Search Results (18,723)

Hydrogen is increasingly seen as a viable energy carrier in the transition to low-carbon energy systems, mainly because of its high gravimetric energy density and the absence of carbon emissions at the point of use. In this context, producing hydrogen from biomass represents a practical and sustainable option, as it allows the use of renewable and waste resources while supporting circular economy principles. This work examines the main pathways for hydrogen production from biomass, considering both thermochemical and biochemical routes, with a focus on their energy performance and practical limitations. The analysis shows that thermochemical processes, particularly gasification, remain the most developed and scalable solutions for converting solid biomass into hydrogen-rich gas, although their performance depends strongly on feedstock properties, reactor design, and operating conditions. By comparison, biochemical processes such as dark fermentation and photofermentation are more suitable for wet biomass but are limited by lower hydrogen yields and issues related to process stability. From a thermal engineering standpoint, system performance is influenced by heat transfer constraints, the energy demand of endothermic reactions, and the efficiency of gas cleaning, while parameters such as temperature, steam-to-biomass ratio, and equivalence ratio play a key role in optimization. Advanced approaches, including catalytic and sorption-enhanced gasification, show potential for improving performance. Overall, efficient hydrogen production requires a system-level approach, as no single technology can be considered universally optimal. Full article

Wireless Sensor Networks (WSNs) enable energy-efficient data collection in dynamic environments but continue to face the dual challenges of severely constrained node energy and the spatiotemporal heterogeneity of data traffic. Inspired by honeybee foraging behavior, this paper proposes a hybrid optimization framework that integrates mixed-integer linear programming (MILP) and Markov decision processes (MDP), utilizing Q-learning for adaptive decision-making. The proposed framework systematically maps the dual-layer decision-making mechanism of honeybee foraging onto a synergistic architecture combining MILP-based global planning and MDP-based local adaptation, offering a novel bio-inspired solution for mobile sink trajectory planning and adaptive routing. Specifically, the upper-level MILP module simulates a colony-level global assessment of distant nectar sources, generating an initial global trajectory by determining the optimal access sequence of cluster heads to minimize the movement cost of the mobile sink. The lower-level Q-learning module simulates the individual-level local adaptation, where bees adjust harvesting behavior in real-time based on nectar quality and distance. This module continuously optimizes routing parameters based on real-time network states, including residual energy, the ratio of surviving nodes, data queue lengths, and cluster head density. The algorithm employs an ϵ-greedy strategy to balance exploration and exploitation, while a periodic decision-update mechanism is introduced to harmonize computational efficiency with learning stability. Furthermore, a multi-objective reward function is designed to jointly optimize energy efficiency, network lifetime, end-to-end latency, and path length. Extensive simulation results demonstrate that the proposed MILP-MDP hybrid framework significantly outperforms several representative baseline algorithms in terms of network lifetime extension and energy balance. These findings validate that the integration of bio-inspired foraging strategies and reinforcement learning provides an efficient and robust solution for trajectory planning and adaptive routing in dynamic WSNs. Full article

In recent years, strong emphasis has been put on decarbonising the transport and mining sectors in an economically viable manner. To this end, ammonia is presented as a fuel, combining a high energy density (when compared to hydrogen) and zero carbon emissions. In this work, conversion of a mining haul truck engine is simulated for its use with an ammonia/diesel dual-fuel system at up to 70% Ammonia Energy Replacement (AER). The numerical setup is partially validated against engine performance data. The simulations suggest a reduction in CO${}_2$ emissions but an increase in N${}_2$O, which increases the carbon-equivalent emissions of the engine. Nevertheless, NO${}_{\mathrm{x}}$ emissions appear to be reduced, suggesting the use of post-treatment is required to deal with the issue of N${}_2$O. Cylinder temperature control is recommended for its reduction, as temperatures are lower when burning ammonia. On the other hand, the simulations suggest that ammonia slip increases with AER if diesel injection phasing is not optimised. Performance-wise, the engine develops a higher indicated mean effective pressure (IMEP) as AER increases, with a maximum at 40% AER, while combustion is delayed progressively into the engine cycle, as CAD50 values increase from −0.6 CAD ATDC at 0% AER to 20.1 CAD ATDC at 70% AER. Opportunities for further research are discussed, including more extensive experimental work to support or reject what is suggested by the simulations. Full article

