Search Results (2,263)

Large-scale wireless sensor networks with electric field energy harvesters (EFEHs) offer self-powered, eco-friendly, and scalable crop monitoring in hydroponic greenhouses. However, their practical adoption is limited by the low power density of current EFEHs, which restricts the reliable operation of external sensors. To address this challenge, this work presents a noninvasive EFEH assembled with hydroponic leafy vegetables that harvests electric field energy and estimates plant functional traits directly from the electrical response. The device operates through electrostatic induction produced by an external alternating electric field, which induces surface charge redistribution on the leaf. These charges are conducted through an external load, generating an AC voltage whose amplitude depends on the dielectric properties of the leaf. A low-voltage prototype was designed, built, and evaluated under controlled electric field conditions. Two representative species, Beta vulgaris (chard) and Lactuca sativa (lettuce), were electrically characterized by measuring the open-circuit voltage (VOC) and short-circuit current (ISC) of EFEHs. Three regression models were developed to determine the relationship between foliar moisture content (FMC) and fresh mass with electrical parameters. Empirical results disclose that the plant functional traits are critical predictors of the electrical output of EFEHs, achieving coefficients of determination of $R^2=0.697$ and $R^2=0.794$ for each species, respectively. These findings demonstrate that EFEHs can serve as self-powered, noninvasive indicators of plant physiological state in living leafy vegetable crops. Full article

Background and Objectives: Osteoporosis is a prevalent skeletal disorder characterized by decreased bone mass and compromised bone microarchitecture, leading to an elevated risk of fractures and significant morbidity, particularly among aging populations. Early diagnosis and personalized management are critical to reducing fracture incidence and associated healthcare burdens. Recent advances in artificial intelligence (AI) and machine learning (ML) have led to potential improvements in enhancing osteoporosis care by enabling accurate diagnostic imaging analysis, robust fracture risk prediction, and personalized therapeutic strategies. Materials and Methods: We performed a narrative review to summarize and critically evaluate the current literature on AI and ML applications in osteoporosis diagnosis and management. We searched relevant literature from inception to January 2025 to provide a comprehensive perspective, focusing on key themes, methodological approaches, and clinical implications. Results: Deep learning models, especially convolutional neural networks, facilitate rapid and accurate bone mineral density assessment from routine radiographs, expanding screening capabilities beyond conventional dual-energy X-ray absorptiometry (DXA). Machine learning algorithms harness clinical and demographic data to generate fracture risk models that often outperform traditional tools, enabling timely identification of high-risk individuals. Furthermore, AI-driven analyses of historical treatment responses coupled with real-time monitoring through wearable technologies and mobile applications allow for personalized therapeutic optimization and enhance patient engagement. Despite these promising advances, challenges remain regarding ethical considerations, data privacy, legal liability, incomplete model validation, lack of standardization, and the need for critical appraisal of real-world clinical efficacy for widespread clinical adoption. Conclusions: This narrative review indicates that AI and ML hold significant promise to revolutionize osteoporosis management by enabling early detection, precise risk stratification, and tailored interventions. However, the current evidence is heterogeneous, often lacking robust external validation and quantitative synthesis. Critical gaps include insufficient evaluation of model robustness across diverse populations, discussion of negative or conflicting results, and a comprehensive assessment of the limitations inherent in current AI evidence. Strategic efforts to validate, regulate, and critically integrate these technologies into routine clinical workflows are essential to realize their full potential and address the growing burden of osteoporosis worldwide. Full article

Wildfires are becoming more frequent in Central Europe, raising questions about the mechanical and chemical integrity of fire-affected conifer wood. Because commercial species such as silver fir (Abies alba), Norway spruce (Picea abies), and Scots pine (Pinus sylvestris) are not evolutionarily adapted to fire, their thermo-mechanical response remains poorly quantified. This study investigates oven-dry density, static bending strength, compressive strength parallel to the grain, Brinell hardness, chemical composition, elemental composition, and heat of combustion of wood collected from a recent post-fire stand in Poland. Fire exposure resulted in a slight reduction in oven-dry density, while compressive and bending strengths increased relative to reported reference values, likely due to moisture depletion and partial thermal modification of cell-wall polymers. Chemical analyses showed moderate thermally induced shifts, including higher lignin and carbon content with depth, consistent with progressive carbonization of the affected tissues. Although surface-affected wood retained measurable mechanical capacity and energy value, its structural applicability remains constrained by potential brittleness and the limited sampling depth. These findings provide essential baseline data for evaluating post-fire conifer wood and its potential use in low-grade material and bioenergy applications. Full article

