Search Results (4,093)

Fiber-reinforced polymer (FRP) composites are increasingly used in civil, marine, offshore, and energy infrastructure, where components routinely experience temperatures above ambient conditions. While the design of these components is largely driven by fiber-dominated characteristics, the deterioration of shear properties can lead to premature weakening and even failure. Thus, the performance and reliability of these systems depend intrinsically on the response of interlaminar shear characteristics, in-plane shear characteristics, and flexure-based shear characteristics to thermal loads ranging from uniform and monotonically increasing to cyclic and spike exposures. This paper presents a critical review of current knowledge of shear response in the presence of thermal exposure, with emphasis on temperature regimes that are below T_g in the vicinity of T_g and approaching T_d. Results show that thermal exposures cause matrix softening and microcracking, interphase degradation, and thermally induced residual stress redistribution that significantly reduces shear-based performance. Cyclic and short-duration spike/flash exposures result in accelerated damage through thermal fatigue; steep thermal gradients, including through the thickness; and localized interfacial failure loading to the onset of delamination or interlayer separation. Aspects such as layup/ply orientation, fiber volume fraction, degree of cure, and the availability and permeation of oxygen through the thickness can have significant effects. The review identifies key contradictions and ambiguities, pinpoints and prioritizes areas of critically needed research, and emphasizes the need for the development of true mechanistic models capable of predicting changes in shear performance characteristics over a range of thermal loading regimes. Full article

High-temperature operation of AlGaN/GaN Heterojunction Field Effect Transistor embedded diaphragm-based MEMS pressure sensors have been investigated, which utilized their wide bandgap and piezo resistivity to perform stably at elevated temperatures. The performance of the pressure sensor was observed over a change in applied pressure of 35 kPa, which resulted in an experimentally measured change in drain–source resistance (ΔR_DS/R_DS(0)) of 0.32% at room temperature and 0.65% at 250 °C, respectively. Additionally, the COMSOL-based Finite Element (FE) Simulations, in conjunction with our developed theoretical model, was utilized to theoretically determine the change in drain–source resistance. This theoretically calculated ΔR_DS/R_DS(0) of 0.45% at room temperature closely aligns with the experimental observations. Moreover, the sensor exhibited a gate-bias-dependent tunability, with the enhancement of sensitivity under increasingly negative gate voltages. Furthermore, the sensors demonstrated a stable and repeatable sensing operation over multiple pressure cycles up to 300 °C, with a rapid response time of <10 ms, suggesting excellent potential for reliable, high-performance pressure sensing in harsh, high-temperature environments. Full article

Carbon capture and storage (CCS) is essential for achieving net-zero emissions, yet amine-based capture systems face significant challenges including high energy penalties (20–30% of power plant output) and operational costs ($50–120/tonne CO${}_2$). This study develops and validates a novel multi-scale Digital Twin (DT) framework integrating Physics-Informed Neural Networks (PINNs) to address these challenges through real-time optimization. The framework combines molecular dynamics, process simulation, computational fluid dynamics, and deep learning to enable real-time predictive control. A key innovation is the sequential training algorithm with domain decomposition, specifically designed to handle the nonlinear transport equations governing CO${}_2$ absorption with enhanced convergence properties.The algorithm achieves prediction errors below 1% for key process variables (R${}^2$> 0.98) when validated against CFD simulations across 500 test cases. Experimental validation against pilot-scale absorber data (12 m packing, 30 wt% MEA) confirms good agreement with measured profiles, including temperature (RMSE = 1.2 K), CO${}_2$ loading (RMSE = 0.015 mol/mol), and capture efficiency (RMSE = 0.6%). The trained surrogate enables computational speedups of up to four orders of magnitude, supporting real-time inference with response times below 100 ms suitable for closed-loop control. Under the conditions studied, the framework demonstrates reboiler duty reductions of 18.5% and operational cost reductions of approximately 31%. Sensitivity analysis identifies liquid-to-gas ratio and MEA concentration as the most influential parameters, with mechanistic explanations linking these to mass transfer enhancement and reaction kinetics. Techno-economic assessment indicates favorable investment metrics, though results depend on site-specific factors. The framework architecture is designed for extensibility to alternative solvent systems, with future work planned for industrial-scale validation and uncertainty quantification through Bayesian approaches. Full article