Sulfur is a well-known catalyst poison, particularly for catalysts based on transition metals. Herein, we studied the adsorption of sulfur species on small nanoparticles (~1 nm in size) of the face centered cubic (fcc) transition metals (Rh, Ir, Ni, Pd, Pt, Cu, Ag, and Au) using density functional theory (DFT) modeling. At low sulfur coverage (one S atom per nanoparticle), sulfur preferentially occupies the surface hollow sites of the nanoparticles. At higher coverage, however, the subsurface diffusion of S in Ni, Pd, and Ag nanoparticles becomes energetically favorable with low activation energies. Among the considered metals, sulfur binds most strongly to Rh and Ir, and most weakly to Ag and Au. The present results shed light on the facility of S-poisoning on such metal nanoparticles, either by surface blocking or by underlying sulfurization of the metal. Full article

A globally applicable and fully automated simulation method based on satellite-derived Earth Observation (EO) data and global circulation models was developed and validated. Inputs to the simulation are DSM/DTM layers, surface roughness layer, forest canopy layer, and single-level point data from the European Centre for Medium-Range Weather Forecasts fifth-generation ECMWF reanalysis (ECMWF ERA5, a global circulation model produced by the Copernicus Climate Change Service (C3S)). High-resolution roughness length maps are produced by deep learning from optical satellite data. Velocity fields are predicted by fluid dynamics simulations in OpenFOAM using the IDDES turbulence model, a 3D resolved tree canopy implemented as isotropic momentum sinks, and a corrector step based on sub-grid-scale dynamic downscaling of ERA5 data. No calibration data from wind measurements close to the target are necessary to achieve results accurate enough for site assessments and wind park planning. The presented method is suitable for the prediction of average wind speeds and average power densities in complex terrain with high ruggedness indices for WEC (wind energy converter) installations closer to the ground and at hub heights of typical large-scale WECs. Full article

The multilayers of Ta/Pd/[CoFeB (0.3 nm)/Pd]×5/Pd films were fabricated by ultra-high-vacuum (UHV) magnetron sputtering and subsequently annealed at temperatures (T_A) ranging from 100 °C to 400 °C. The magnetic measurements were performed with the applied field oriented parallel and perpendicular to the film plane to evaluate the out-of-plane magnetic anisotropy (PMA). A maximum effective PMA energy density (K_eff) of ≈7.82 × 10⁵ erg/cc and a small out-of-plane saturation magnetisation (M_s⊥) were achieved at the optimal T_A. The evolution of PMA is associated with interfacial atomic migration and oxidation processes, as confirmed by X-ray photoelectron spectroscopy (XPS). Annealing at 300 °C initiates the formation of TaB and TaOB interfacial phases, whereas annealing at 400 °C promotes the enhanced growth of Ta₂O₅ and TaB, along with additional TaOB formation owing to increased oxygen migration. These thermally stable Ta–boride phases lead to pronounced modifications in the magnetic properties. Consequently, oxygen migration and interfacial reactions at elevated temperatures primarily alter the chemical states of the B 1s, Pd 3d, and Ta 4f orbitals, thereby influencing the PMA. The field-dependent electrical resistance (MR) study demonstrates that annealing at 100–400 °C optimises the anisotropic effect in the [CoFeB/Pd]×5-based multilayers. However, higher temperatures can trigger atomic intermixing, which degrades PMA strength and the resistance response. Moreover, the samples were further characterised by their structural, anomalous Hall effect (AHE) and magnetoresonance (MRO) properties. Overall, controlled T_A-driven oxygen diffusion and interfacial oxidation enable effective tuning of the PMA, MR, and MRO properties of ultrathin [CoFeB/Pd]×5 multilayers, highlighting their strong potential for spin–orbit torque (SOT), Dzyaloshinskii–Moriya interaction (DMI), and magnetic skyrmion-based spintronic devices. Full article

In controlled-environment agriculture (CEA), light serves both as an energy source for photosynthesis and as a regulatory factor. However, the light responses of underutilized leafy greens are still not fully characterized compared with model crops such as lettuce. This study evaluated the effects of lighting parameters on the growth, metabolism, antioxidant properties, and mineral composition of Chrysanthemum coronarium (shungiku) greens cultivated hydroponically in CEA. Three parallel experiments were conducted, aiming to explore the effects of (I) light spectrum using red (R, 660 nm), blue (B, 447 nm), and combined RB light; (II) photoperiod, using 12, 16, and 24 h photoperiods at equal daily light integral; and 150, 200, 250, and 300 µmol m⁻² s⁻¹ photosynthetic photon flux density (PPFD) at 16 h photoperiod. RB light promoted the highest biomass accumulation and light use efficiency (LUE), while monochromatic red and blue light limited growth and reduced Fe and Zn contents. A 12 h photoperiod yielded the best results for leaf area, fresh weight, and LUE compared with 16 and 24 h photoperiods. Higher PPFD increased biomass, soluble sugars, antioxidant capacity, organic acids, and micronutrients, with peak LUE at 200 µmol m⁻² s⁻¹ instead of the maximum yield at 300 µmol m⁻² s⁻¹. These findings emphasize the importance of crop-specific and trait-oriented light optimization for underutilized leafy vegetables. Full article

