Search Results (14,098)

Hexagonal Boron Nitride (h-BN) is an exceptional dielectric material with significant potential for high-performance electronic and optoelectronic devices. While previous studies have explored its role in GaN-based MIS (metal/insulator/semiconductor) structures, the influence of few-layer h-BN on AlGaN MIS devices—particularly with varying Al compositions—remains unexplored. In this work, we systematically investigate the Fowler–Nordheim tunneling effect in few-layer h-BN integrated into AlGaN MIS architectures, focusing on the critical roles h-BN layer count, AlGaN alloy composition, and interfacial properties in determining device performance. Through combined simulations and experiments, we accurately determine key physical parameters, such as the layer-dependent effective mass and band alignment, and analyze their role in optimizing MIS device characteristics. Our findings reveal that the 2D h-BN insulating layer not only enhances breakdown voltage and reduces leakage current but also mitigates interfacial defects and Shockley–Read–Hall recombination, enabling high-performance AlGaN MIS devices under elevated voltage and power conditions. This study provides fundamental insights into h-BN-based AlGaN MIS structures and advances their applications in next-generation high-power and high-frequency electronics. Full article

Soybean (Glycine max (L.) Merrill) is a major oilseed crop rich in phytosterols and tocopherols, compounds associated with functional and nutritional properties of vegetable oils. This study aimed to apply, for the first time, Independent Component Analysis (ICA) to discriminate the composition of phytosterols (β-sitosterol, campesterol, stigmasterol) and tocopherols (α, β, γ, δ) in 20 soybean genotypes—14 non-transgenic and six transgenic—cultivated in two major producing regions of Paraná state, Brazil (Londrina and Ponta Grossa). Lipophilic compounds were extracted from soybean seeds, quantified via gas chromatography and HPLC, and statistically analyzed using ICA with the JADE algorithm. The extracted independent components successfully differentiated soybean varieties based on phytochemical profiles. Notably, transgenic cultivars from Ponta Grossa exhibited higher levels of total tocopherols, including α- and β-tocopherol, while conventional cultivars from both regions showed elevated phytosterol content, particularly campesterol and stigmasterol. ICA proved to be a powerful unsupervised method for visualizing patterns in complex compositional data. These findings highlight the significant influence of genotype and growing region on the nutraceutical potential of soybean, and support the use of multivariate analysis as a strategic tool for cultivar selection aimed at enhancing functional quality in food applications. Full article

At present, various advanced technologies for field development based on gas-enhanced oil recovery (EOR) methods are widely applied worldwide. These include high-pressure gas injection (hydrocarbon gases, nitrogen, flue gases), water-alternating-gas (WAG) injection, and carbon dioxide (CO₂) flooding. This study presents the results of filtration experiments investigating the application of gas EOR methods using core samples from a heavy oil reservoir. The primary objective of these experiments was to determine the oil displacement factor and analyze changes in interfacial tension upon injection of different gas agents. The following gases were utilized for modeling gas EOR processes: nitrogen (N₂), carbon dioxide (CO₂), and hydrocarbon gases (methane, propane). The core samples used in the study were obtained from the East Moldabek heavy oil field in Kazakhstan. Based on the results of the filtration experiments, carbon dioxide (CO₂) injection was identified as the most effective gas EOR method in terms of increasing the oil displacement factor, achieving an incremental displacement factor of 5.06%. Other gas injection methods demonstrated lower efficiency. Full article

Natural gas plays a critical role in integrated energy systems. In this context, the present study proposes an optimization model for the electricity–gas coupling system, grounded in the theory of interdependent networks. By integrating network topology parameters with real-time operational metrics, the model substantially enhances system robustness and adaptability. To quantify nodal vulnerability and importance, the study introduces two novel evaluation indicators: the Electric Potential–Closeness Fusion Indicator (EPFI) for power networks and the Pressure Difference–Closeness Comprehensive Indicator (PDCI) for natural gas systems. Leveraging these indicators, three coupling paradigms—assortative, disassortative, and random—are systematically constructed and analyzed. System resilience is assessed through simulation experiments incorporating three attack strategies: degree-based, betweenness centrality-based, and random node removal. Evaluation metrics include network efficiency and the variation in the size of the largest connected subgraph under different coupling configurations. The proposed framework is validated using a hybrid case study that combines the IEEE 118-node electricity network with a 20-node Belgian natural gas system, operating under a unidirectional gas-to-electricity energy flow model. Results confirm that the disassortative coupling configuration, based on EPFI and PDCI indicators, exhibits superior resistance to network perturbations, thereby affirming the effectiveness of the model in improving the robustness of integrated energy systems. Full article