The flow behavior of fluids can be characterized by rheology and is especially used in the field of polymeric materials. This study focused on characterizing cerebrospinal fluid (CSF) of patients who developed hydrocephalus after subarachnoid hemorrhage (SAH) with rheology. Samples were drawn from an external ventricular drainage (EVD) at four pre-defined time points after the initial hemorrhage. The CSF samples were analyzed using a rotational rheometer with a double gap geometry. In addition to the characterization of viscoelastic parameters, the cumulative storage factor was calculated to determine the interactions in the fluid. In order to investigate the temperature dependence of the CSF properties, the oscillatory measurements were implemented at certain temperatures that simulated specific conditions, such as 5 °C, at which temperature the CSF samples were stored; 35 °C for hypothermic conditions; 37 °C for physiologic conditions; and 40 °C for elevated body temperature. The overall goal was to evaluate whether rheology-based parameters may help in the prediction of shunt dependence for post-hemorrhagic hydrocephalus patients. For this aim, rheological parameters were correlated to certain laboratory parameters, such as erythrocyte and leukocyte count, glucose, lactate, and total protein concentration. Full article

The discharge of dye-contaminated effluents from textile industries into water bodies poses a severe threat to aquatic ecosystems and human health. To address this challenge, cellulose and interpenetrating polymer network (IPN) hydrogels based on cellulose and poly(vinyl alcohol) (PVA) were developed via an in situ synthesis method. The cellulose solution was obtained by cold dissolving the polysaccharide in NaOH, then dissolving PVA. The IPN hydrogels were obtained by co-cross-linking the two polymers in an alkaline medium using ECH. To optimize the hydrogels, synthesis parameters like time (4–7 h), temperature (50–80 °C), and cross-linking ratio (ECH = 50–125% w/w) were varied. Different hydrogel compositions (Cel/PVA = 90/10 to 60/40 w/w) were tested for their absorption efficiency in removing Tubantin Blue (DB 78) dye under varying initial concentrations and temperatures. Hydrogels exhibit varying adsorption capacities for DB78, depending on their IPN composition, synthesis parameters, and dye concentration. Specifically, IPN adsorption capacity ranges from 8.8 to 38.1 mg DB78/g hydrogel (7.5–36.2% efficiency). At high effluent concentrations, IPN can reach a retention capacity of 217.7 mg/g, achieving a retention efficiency of 58.4%. Cellulose and cellulose/PVA IPN hydrogels show promise as sustainable adsorbents for treating dye-contaminated wastewater. Full article

Cutaneous leishmaniasis (CL) is a neglected tropical disease for which current chemotherapeutic options are limited by systemic toxicity (such as hepato-nephrotoxicity, arrhythmia, nausea, vomiting) and difficult administration regimens. Pentamidine (PTM), although effective, exhibits severe dose-limiting adverse effects. Polymeric micelles based on Pluronic^® F127 (F127) offer an attractive strategy to improve PTM delivery by enhancing solubility, reducing cytotoxicity, and enabling controlled release. Here, we developed PTM-loaded F127 polymeric micelles and performed a multidisciplinary evaluation combining physicochemical characterization, in vitro biological assays, and gene expression profiling. Dynamic light scattering, UV–visible absorption, fluorescence spectroscopy, and NMR confirmed micelle formation, PTM–polymer interactions, and temperature-dependent assembly. PTM-loaded micelles exhibited biorelevant nanoscale dimensions and preserved stability under physiological conditions. Biological assays demonstrated that F127 micelles markedly reduced PTM cytotoxicity in RAW264.7 macrophages while maintaining potent antileishmanial activity against Leishmania major promastigotes. RT-qPCR analysis revealed modulation of key pathways involved in redox homeostasis, oxidative stress, calcium regulation, apoptosis-like responses, and drug resistance, suggesting that micellar encapsulation influences both PTM bioavailability and parasite stress responses. Overall, PTM-loaded F127 micelles significantly improved the therapeutic index of PTM in vitro. These findings support the potential of F127 polymeric micelles as a promising nanocarrier platform for safer and more effective CL therapy. Full article