The Gulong shale oil reservoir is characterized by high clay content and strong heterogeneity, with substantial variations in mineral composition among different intervals. However, existing fracability evaluation methods for such continental shales remain inconsistent and often rely on oversimplified two-dimensional fracture descriptors, lacking a multi-parameter quantitative framework derived from three-dimensional fracture characterization. In this study, the Q1 and Q9 members of the Gulong shale oil were selected, and laboratory-scale hydraulic fracturing simulation experiments were conducted using supercritical carbon dioxide (SC-CO₂), liquid CO₂, and water as the fracturing media. Within a fractal-theory framework based on CT-derived three-dimensional reconstructions, a multi-scale evaluation index system was established by integrating fractal dimension, fracture density, and spatial connectivity. The experimental results demonstrate that fluid properties exert a decisive influence on rock failure behavior. Owing to its ultra-low viscosity and strong diffusivity, SC-CO₂ can significantly reduce formation breakdown pressure while effectively activating natural weak planes to generate a more complex fracture network. For the Q9 shale, the breakdown pressure under SC-CO₂ is reduced by 11.91% and 8.33% relative to water and liquid CO₂, respectively. Moreover, the fracture fractal dimension reaches 2.41 under SC-CO₂, which is markedly higher than the values obtained under liquid CO₂ (2.18) and water (2.12). Mineral composition and densely developed bedding are the key factors inducing fracture branching and deflection, whereas injection rate and an asymmetric stress field regulate the internal energy-release rate and stress path, thereby influencing fracture crossing capability and aperture evolution. Based on the experimental dataset, a fracture complexity index (FCI) evaluation model was developed: under SC-CO₂ fracturing, the FCI values are 8.92 for the Q9 member and 4.43 for the Q1 member, and the model predictions are in good agreement with physical observations. This work elucidates the failure mechanism of the Gulong shale under multi-field coupling and provides a theoretical basis for optimizing hydraulic fracturing and evaluating fracability in unconventional reservoirs through the proposed FCI-based assessment framework. Full article

Since the synthesis of ferrocene in 1951, metallocenes have attracted attention, making the accurate prediction of their electronic structure and ionization energy crucial for understanding their photophysical and electrochemical behavior in materials and in biological systems. Here, we combined Density Functional Theory (DFT), Complete Active Space Self-Consistent Field (CASSCF), NEVPT2 (N-Electron Valence State Perturbation Theory) and Coupled Cluster approaches (CCSD, DLPNO-CCSD(T)) to study the electronic structure, ionization energies (IEs) and absorption spectra of metallocene and metallocenium complexes in the gas phase and in THF implicit solvent. DFT IEs agree closely with NEVPT2 and DLPNO-CCSD(T) values and with experiment values (deviations 0.02–0.3 eV). For CASSCF and NEVPT2, the minimal active space of the d electrons at six orbitals is not enough for the accurate prediction of the IEs, while an extended active space incorporating all 3d metal electrons plus four ligand valence electrons into 15 orbitals improves the calculated IE values. In solution, computed oxidation energies (OEs) in THF reproduce experimental values and follow the Fe > Ni > Co ordering. Substitution of metallocene complexes with chromophore units results in similar OEs. Overall, the substitution effects remain modest: the effect of substitution on OE values results in differences up to 0.2 eV. These results clarify the effect of the metal center on IE and OE values and UV–vis absorption behavior. Full article

