation. Additionally, BNNSs have demonstrated excellent fire resistance, hydrophobicity, and oxidation resistance when applied to wood, functioning as a binder-free, retardant coating that remains effective up to 900 °C in air. This review focuses on the anti-corrosion properties of BNNSs, particularly on copper and steel substrates, and discusses various methods for their application. This article also discusses future perspectives in this field, including the innovative concept of wooden satellites designed for short- and long-term missions. Full article

In the present work, hybrid nanobiocomposites based on poly(3-hydroxybutyrate), P3HB, with the use of aromatic linear polyurethane as modifier and organic nanoclay, Cloisite 30B, as a nanofiller were produced. The aromatic linear polyurethane (PU) was synthesized in a reaction of diphenylmethane 4,4′-diisocyanate and polyethylene glycol with a molecular mass of 1000 g/mole. The obtained nanobiocomposites were characterized by the small-angle X-ray scattering technique, scanning electron microscopy, Fourier infrared spectroscopy, thermogravimetry, and differential scanning calorimetry, and moreover, their selected mechanical properties, biodegradability, and cytotoxicity were tested. The effect of the organomodified montmorillonite presence in the biocomposites on their properties was investigated and compared to those of the native P3HB and the P3HB-PU composition. The obtained hybrid nanobiocomposites have an exfoliated structure. The presence and content of Cloisite 30B influence the P3HB-PU composition’s properties, and 2 wt.% Cloisite 30B leads to the best improvement in the aforementioned properties. The obtained results indicate that the thermal stability and mechanical properties of P3HB were improved, particularly in terms of increasing the degradation temperature, reducing hardness, and increasing impact strength, which were also confirmed by the morphological analysis of these bionanocomposites. However, the presence of organomodified montmorillonite in the obtained polymer biocomposites decreased their biodegradability slightly. The produced hybrid polymer nanobiocomposites have tailored mechanical and thermal properties and processing conditions for their expected application in the production of biodegradable, short-lived products for agriculture. Moreover, in vitro studies on human skin fibroblasts and keratinocytes showed their satisfactory biocompatibility and low cytotoxicity, which make them safe when in contact with the human body, for instance, in biomedical applications. Full article

Cassava starch solid biopolymer electrolyte (SBPE) films were prepared by a thermochemical method with different concentrations of lithium triflate (LiTFT) as a dopant salt. The process began with dispersing cassava starch in water, followed by heating to facilitate gelatinization; subsequently, plasticizers and LiTFT were added at differing concentrations. The infrared spectroscopy analysis (FTIR-ATR) showed variations in the wavenumber of some characteristic bands of starch, thus evidencing the interaction between the LiTFT salt and biopolymeric matrix. The short-range crystallinity index, determined by the ratio of COH to COC bands, exhibited the highest crystallinity in the salt-free SBPEs and the lowest in the SBPEs with a concentration ratio (Xm) of 0.17. The thermogravimetric analysis demonstrated that the salt addition increased the dehydration process temperature by 5 °C. Additionally, the thermal decomposition processes were shown at lower temperatures after the addition of the LiTFT salt into the SBPEs. The differential scanning calorimetry showed that the addition of the salt affected the endothermic process related to the degradation of the packing of the starch molecules, which occurred at 70 °C in the salt-free SBPEs and at lower temperatures (2 or 3 °C less) in the films that contained the LiTFT salt at different concentrations. The cyclic voltammetry analysis of the SBPE films identified the redox processes of the glucose units in all the samples, with observed differences in peak potentials (Ep) and peak currents (Ip) across various salt concentrations. Electrochemical impedance spectroscopy was used to establish the equivalent circuit model Rf–(Cdl/(Rct–(CPE/Rre))) and determine the electrochemical parameters, revealing a higher conduction value of 2.72 × 10⁻³ S cm⁻¹ for the SBPEs with Xm = 17 and a lower conduction of 5.80 × 10⁻⁴ S cm⁻¹ in the salt-free SBPEs. It was concluded that the concentration of LiTFT salt in the cassava starch SBPE films influences their morphology and slightly reduces their thermal stability. Furthermore, the electrochemical behavior is affected in terms of variations in the redox potentials of the glucose units of the biopolymer and in their ionic conductivity. Full article

This study explores the enhancement of silicon-based solar cell performance and durability through the application of zinc oxide (ZnO) nanocomposite film coatings. Utilizing the sol–gel method, ZnO nanorods were synthesized and dispersed within a polyvinyl butyral (PVB) matrix, resulting in uniform nanocomposite films. Comprehensive characterization using X-ray Diffraction (XRD), Fourier-Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), UV-Visible spectroscopy, and contact angle measurements confirmed the effective integration and desirable properties of ZnO within the PVB matrix. The ZnO coatings demonstrated superior UV absorptivity, significantly blocking UV radiation at 355 nm while maintaining high transparency in the visible range. This led to improvements in key photovoltaic parameters, including short circuit current (J_sc), open-circuit voltage (V_oc), efficiency (η), and fill factor (FF). Although a minor reduction in Isc was observed due to the ZnO layer’s influence on the light absorption spectrum, the overall efficiency and fill factor experienced notable enhancements. Furthermore, the thermal load on the solar cells was effectively reduced, mitigating UV-induced degradation and thereby prolonging the operational lifespan of the solar panels. Under damp heat conditions, the coated solar panels exhibited remarkable durability compared to their uncoated counterparts, underscoring the protective advantages of ZnO films. These findings highlight the potential of ZnO nanocomposite coatings to significantly boost the efficiency, reliability, and longevity of silicon-based solar panels, making them more viable for long-term deployment in diverse environmental conditions. Full article