Basic fibroblast growth factor (bFGF) and Transforming growth factor-beta (TGF-β) are key regulators of human pluripotent stem cell (hPSC) maintenance, supporting pluripotency and self-renewal. bFGF is particularly critical for sustaining the undifferentiated state and is commonly supplied through feeder-derived conditioned media. Similarly, TGF-β promotes hPSC expansion by modulating signaling pathways and contributing to a supportive stem cell niche. In this study, we investigated how the quality and variability of these growth factors influence hPSC culture performance. To address this, we developed and applied multiple physicochemical characterization methods—including size exclusion and reverse-phase chromatography—to assess growth factor purity and identify impurities across different material sources. Our findings show that certain post-translational modifications in TGF-β (e.g., oxidized variants) did not measurably affect hPSC culture. However, high temperature-dependent instability of bFGF preparations significantly altered hPSC morphology and growth. These findings underscore the need for improved quality control of growth factor components in culture media to ensure consistent hPSC maintenance, thus decreasing variability across experiments. This study highlights the value of correlating analytical physicochemical data with process performance, thereby advancing material understanding, enabling more efficient process development, and facilitating the identification of critical material attributes that affect the quality of cell therapy products. Full article

Cryopreservation is a critical strategy for the long-term conservation of plant germplasm, particularly for clonally propagated crops, endangered species, and plants producing recalcitrant seeds. Hydrogel-based encapsulation systems can improve survival during ultra-low-temperature storage by providing mechanical protection, moderating dehydration, and regulating cryoprotectant uptake. Although calcium–alginate beads remain the traditional matrix for encapsulation–dehydration and encapsulation–vitrification, recent advances in biomaterials science have enabled the development of composite polysaccharide blends, protein-based matrices, synthetic polymer networks, macroporous cryogels, and functionalized hybrid hydrogels incorporating surfactants, antioxidants, or nanomaterials. These engineered systems provide improved control over water state, pore architecture, diffusion kinetics, and thermal behavior, thereby reducing cryoinjury and enhancing post-thaw recovery across diverse plant explants. This review synthesizes current knowledge on hydrogel platforms used in plant cryopreservation, with emphasis on how physicochemical properties influence dehydration dynamics, cryoprotectant transport, vitrification stability, and rewarming responses. Performance across major explant types is assessed, key limitations in existing materials and protocols are identified, and design principles for next-generation hydrogel systems are outlined. Future progress will depend on material standardization, integration with automated cryopreservation workflows, and the development of responsive hydrogel matrices capable of mitigating cryogenic stresses. Full article

To ensure food security, integrated mulching and irrigation practices are widely used in arid maize fields. Mitigating climate change is vital for sustainable agricultural development. Yet, few studies have examined how different mulching and irrigation methods affect farmland carbon fluxes, particularly with maize variety shifts under policy guidance. In this study, we conducted experimental observations over five growing seasons using eddy covariance systems in maize fields (including seed maize fields and grain maize fields), where drip irrigation under plastic mulch (DM) and border irrigation under plastic mulch (BM) were employed in Northwest China. Results revealed that the multi-year mean gross primary productivity (GPP), net ecosystem productivity (NEP), and ecosystem respiration (ER) in maize fields under DM were 16.70%, 15.63% and 17.52% higher than those under BM, respectively. The changes in cumulative GPP, cumulative NEP and cumulative ER caused by the alteration of maize varieties were 7.64, 13.34 and 4.20 times, respectively, compared to the changes caused by the irrigation method. After mechanical harvesting, net biome productivity (NBP) was negative in seed maize fields but positive in grain maize fields. However, after the straws were returned to the fields, the NBP of both types of maize fields became positive. Interestingly, the carbon fluxes of seed maize and grain maize, respectively, exhibit strong dependence on soil temperature and leaf area index. Our study will provide important insights for the green and sustainable development of agriculture and the advancement of ecosystem models. Full article