The rising market penetration of new energy vehicles (NEVs) is transforming urban traffic into a heterogeneous mix of battery electric (BEVs), hybrid electric (HEVs), and conventional fuel vehicles (FVs). For analytical brevity, traditional internal combustion engine vehicles (ICEVs) are hereafter referred to as ‘fuel vehicles (FVs)’ in the discussion of New Energy Vehicle (NEV) networks. This research investigates the efficacy of centralized coordination for NEVs within a localized region, as opposed to individualized speed control, in enhancing the mitigation of traffic congestion. Evaluating traffic efficiency and decarbonization strategies in such settings often requires extensive random sampling and Monte Carlo simulations over a large set of parameter combinations. However, conventional microscopic traffic simulators (e.g., SUMO), which rely on fine-grained modeling of vehicle dynamics and signal control, incur prohibitive computational time when scaled to large networks and numerous experimental scenarios. In this study, battery electric vehicles and hybrid electric vehicles are designed as density-aware vehicles, whose movement speed is adaptively adjusted according to the regional traffic density in their vicinity and the control parameter β. In contrast, fuel vehicles adopt a stochastic movement speed and, together with other vehicle types, exhibit either movement or stoppage in the lattice environment. This density-driven speed-adaptive control and lattice arbitration mechanism is intended to reproduce, in a simplified yet extensible manner, changes in mobility and traffic-flow stability under high-density traffic conditions. The simulation results indicate that, under the same Manhattan road network and vehicle-density conditions, tuning the β parameter of new energy vehicles to reduce their movement speed in high-density areas and to mitigate abrupt position changes can suppress traffic-flow oscillations, delay the onset of the congestion phase transition, and promote spatial equilibrium of traffic flow. Meanwhile, this study develops simplified energy-consumption and carbon emission models for battery electric vehicles, hybrid electric vehicles, and fuel vehicles, demonstrating that incorporating a speed-adaptive density strategy into mixed traffic flow not only helps alleviate abnormal congestion but also reduces potential energy use and carbon emissions caused by congestion and stop-and-go behavior. From a sensing and practical perspective, the proposed framework assumes that future connected and autonomous vehicles (CAVs) can estimate vehicle states and local traffic density through GNSS–IMU multi-sensor fusion and V2X communications, indicating methodological consistency between the proposed model and real-world CAV sensing capabilities and making it a suitable and effective experimental platform for investigating the relationships among new energy vehicle penetration, density-control strategies, and carbon footprint. Full article

This study investigates the enhancement of hydrogen production efficiency in water electrolysis through the application of external magnetic fields. A series of controlled experiments were conducted using four distinct electrode materials—stainless steel (SS), low-carbon steel (LCS), titanium (Ti), and platinum-plated titanium (Ti/Pt)—to identify the optimal configuration for maximizing gas output. The research evaluated the influence of electrolyte concentration (KOH), current density, and magnetic field intensity ranging from 0 to 1800 G. Our findings indicate that the application of a 200 G magnetic field leads to a notable 6% increase in the rate of gas production compared to non-magnetized conditions. Specifically, a magnetic field oriented parallel to the electrode plates outperformed a perpendicular orientation by approximately 5%, a phenomenon attributed to the Lorentz force facilitating ionic mass transfer and gas bubble detachment. Furthermore, the integration of ion-exchange and proton-exchange membranes (MC-3470 and N-117) effectively isolated the anodic and cathodic products, elevating hydrogen purity from 67.4% to approaching 100% without compromising electrolysis efficiency. These results demonstrate that the strategic coupling of moderate magnetic fields with optimized electrode configurations provides a promising pathway for improving the efficiency and cleanliness of hydrogen production, which is essential for its role as a sustainable energy carrier. Full article

Background/Objectives: Co-processed excipients (CPEs) are designed for direct compression through particle engineering, yet comprehensive powder rheological profiles systematically comparing advanced and traditional characterization methods remain limited. This study characterized fifteen lactose-based excipients using European Pharmacopoeia (Ph. Eur.) methods and the complete Freeman FT4 Powder Rheometer measurement suite, establishing a correlation framework linking particle-level attributes to macroscopic flow behavior. Methods: Fifteen excipients were characterized for bulk and tapped density, compressibility index, flow time (Ph. Eur. 2.9.16), and angle of repose (Ph. Eur. 2.9.36). Particle size and shape were measured by dynamic image analysis. FT4 measurements comprised stability and variable flow rate testing, consolidation, aeration, compressibility, permeability, shear cell, and wall friction at three surface roughness. Pearson correlation matrices were computed across all 53 parameters. Results: Classical flow indices classified most CPE as good-to-satisfactory, failing to discriminate materials with fundamentally different dynamic flow profiles. FT4 testing revealed a fourfold range in Basic Flowability Energy (624–2107 mJ), a ninefold range in flow function coefficient (4.3–35.8), and wide aeration sensitivity differences (Aeration Ratio: 1.9–283.7). Strong correlations were identified between Specific Energy and compressibility index (r = 0.85), cohesion and Flow Rate Index (r = 0.79), and Normalized Aeration Sensitivity and pressure drop (r = 0.86). Within-family comparisons (Tablettose 70/80/100, FlowLac 90/100) revealed that particle size distribution breadth is a more critical flow determinant than median size alone. Conclusions: Combining FT4 rheometry with pharmacopoeial testing provides substantially greater discriminating power than either approach alone, enabling rational excipient selection for direct compression formulation. Full article