Cryogenic Energy Storage (CES) has emerged as a promising solution for large-scale and long-duration energy storage, offering high energy density, zero local emissions, and compatibility with intermittent renewable energy sources. This systematic review critically examines recent advances in the numerical modeling of CES systems, with the objective of identifying prevailing methodologies, emerging trends, and existing research gaps. The studies analyzed are classified into three main categories: global thermodynamic modeling, simulation of specific components, and transient dynamic modeling. The findings highlight the continued use of thermodynamic models due to their simplicity and computational efficiency, alongside a growing reliance on high-fidelity CFD and transient models for more realistic operational analyses. A clear trend is also observed toward hybrid approaches, which integrate deterministic modeling with machine learning techniques and response surface methodologies to enhance predictive accuracy and computational performance. Nevertheless, significant challenges persist, including the absence of multiscale integrative models, the scarcity of high-resolution experimental data under transient conditions, and the limited consideration of operational uncertainties and material degradation. It is concluded that the development of integrated numerical frameworks will be critical to advancing the technological maturity of CES systems and ensuring their robust deployment in real-world energy transition scenarios. Additionally, the review also discusses local thermal non-equilibrium (LTNE) conditions, the influence of geometric and operational parameters, and the role of multidimensional and multi-region modeling in predicting thermal and exergy performance of packed-bed TES within LAES cycles. Full article

Distributed fiber-optic photoacoustic non-destructive testing (DFP-NDT) represents a paradigm shift from passive sensing to active probing, fundamentally transforming structural health monitoring through integrated fiber-based ultrasonic generation and detection capabilities. This review systematically examines DFP-NDT’s evolution by following the technology’s natural progression from fundamental principles to practical implementations. Unlike conventional approaches that require external excitation mechanisms, DFP-NDT leverages photoacoustic transducers as integrated active components where fiber-optical devices themselves generate and detect ultrasonic waves. Central to this technology are photoacoustic materials engineered to maximize conversion efficiency—from carbon nanotube-polymer composites achieving 2.74 × 10⁻² conversion efficiency to innovative MXene-based systems that combine high photothermal conversion with structural protection functionality. These materials operate within sophisticated microstructural frameworks—including tilted fiber Bragg gratings, collapsed photonic crystal fibers, and functionalized polymer coatings—that enable precise control over optical-to-thermal-to-acoustic energy conversion. Six primary distributed fiber-optic photoacoustic transducer array (DFOPTA) methodologies have been developed to transform single-point transducers into multiplexed systems, with low-frequency variants significantly extending penetration capability while maintaining high spatial resolution. Recent advances in imaging algorithms have particular emphasis on techniques specifically adapted for distributed photoacoustic data, including innovative computational frameworks that overcome traditional algorithmic limitations through sophisticated statistical modeling. Documented applications demonstrate DFP-NDT’s exceptional versatility across structural monitoring scenarios, achieving impressive performance metrics including 90 × 54 cm² coverage areas, sub-millimeter resolution, and robust operation under complex multimodal interference conditions. Despite these advances, key challenges remain in scaling multiplexing density, expanding operational robustness for extreme environments, and developing algorithms specifically optimized for simultaneous multi-source excitation. This review establishes a clear roadmap for future development where enhanced multiplexed architectures, domain-specific material innovations, and purpose-built computational frameworks will transition DFP-NDT from promising laboratory demonstrations to deployable industrial solutions for comprehensive structural integrity assessment. Full article

Intermetallic Fe₃Al-based alloys reinforced with Laves-phase precipitates are emerging as potential replacements for conventional high-alloy steels and possibly polycrystalline Ni-based superalloys in structural applications up to 700 °C. Their impressive mechanical properties, however, are offset by limited fabricability and poor machinability due to their severe brittleness. High tool wear during finish-machining, which is still required for components such as turbine blades, remains a key barrier to their broader adoption. In contrast to conventional manufacturing routes, additive manufacturing offers a viable solution by enabling near-net-shape manufacturing of difficult-to-machine iron aluminides. In the present study, laser powder bed fusion was used to produce an Fe-25Al-1.5Ta intermetallic containing strengthening Laves-phase precipitates, and the porosity, microstructure and phase composition were characterized as a function of the process parameters. The results showed that preheating the build plate to 650 °C effectively suppressed delamination and macrocrack formation, even though noticeable cracking still occurred at the high scan speed of 1000 mm/s. X-ray tomography revealed that samples fabricated with a lower scan speed (500 mm/s) and a higher layer thickness (0.1 mm) contained larger, irregularly shaped pores, whereas specimens printed at the same volumetric energy density (40 J/mm³) but with different parameter sets exhibited smaller fractions of predominantly spherical pores. All samples contained mostly elongated grains that were either oriented close to <001> relative to the build direction or largely texture-free. X-ray diffraction confirmed the presence of Fe₃Al and C14-type (Fe, Al)₂Ta Laves phase in all samples. Hardness values fell within a narrow range (378–398 HV10), with only a slight reduction in the specimen exhibiting higher porosity. Full article