Extrusion processing can induce gel-like network formation in plant proteins, enabling the advancement of structured meat alternatives with tailored textural properties. In this study, extrusion-induced gelation behavior of isolated mung bean protein (IMBP) was systematically investigated during the manufacture of low-moisture meat analogs (LMMA). The effects of key processing variables, rotational speed of the screw, moisture level, and processing temperature on gel network development, hydration behavior, and textural responses were evaluated using response surface methodology as an analytical framework. Increasing moisture content promoted protein hydration and facilitated the formation of continuous gel-like interactions, resulting in enhanced pore development and water-holding capacity. Variations in screw speed and processing temperature further modulated the extent of protein denaturation and network consolidation, influencing nitrogen solubility and mechanical properties. While the integrity index remained relatively insensitive to processing conditions, structural and functional responses exhibited clear dependencies on extrusion-induced gelation dynamics. The extrusion conditions of 39% moisture, 216 rpm, and 159 °C promoted the development of a well-defined protein network, leading to improved functional properties. These findings provide mechanistic insight into extrusion-driven gelation of IMBP and highlight its potential as a protein matrix for gel-based meat analog applications. Full article

Climate change is altering temperature and precipitation regimes in Argentina, with potential consequences for regeneration and persistence of forest tree species, emphasizing the importance of ex situ seed conservation. We evaluated interannual variation in seed traits, desiccation tolerance, storage behavior, and longevity of Cedrela balansae C. DC. and C. fissilis Vell. (Meliaceae), two endangered native species of subtropical rainforests in Argentina. Both species produced desiccation-tolerant seeds, independently of collection year, seed traits, or climatic conditions. Depending on the species, seed traits and longevity varied across years and showed strong relationships with temperature and precipitation, particularly during seed development. Cedrela balansae seeds are medium-lived seeds and have high longevity under standard seed banking conditions, suggesting strong potential for long-term ex situ conservation. Cedrela fissilis seeds are short-lived seeds and have high sensitivity to the storage environment. Correlations among climatic variables and seed traits and longevity parameters suggest that future warming and drying environments may shorten the window for germination and seedling establishment, with species-specific responses depending on climatic conditions during seed development. These results highlight the importance of climate effects in determining seed traits and seed longevity and emphasize the role of seed banking as a critical conservation strategy under climate change. Full article

Reliable measurement of multiphase flow is fundamental to production evaluation in complex oil and gas wells. However, conventional sensors often suffer from low integration, limited measurement capability, and potential environmental impact. To address these challenges, a photoelectric composite three-phase flow sensor is developed, integrating multiple electrode rings for water holdup and liquid-phase velocity measurement, with dual optical-fiber probes for gas holdup and gas-phase velocity detection. A slip model is further applied to quantify the dependence of slip velocity on liquid holdup based on measured phase rates. Experimental results demonstrate high sensitivity to bubble-flow structures, accurate extraction of gas holdup and phase velocities, and stable full-range water holdup calibration from 0% to 100% at 5 V and 15 V with effective temperature and salinity compensation. And compared with existing technologies, the sensor designed in this paper has the advantages of high integration, a simple structure, multiple measurement parameters, and higher water-holding capacity resolution in low-saturation areas, providing more advanced technical means for conventional profile three-phase flow logging. Full article