Electric vehicles can reduce the dependence on limited resources such as oil, which is conducive to the development of clean energy. An accurate battery state of health (SOH) is beneficial for the safety of electric vehicles. A multi-feature and Convolutional Neural Network–Bidirectional Long Short-Term Memory–Multi-head Attention (CNN-BiLSTM-MHA)-based lithium-ion battery SOH estimation method is proposed in this paper. First, the voltage, energy, and temperature data of the battery in the constant current charging phase are measured. Then, based on the voltage and energy data, the incremental energy analysis (IEA) is performed to calculate the incremental energy (IE) curve. The IE curve features including IE, peak value, average value, and standard deviation are extracted and combined with the thermal features of the battery to form a complete multi-feature sequence. A CNN-BiLSTM-MHA model is set up to map the features to the battery SOH. Experiments were conducted using batteries with different charging currents, and the results showed that even if the nonlinearity of battery SOH degradation is significant, this method can still achieve a fast and accurate estimation of the battery SOH. The Mean Absolute Error (MAE) is 0.1982%, 0.1873%, 0.1652%, and 0.1968%, and the Root-Mean-Square Error (RMSE) is 0.2921%, 0.2997%, 0.2130%, and 0.2625%, respectively. The average Coefficient of Determination (R²) is above 96%. Compared to the BiLSTM model, the training time is reduced by an average of about 36%. Full article

High-viscosity modified asphalt binder (HVMA) is used widely as a polymer-modified binder in porous asphalt pavement because it can improve the cohesiveness of the asphalt mixture. However, because of the high voidage in the mixture, HVMA is vulnerable to aging induced by temperature, oxygen, water, sunlight, and other climatic conditions, which degrades the performance of pavement. The properties of asphalt binder are affected adversely by the effects of hygrothermal environments in megathermal and rainy areas. Therefore, it is essential to study the aging characteristics of HVMA under the influence of hygrothermal environments to promote its application as a high-viscosity modifier. A hygrothermal cycle aging test (HCAT) was designed to simulate the aging of HVMA when rainwater was kept inside of the pavement after rainfall in megathermal areas. One kind of base bitumen and three kinds of HVMA (referred to as SBS, A, and B, respectively) were selected in this study. Short-term aging tests, hygrothermal cycling aging tests, and long-term aging tests were performed on the base bitumen and three kinds of modified asphalt binder. Fourier-transform infrared spectroscopy (FTIR), thermo-gravimetric analysis (TGA), and dynamic shear rheological (DSR) tests were used to evaluate the properties of the binders on the micro and macro scales. By comparing the index variations of the four binders before and after aging, the effects of the hygrothermal environment on the properties of HVMA were studied. It was found that the effects of the hygrothermal environment expedited the decomposition of the polymer and the formation of carbonyl groups compared with the TFOT and PAV test, which TGA confirmed further. Moreover, the thermal stability of the samples was improved after HCAT. In addition, the master curves of the complex modulus showed that hygrothermal cycles made the high-temperature rutting resistance of asphalt binder increase significantly. All of the results above verified that the effect of hygrothermal cycling could accelerate the aging of HVMA and shorten its service life. Full article

Polymer biocompositions of poly(3-hydroxybutyrate) (P3HB) and linear polyurethanes (PU) with aromatic rings were produced by melt-blending at different P3HB/PU weight ratios (100/0, 95/5, 90/10, and 85/15). Polyurethanes have been prepared with 4,4′-diphenylmethane diisocyanate and polyethylene glycols with molar masses of 400 g/mol (PU400), 1000g/mol (PU1000), and 1500 g/mol (PU1500). The compatibility and morphology of the obtained polymer blends were determined by infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and differential scanning calorimetry (DSC). The effect of the polyurethane content in the biocompositions on their thermal stability and mechanical properties was investigated and compared with those of the native P3HB. It was shown that increasing the PU content in P3HB-PU compositions to 10 wt.% leads to an improvement in the mentioned properties. The obtained results demonstrated that the thermal stability and mechanical properties of P3HB were improved, particularly in terms of increasing the degradation temperature, reducing hardness, and increasing impact strength. The best thermal and mechanical properties were shown by the P3HB-PU polymer compositions containing 10 wt.% of polyurethane modifiers, especially PU1000, which was also confirmed by the morphology analysis of these biocompositions. The presence of polyurethanes in the resulting polymer biocomposites decreases their glass transition temperatures, i.e., makes the materials more flexible. The resulting polymer biocompositions have suitable mechanical properties and thermal properties within the processing conditions for the predicted application as biodegradable, short-lived products for agriculture. Full article