Silicon-graphite anodes offer a practical route to increase the energy density of lithium-ion batteries (LIBs), but their widespread adoption is hampered by cyclic instability due to huge volume changes of silicon during lithiation/delithiation process. Another fallout of LIBs capacity gain is growing safety concerns due to fire risks, associated with the uncontrolled release of chemical energy. Herein, we test a hexakis(fluoroethoxy)phosphazene (HFEPN) as a multifunctional electrolyte additive designed to mitigate both issues. The flammability of HFEPN-containing electrolytes was evaluated using a self-extinguishing time test, while the electrochemical performance was assessed in Si/C composite||NMC pouch cells under a progressively accelerated cycling protocol. It is shown that the additive fully imparts flame-retardant properties to the electrolyte at a 15 wt% loading. Despite forming a more stable solid–electrolyte interphase (SEI) with enhanced interfacial kinetics the additive did not improve the cycling stability of the Si/C-based cells. The cells with 15 wt% HFEPN retained 43% of capacity after 70 cycles, comparable to 46.5% for the reference electrolyte. The diffusion limitations imposed by the increased electrolyte viscosity are assumed to offset the interfacial benefits of the additive. Thus, alongside the improved synthetic route, this study demonstrates that while HFEPN functions as an effective flame retardant and SEI modifier, its practical benefits for silicon anodes are limited at high concentrations by detrimental effects on electrolyte transport properties and should be improved in future molecular design efforts. Full article

Auxetic metamaterials, characterised by a negative Poisson’s ratio, offer excellent energy absorption but often present limited compressive strength due to their strut-based architectures. Selective laser sintering (SLS) enables the precise fabrication of these structures, yet enhancing their mechanical performance remains challenging. This research investigates the influence of nodal spheres on re-entrant dodecahedral unit cells produced in PA12, varying node-to-strut diameter ratios (1:1, 2:1, and 3:1). Compression tests reveal significant increases in stiffness and compressive strength, reaching up to 88.70% for the 3:1 ratio. When normalised by relative density, the 2:1 configuration proves most effective, achieving a 35.33% increase in specific strength and a 19.58% improvement in specific energy absorption. The deformation behaviour indicates a mixed bending–stretching mechanism, with geometry exerting a stronger influence than the base material. Although larger nodal spheres enhance absolute strength, they also increase mass and relative density, which may limit their suitability for weight-sensitive applications. Overall, these findings highlight nodal reinforcement as a promising strategy to enhance the mechanical efficiency of auxetic metamaterials while maintaining their auxetic response. These improvements support applications in aerospace, automotive engineering, personal protection systems, lightweight structural panels, and energy-absorbing components. Full article

Titanium-based bulk metallic glasses (BMGs) offer high strength, lower stiffness than Ti-6Al-4V, and superior corrosion resistance, but conventional Ti glass-forming systems often contain toxic Ni, Be, or Cu. This work investigates five novel Ti-based alloys free of these elements—Ti₄₂Zr₃₅Si₅Co_12.5Sn_2.5Ta₃, Ti₄₂Zr₄₀Ta₃Si₁₅, Ti₆₀Nb₁₅Zr₁₀Si₁₅, Ti₃₉Zr₃₂Si₂₉, and Ti_65.5Fe_22.5Si₁₂—synthesized by arc melting and suction casting. Single-track laser remelting using a selective laser melting (SLM) system was performed to simulate additive manufacturing and examine microstructural evolution, cracking behavior, mechanical properties, and cytocompatibility. All alloys solidified into fully crystalline α/β-Ti matrices with Ti/Zr silicides; no amorphous structures were obtained. Laser remelting refined the microstructure but did not induce glass formation, consistent with the known limited glass-forming ability of Cu/Ni/Be-free Ti systems. Cracking was observed at low laser energies but crack density decreased as laser energy increased. Cracks were eliminated above ~0.4 J/mm for most alloys. Ti₄₂Zr₃₅Si₅Co_12.5Sn_2.5Ta₃ exhibited the lowest stiffness (~125 GPa), while Ti₆₀Nb₁₅Zr₁₀Si₁₅ showed the highest due to silicide precipitation. Cytotoxicity tests (ISO 10993-5) confirmed all alloys to be non-toxic, with some extracts even enhancing fibroblast proliferation. This rapid laser-remelting approach enables cost-effective screening of Ti-based glass-forming alloys for additive manufacturing. Ti–Zr–Ta–Si systems demonstrated the most promising properties for further testing using the powder bed method. Full article