This study aims to evaluate the robustness of the well proved Aungier meanline model, originally developed for air and steam turbines, on Organic Rankine Cycles (ORC) turbines. More specifically, the study focuses on two pure-impulse axial turbines with partial admission and using various working fluids, including zeotropic mixtures. To this end, a three-part numerical model was developed to adapt this type of meanline model to a prediction-oriented methodology rather than a design-oriented one. Using inlet and outlet pressures, inlet temperature, and rotational speed as inputs, the model provides the resulting mass flow rate through the turbine as well as its performance characteristics. The model predictions are compared against an extensive experimental dataset comprising more than 300 operating points obtained with three pure fluids—R1233zd(E), NOVEC™ 649, and HFE7000—and three zeotropic mixtures. The model demonstrates good predictive accuracy over a wide range of operating conditions, including very low velocity ratios corresponding to severe off-design operation. Specifically, the mass flow rate is predicted with a Mean Absolute Percentage Error (MAPE) ranging from 1.23% to 3.31%, depending on the working fluid. Furthermore, over an experimental specific work range of 5 to 15 kJ/kg, the predicted numerical work exhibits a MAPE of 7.04% for 102 experimental points corresponding to the main dataset (R1233zd(E)). Finally, the total-to-total efficiency is predicted within ±4 efficiency points, showing a very good trend over a velocity ratio range from 0.06 to 0.36. Full article

Camellia oleifera, a woody oil crop unique to China, plays a crucial role in alleviating the global pressure of edible oil supply and maintaining ecological security. However, it remains challenging to accurately forecast Camellia oleifera yield in complex landscapes using only remote sensing data. The aim of this study is to develop an interpretable deep learning model, namely Shapley Additive Explanations–guided Attention–long short-term memory (SALSTM), for estimating Camellia oleifera yield by integrating an improved spectral bloom index and environmental parameters. The study area is located in Hengyang City in Hunan Province. Sentinel-2 imagery, meteorological observation from 2019 to 2023, and topographic data were collected. First, an improved spectral bloom index (ISBI) was constructed as a proxy for flowering density, while average temperature, precipitation, accumulated temperature, and wind speed were selected to represent environmental regulation variables. Second, a SALSTM model was designed to capture temporal dynamics from multi-source inputs, in which the LSTM module extracts time-dependent information and an attention mechanism assigns time-step-wise weights. Feature-level importance derived from SHAP analysis was incorporated as a guiding prior to inform attention distribution across variable dimensions, thereby enhancing model transparency. Third, model performance was evaluated using root mean square error (RMSE) and coefficient of determination (R²). The result show that the constructed SALSTM model achieved strong predictive performance in predicting Camellia oleifera yield in Hengyang City (RMSE = 0.5738 t/ha, R² = 0.7943). Feature importance analysis results reveal that ISBI weight > 0.26, followed by average temperature and precipitation from flowering to fruit stages, these features are closely associated with C. oleifera yield. Spatially, high-yield zones were mainly concentrated in the central–southern hilly regions throughout 2019–2023, In contrast, low-yield zones were predominantly distributed in the northern and western mountainous areas. Temporally, yield hotspots exhibited a gradual increasing while low-yield zones showed mild fluctuations. This framework provides an effective and transferable approach for remote sensing-based yield estimation of flowering and fruit-bearing crops in complex landscapes. Full article

The mechanical response of geomembranes in hydraulic structures is strongly influenced by temperature variations, which alter both material stiffness and interface shear strength behavior. This study develops a non-linear, temperature-dependent tensile behavior constitutive model for a polyvinyl chloride (PVC) geomembrane and evaluates its implications for the stability of geomembrane-lined reservoir slopes. The empirical relationship was calibrated using tensile tests reported in literature for temperatures between 10 °C and 60 °C, reproducing the observed non-linear softening and modulus reduction with increasing temperature. A classical thermal dilation formulation was incorporated to simulate cyclic thermal expansion and contraction. The constitutive and thermal formulations were implemented in FLAC2D and applied to a 2H:1V covered geomembrane slope representative of dam lining systems. The results show that temperature-induced softening significantly increases tensile strain within the geomembrane. The model also shows that the lower surface interface friction angle of the geomembrane plays a significant role in the slope stability. Thermal cycle analysis demonstrates the accumulation of efforts resulting from the fatigue of the geomembrane. The proposed model provides a practical framework for incorporating thermo-mechanical coupling in design analyses and highlights the necessity of accounting for realistic thermal conditions in assessing the long-term stability of geomembrane-lined reservoirs. Full article