Background/Objectives: Protein intake is a key determinant of skeletal muscle health across the lifespan, yet optimal strategies must also account for cardiometabolic health and environmental sustainability. Differences in digestibility and amino acid composition between plant and animal-based proteins may influence their capacity to stimulate muscle protein synthesis (MPS), particularly in aging. Methods: This narrative review integrates evidence from acute tracer studies, randomized controlled trials, and long-term observational research comparing plant versus animal-based proteins for preserving muscle while supporting environmental goals and cardiometabolic health across populations. PubMed and Google Scholar were searched from inception to 11 December 2025 (plant-based protein OR animal-based protein AND sarcopenia OR muscle protein synthesis), with citation tracking. In total, 80 relevant findings were identified. Results: Acute tracer studies show that, gram-for-gram, animal-based proteins (particularly whey/dairy) stimulate greater myofibrillar protein synthesis due to higher leucine density, digestibility, and more rapid aminoacidemia—an effect that is more pronounced in older adults with anabolic resistance. In younger individuals, these differences are largely attenuated when total protein intake is sufficient. Importantly, the anabolic potential of plant-based proteins can be enhanced through higher dosing, amino acid or leucine fortification, and complementary protein blending (e.g., cereals with legumes or use of high-DIAAS isolates). Consistent with this, longer-term resistance training studies demonstrate comparable gains in muscle mass and strength between plant- and animal-based diets when protein intake (≥1.0–1.2 g/kg/day; ≥1.2–1.5 g/kg/day in illness), per-meal distribution (~0.4 g/kg with ~3–4 g leucine in older adults), and energy intake are optimized. Beyond muscle outcomes, higher plant-based protein intake is associated with favorable cardiometabolic profiles and lower environmental impact. Conclusions: An age-specific, mixed protein approach is recommended, emphasizing plant-based proteins in younger adults and higher-quality, leucine-rich proteins in older individuals. Defining optimal plant-to-animal-based protein ratios remains a key research priority. Full article

Solid oxide electrolysis cells (SOECs) are regarded as a promising technology for sustainable hydrogen production because of their high energy conversion efficiency. In this study, a multiphysics numerical model combined with a random particle packing framework was used to evaluate the influence of anode microstructural parameters on the electrochemical performance of a button-type SOEC. The effects of anode porosity, particle size, and electrode thickness on current density were systematically analyzed. Increasing porosity from 0.3 to 0.5 reduced the current density because of the decreased fraction of electrochemically active material. Increasing the anode particle size from 50 to 300 nm significantly shortened the triple-phase boundary (TPB) length, leading to a decrease in current density from 6289 to 5502 A m⁻². The effect of anode thickness reflects a trade-off between electrochemical activity and gas transport, with the current density increasing from 5502 to 5940 A m⁻² as the thickness increased from 10 to 20 μm. Overall, the results highlight the coupled roles of reaction-site availability and oxygen transport in determining SOEC performance. This study provides a parametric assessment of how anode microstructure affects SOEC performance and may support the structural optimization of SOEC oxygen electrodes. Full article

This study investigates a thermal management strategy for butyl/chloroprene rubber (IIR/CR) bladder compounds by incorporating hexagonal boron nitride (h-BN) as a thermally conductive filler to enhance heat transfer efficiency. Compounds containing 0, 10, 25, and 33 wt% h-BN were prepared via solution mixing to ensure uniform dispersion and subsequently vulcanized using a hot press. The materials were characterized in terms of morphology, cure behavior using a moving die rheometer (MDR), thermal conductivity, crosslink density, mechanical properties, and dynamic mechanical analysis (DMA). The incorporation of h-BN significantly enhanced thermal performance, nearly doubling the thermal conductivity at 33 wt%. MDR measurements demonstrated that this improved heat transfer capability accelerated the thermal onset of vulcanization, effectively reducing scorch time. Mechanical testing revealed a systematic increase in stiffness at application-relevant low strain levels (25–50%), attributed to hydrodynamic reinforcement, accompanied by a progressive increase in elongation at break. This enhanced extensibility is associated with the presence of lamellar h-BN platelets, which facilitate stress redistribution and promote dynamic chain mobility under deformation. DMA showed that h-BN incorporation increased the storage modulus and intensified the Payne effect, confirming the formation of a robust physical filler network. Overall, the incorporation of h-BN delivers a formulation pathway for energy-efficient tire curing bladders by significantly improving heat transfer efficiency and dimensional stability. Full article