Aqueous redox flow batteries (ARFBs) have attracted significant attention in the field of electrochemical energy storage due to their high intrinsic safety, low cost, and flexible system configuration. However, the advancement of this technology is still hindered by several critical challenges, including capacity decay, structural optimization, and the design and application of key materials as well as their performance within battery systems. Addressing these issues requires systematic theoretical foundations and scientific guidance. Numerical modeling has emerged as a powerful tool for investigating the complex physical and electrochemical processes within flow batteries across multiple spatial and temporal scales. It also enables predictive performance analysis and cost-effective optimization at both the component and system levels, thus accelerating research and development. This review provides a comprehensive overview of recent progress in the modeling of ARFBs. Taking the all-vanadium redox flow battery as a representative example, we summarize the key multiphysics phenomena involved and introduce corresponding multi-scale modeling strategies. Furthermore, specific modeling considerations are discussed for phase-change ARFBs, such as zinc-based ones involving solid–liquid phase transition, and hydrogen–bromine systems characterized by gas–liquid two-phase flow, highlighting their distinctive features compared to vanadium systems. Finally, this paper explores the major challenges and potential opportunities in the modeling of representative ARFB systems, aiming to provide theoretical guidance and technical support for the continued development and practical application of ARFB technology. Full article

Accurately predicting the compressive strength of high-performance concrete (HPC) is critical for ensuring structural integrity and promoting sustainable construction practices. However, HPC exhibits highly complex, nonlinear, and multi-factorial interactions among its constituents (such as cement, aggregates, admixtures, and curing conditions), which pose significant challenges to conventional predictive models. Traditional approaches often fail to adequately capture these intricate relationships, resulting in limited prediction accuracy and poor generalization. Moreover, the high dimensionality and noisy nature of HPC mix data increase the risk of model overfitting and convergence to local optima during optimization. To address these challenges, this study proposes a novel bio-inspired hybrid optimization model, AP-IVYPSO-BP, which is specifically designed to handle the nonlinear and complex nature of HPC strength prediction. The model integrates the ivy algorithm (IVYA) with particle swarm optimization (PSO) and incorporates an adaptive probability strategy based on fitness improvement to dynamically balance global exploration and local exploitation. This design effectively mitigates common issues such as premature convergence, slow convergence speed, and weak robustness in traditional metaheuristic algorithms when applied to complex engineering data. The AP-IVYPSO is employed to optimize the weights and biases of a backpropagation neural network (BPNN), thereby enhancing its predictive accuracy and robustness. The model was trained and validated on a dataset comprising 1,030 HPC mix samples. Experimental results show that AP-IVYPSO-BP significantly outperforms traditional BPNN, PSO-BP, GA-BP, and IVY-BP models across multiple evaluation metrics. Specifically, it achieved an R² of 0.9542, MAE of 3.0404, and RMSE of 3.7991 on the test set, demonstrating its high accuracy and reliability. These results confirm the potential of the proposed bio-inspired model in the prediction and optimization of concrete strength, offering practical value in civil engineering and materials design. Full article

Mining (1) operations in remote areas (2) face significant challenges related to energy supply, high fuel costs, and limited infrastructure. This study investigates the potential for achieving energy independence (3) and resilience (4) in such environments through the integration of renewable energy sources (5) and battery–electric mining equipment. Using the “Studena Vrila” underground bauxite mine as a case study, a comprehensive techno-economic and environmental analysis was conducted across three development models. These models explore incremental scenarios of solar and wind energy adoption combined with electrification of mobile machinery. The methodology includes calculating levelized cost of energy (LCOE), return on investment (ROI), and greenhouse gas (GHG) reductions under each scenario. Results demonstrate that a full transition to RES and electric machinery can reduce diesel consumption by 100%, achieve annual savings of EUR 149,814, and cut GHG emissions by over 1.7 million kg CO₂-eq. While initial capital costs are high, all models yield a positive Net Present Value (NPV), confirming long-term economic viability. This research provides a replicable framework for decarbonizing mining operations in off-grid and infrastructure-limited regions. Full article

Urban forests are vital to cities because they provide a range of ecosystem services, including carbon (C) sequestration, air purification, and urban cooling. However, urban forestry also generates significant amounts of organic waste, such as grass clippings, pruned tree branches, and fallen tree leaves and woody debris that can contribute to greenhouse gas (GHG) emissions if not properly managed. In this study, we investigated the effect of wheat straw biochar (produced at 500 °C) on GHG emissions from two types of urban forestry waste: green waste (GW) and yard waste (YW), using a 100-day laboratory incubation experiment. Overall, GW released more CO₂ than YW, but biochar addition reduced cumulative CO₂ emissions by 9.8% in GW and by 17.6% in YW. However, biochar increased CH₄ emissions from GW and reduced the CH₄ sink strength of YW. Biochar also had contrasting effects on N₂O emissions, increasing them by 94.3% in GW but decreasing them by 61.4% in YW. Consequently, the highest global warming potential was observed in biochar-amended GW (125.3 g CO₂-eq kg⁻¹). Our findings emphasize that the effect of biochar on GHG emissions varies with waste type and suggest that selecting appropriate biochar types is critical for mitigating GHG emissions from urban forestry waste. Full article