Laser-driven ion acceleration in dense, hydrogen-rich media can be significantly enhanced by embedding metallic nanoantennas that support localized surface plasmon (LSP) resonances. Using large-scale particle-in-cell (PIC) simulations with the EPOCH code, we investigate how nanoantenna geometry and laser pulse parameters influence proton acceleration in gold-doped polymer targets. The study covers dipole, crossed, and advanced 3D-cross antenna configurations under laser intensities of 10¹⁷–10¹⁹ W/cm² and pulse durations from 2.5 to 500 fs, corresponding to experimental conditions at the ELI laser facility. Results show that the dipole antennas exhibit resonance-limited proton energies of ~0.12 MeV, with optimal acceleration at the intensities 4 × 10¹⁷–1 × 10¹⁸ W/cm² and pulse durations around 100–150 fs. This energy is higher by roughly three orders of magnitude than the proton energy for the same field and same polymer without dopes: ~1–2 × 10⁻⁴ MeV. Crossed antennas achieve higher energies (~0.2 MeV) due to dual-mode plasmonic coupling that sustains local fields longer. Advanced 3D and Yagi-like geometries further enhance field localization, yielding proton energies up to 0.4 MeV and larger high-energy proton populations. For dipole antennas, experimental data from ELI exists and our results agree with it. We find that moderate pulses preserve plasmonic resonance for longer and improve energy transfer efficiency, while overly intense pulses disrupt the resonance early. These findings reveal that plasmonic field enhancement and its lifetime govern energy transfer efficiency in laser–matter interaction. Crossed and 3D geometries with optimized spacing enable multimode resonance and sequential proton acceleration, overcoming the saturation limitations of simple dipoles. The results establish clear design principles for tailoring nanoantenna geometry and pulse characteristics to optimize compact, high-energy proton sources for inertial confinement fusion and high-energy-density applications. Full article

Background: Socioeconomic disparities may drive cancer inequities in Hispanic/Latino populations. We examined associations of perceived access to healthy foods (AHF) and food insecurity (FI) with diet and body mass index (BMI) changes in Latina breast cancer (BC) survivors. Methods: Latina BC survivors in a 12-month intervention trial aiming to increase fruit/vegetable intake and physical activity were analyzed. AHF was from a modified, validated neighborhood environment scale and dichotomized (low–medium vs. high). FI was defined as eating less and/or going hungry due to a lack of money. AHF and FI surveys were self-reported. Outcomes included dietary intake, diet quality, and BMI. Fruit/vegetable intake was log-transformed. Relationships between AHF and FI and changes in diet and BMI were evaluated using generalized estimating equations. Results: Of women with AHF data (n = 86), 58% reported low–medium access and 42% reported high access. Fruit/vegetable (FV) intake declined overall from baseline to 12 months, with greater reductions among low–medium AHF women (−32%, 95% CI: −51%, −7%) compared with high AHF women (−17%, 95% CI: −40%, +13%). Statistically significant 12-month decreases in total calories, carbohydrates, sugars, and fat occurred in low–medium AHF women but not high AHF women, and changes in total energy density, carbohydrates, sugars, and BMI at 12 months were statistically significantly different between women with low–medium AHF and women with high AHF, p ≤ 0.05. Among 157 women, 23% reported FI. Reductions in fruit/vegetable intake were larger in women with FI (−39%, 95% CI: −57%, −14%) than in women without FI (−10% reductions, 95% CI: −25%, +8%) and between-group differences were significant at both 6 and 12 months, p ≤ 0.05. Most diet measures decreased for both FI and non-FI women, with greater decreases among those with FI. Conclusions: Latina BC survivors with FI or perceived limited AHF experienced greater declines in indicators of healthy diets including FV intake. Future interventions should integrate strategies to measure AHF and FI to address disparate access to healthy food options. Full article