Essential oils (EOs) constitute intricate mixtures of volatile phytochemicals that have garnered significant attention due to their multifaceted biological effects. Notably, the presence of bioactive constituents capable of inhibiting tyrosinase enzyme activity and scavenging reactive oxygen species (ROS) underpins their potential utility in skin-related applications, particularly through the modulation of melanin biosynthesis and protection of skin-relevant cells from oxidative damage—a primary contributor to hyperpigmentation disorders. Zingiber officinale Rosc. (ginger) and Humulus lupulus L. (hop) are medicinal plants widely recognized for their diverse pharmacological properties. To the best of our knowledge, this study provides the first report on the synergistic interactions between essential oils derived from these species (referred to as EOZ and EOH) offering novel insights into their combined bioactivity. The purpose of this study was to evaluate essential oils extracted from ginger rhizomes and hop strobiles with respect to the following: (1) chemical composition, determined by gas chromatography–mass spectrometry (GC-MS); (2) tyrosinase inhibitory activity; (3) capacity to inhibit linoleic acid peroxidation; (4) ABTS^•+ radical scavenging potential. Furthermore, the study utilizes both the combination index (CI) and dose reduction index (DRI) as quantitative parameters to evaluate the nature of interactions and the dose-sparing efficacy of essential oil (EO) combinations. GC–MS analysis identified EOZ as a zingiberene-rich chemotype, containing abundant sesquiterpene hydrocarbons such as α-zingiberene, β-bisabolene, and α-curcumene, while EOH exhibited a caryophyllene diol/cubenol-type profile, dominated by oxygenated sesquiterpenes including β-caryophyllene-9,10-diol and 1-epi-cubenol. In vitro tests demonstrated that both oils, individually and in combination, showed notable anti-tyrosinase, radical scavenging, and lipid peroxidation inhibitory effects. These results support their multifunctional bioactivity profiles with possible relevance to skin care formulations, warranting further investigation. Full article

This study investigates the viability of a native Scenedesmus sp. strain for use in a 50 L bubble column photobioreactor designed to reduce greenhouse gas emissions under simulated spring, extreme summer, and winter conditions. The experiments were conducted by placing the reactor in a controlled climatic chamber, which allowed us to regulate the temperature, light intensity, and day–night cycles throughout the entire experiment. The results showed that under simulated spring conditions (a maximum temperature of 22 °C), the algal culture grew continuously for 61 days. Under extreme summer conditions (a maximum temperature of 39 °C), an initial drop in cell density was followed by recovery and continued growth over 75 days, although biomass production was 35% lower. Under winter conditions (a maximum temperature of 10 °C), the culture failed, indicating the need to prevent temperatures below 10 °C. In terms of biomass production, the culture densities achieved were 1.04 g L⁻¹ and 0.68 g L⁻¹ in the spring and summer trials, respectively. The Scenedesmus sp. strain demonstrated high carbon capture efficiency, tolerance to extreme heat, and sustained growth without the need for fresh medium or pH adjustments for over 60 days during spring and extreme summer conditions, confirming its potential for outdoor applications. Full article

The large number of underutilized tree residues in Japan is a matter of concern, and their appropriate application needs to be promoted. Trees are very diverse, and there are differences in the volatile essential oil compounds and biological activities among different tree species. However, the effects of these tree species’ characteristics on human sensitivity and mental and physical functionality remain underexplored. This study investigated the effects of essential oils from multiple tree species on subjective and physiological responses. The essential oils from nine tree species were tested, subjective scent assessments were conducted, and their effect on autonomic nervous activity was measured. The volatile profiles of the oils were analyzed using gas chromatography–mass spectrometry. Our findings revealed clear differences in the composition of volatile essential oils among species, which influenced the scent evaluation and individual preferences. We suggest that scent preferences have the potential to influence physiological responses. The findings indicate that volatile essential oils could play a potential role in making use of tree resources effectively, and they may also be beneficial for maintaining human health. Full article