Platinum-based drugs play a pivotal role in contemporary cancer treatment, but their therapeutic utility is often limited by acquired resistance. The diiodido analog, cis-[PtI₂(NH₃)₂] is a promising derivative that has demonstrated the ability to overcome cisplatin resistance in vitro. To establish the molecular basis for this superior activity, we integrated experimental (NMR) spectroscopy with computational density functional theory (DFT) methods to precisely and comparatively understand the drug activation mechanisms. Comparative ¹⁴N NMR experiments elucidated the initial ligand substitution step, confirming halide displacement and a markedly higher tendency for ammonia release from cis-[PtI₂(NH₃)₂], particularly when reacting with sulfur-containing amino acids. Complementary DFT calculations determined the substitution energy values, revealing that the superior leaving-group ability of iodide results in a thermodynamically more favorable activation. Conceptual DFT parameters (softness, hardness, and Fukui indices) further demonstrated that initial substitution induces a strong trans effect, leading to the electronic sensitization of the remaining iodide ligand. This strong agreement between computational predictions and experimental data establishes a coherent molecular activation mechanism for cis-[PtI₂(NH₃)₂], demonstrating that iodide substitution promotes both thermodynamic and electronic activation of the platinum center, which is the key to its distinct pharmacological profile and ability to circumvent resistance. Full article

The use of liquid hydrogen (LH₂) as an energy carrier is gaining traction across sectors such as aerospace, maritime, and large-scale energy storage due to its high gravimetric energy density and low environmental impact. However, the cryogenic nature of LH₂, with storage temperatures near 20 K, poses significant thermodynamic and safety challenges. This review consolidates the current state of modelling approaches used to simulate LH₂ behaviour during storage and transfer operations, with a focus on improving operational efficiency and safety. The review categorizes the literature into two primary domains: (1) thermodynamic behaviour within storage tanks and (2) multi-phase flow dynamics in storage and transfer systems. Within these domains, it covers a variety of phenomena. Particular attention is given to the role of heat ingress in driving self-pressurization and boil-off gas (BoG) formation, which significantly influence storage performance and safety mechanisms. Eighty-one studies published over six decades were analyzed, encompassing a diverse range of modelling approaches. The reviewed literature revealed significant methodological variety, including general analytical models, lumped-parameter models (0D/1D), empirical and semi-empirical models, computational fluid dynamics (CFD) models (2D/3D), machine learning (ML) and artificial neural network (ANN) models, and numerical multidisciplinary simulation models. The review evaluates the validation status of each model and identifies persistent research gaps. By mapping current modelling efforts and their limitations, this review highlights opportunities for enhancing the accuracy and applicability of LH₂ simulations. Improved modelling tools are essential to support the design of inherently safe, reliable, and efficient hydrogen infrastructure in a decarbonized energy landscape. Full article

Degrowth scholars emphasize the importance of the foundational economy (FE) for ‘living well within planetary boundaries’. The foundational economy describes the provision and regulation of everyday goods and services needed for the satisfaction of basic needs, such as housing, care, education, energy, food and mobility. However, there is a lack of conceptual models linking FE production and consumption to biodiversity conservation and restoration. This paper develops an ecological–economic model of ecosystem services, biodiversity conservation, and the foundational economy. It embeds FE sectors in the whole economy and provides economic arguments both on the supply side (e.g., economies of scale, scope and density; transaction costs) as well as on the demand side (e.g., trust in institutions; universal basic services; willingness to accept changes) in favor of resource efficiency. Compared to extractive and financialized business models, the FE production has major environmental advantages, especially if connected to public and not-for-profit economic activities. Though FE production is certainly a necessary condition for biodiversity conservation, it is not per se a sufficient strategy. The foundational economy is also embedded in natural processes; thus, respective institutional, legal and economic frameworks are needed to limit the environmental impacts of FE. Full article

With the advancement of new power systems, phase-change materials (PCMs), owing to their ability to convert and store electrical energy, are increasingly recognized as a key solution to the intermittency of power supply. Nevertheless, such materials face challenges, including leakage and low thermal conductivity, which lead to reduced utilization efficiency. In this study, guar gum was used as the macroscopic framework, while self-prepared and optimized silica aerogel microsheets served as the microscopic framework to synergistically encapsulate the polyethylene glycol (PEG). Titanium dioxide (TiO₂) nanoparticles were incorporated to improve overall thermal conductivity, resulting in the composite PCM, GTS-PEG. In-depth characterization demonstrated effective PEG retention within the matrix, with a melting heat storage density of 164.16 J/g. Upon 30 min of continuous heating at 90 °C, the mass loss remained as low as 4.83%, indicating excellent thermal stability. The addition of TiO₂ increased thermal conductivity to 0.53 W/(m·K), representing a 140% boost over unmodified material. As a result, GTS-PEG not only successfully overcomes the leakage and thermal conductivity limitations of conventional PCMs but also, as a green and low-carbon innovative solution, paves a new path for the coordinated optimization and efficient conversion of power grid energy systems. Full article