Pistachio nuts are among the 50 best foods with the highest antioxidant potential. They have a balanced content of mono- (~70%) and polyunsaturated (~20%) fatty acids, minerals, and bioactive compounds such as tocopherols, phytosterols, and phenolic compounds, which have shown rapid accessibility in the stomach. Pistachio consumption provides several health benefits, primarily due to its antioxidant properties and high content of essential nutrients. In this study, we analyzed the mineral composition, total phenolic content (TP), antioxidant activity (AA), and UHPLC/MS-MS polyphenolic profile of three Argentinian pistachio crops. Additionally, the physicochemical parameters and the elemental profiles of the growing soils were determined, as they influence mineral uptake and the synthesis of bioactive compounds in pistachio kernels. The TP was not significantly modified by the growing soils, with Crop3 presenting the highest TP content (276 ± 14 mg GA/100 g DW). Crop3 exhibited 18% higher TP content compared to Crop2. Similarly, FRAP values ranged from 28.0 to 36.5 mmol TE/100 g DW, with Crop1 showing a 30% increase compared to Crop2. DPPH values varied from 19.0 to 24.3 mmol TE/100 g DW, with Crop1 displaying 28% higher activity than Crop2. However, the polyphenolic profile was similar for all crops analyzed. Thirty compounds were identified; only Crop 1 contained the flavanone eriodyctiol and the isoflavone genistein, while the flavanone naringenin and the flavone luteolin were identified in Crop1 and Crop3. Regarding mineral content, the pistachio kernels mainly contained K, Ca, and Mg. Multivariate analyses revealed distinct elemental and antioxidant profiles among crops. LDA achieved classification accuracies of 77.7% for soils and 74.4% for kernels, with Pb, Zn, Cu, Rb, Sr, and Mn as key discriminants. CCA confirmed strong soil–kernel mineral correlations (r = 1), while GPA showed higher congruence between antioxidant traits and kernel composition than with soil geochemistry. These findings underscore the importance of soil composition in determining the nutritional quality of pistachio kernels, thereby supporting the beneficial health effects associated with pistachio consumption. Full article

Analysis of changes in TVOC and VOCs chemical composition or odor characteristics of particleboard before and after decoration treatment with resin-impregnated paper (RIP), polypropylene (PP) film and polyvinyl chloride (PVC) film were studied. The effects of these three decoration treatments on masking or suppressing the release of VOCs and odorants from particleboard were explored. The substances that were covered or suppressed and newly introduced before and after processing were identified to provide a basis for reducing the odor emissions of PVC-, PP- and RIP-decorated particleboard. Taking undecorated particleboard and particleboard treated by three types of decorative materials as research subjects, the air permeability of the three decorative materials was tested using the Gurley Permeability Tester. TVOC emissions from the boards were evaluated using the 1 m³ environmental chamber method. Qualitative and quantitative analyses of the samples were conducted via thermal desorption–gas chromatography–mass spectrometry (TD-GCMS). The contribution of odor substances was determined using odor activity value (OAV). The results indicated that the permeability from high to low was PVC film, PP film and RIP. Compared with undecorated particleboard, the TVOC emissions of PVC-decorated boards decreased by 93%, PP-decorated particleboard by 83% but the TVOC emissions of RIP-decorated particleboard increased by 67%. PP decoration treatment masked or suppressed the release of 20 odor substances but introduced xylene, which can increase potentially the health risks for PP-decorated particleboard. PVC decoration treatment masked or suppressed 19 odor substances, but it introduced 12 new compounds, resulting in an overall increase in TVOC emissions. RIP treatment did not introduce new odor substances. After PP film and RIP treatments, both the variety of VOCs released and the number of key odor-contributing compounds and modifying odorants decreased. In contrast, the number of modifying odorants and potential odorants increased after PVC treatment. VOC emissions were effectively masked or suppressed by three decoration treatments, same as the release of substances contributing to overall odor of particleboard was reduced. Among them, PP and RIP decorative materials demonstrate better effects. Full article

The increasing prevalence of antibiotic resistance and the limited availability of antiviral therapeutics for pathogens such as human respiratory syncytial virus (hRSV) underscore the need for novel, plant-derived antimicrobial substances. In this study, we evaluated the antiproliferative, antibacterial, and antiviral activities of aqueous leaf extracts from two plants commonly found in North America, Osage orange (M. pomifera) and spearmint (M. spicata). Both extracts exhibited no significant cytotoxic or morphologic impact on HEp-2 human cancer cells up to 25 mg/mL. However, both extracts demonstrated strong dose-dependent antibacterial activity, significantly inhibiting replication of E. coli and S. aureus at concentrations ≥ 1 mg/mL. Antiviral assays revealed that both extracts inhibited hRSV infectivity, with spearmint extract showing higher potency (EC₅₀ = 1.01 mg/mL) compared to Osage orange (EC₅₀ = 3.85 mg/mL). Gas chromatography–mass spectrometry (GC-MS) identified three major extract constituents: 3-hydroxybenzyl alcohol, 4-hydroxybenzyl alcohol (Osage orange), and R-(-)-carvone (spearmint). Among these, only carvone significantly inhibited hRSV in vitro, suggesting its key role in spearmint’s antiviral activity. These findings highlight the therapeutic potential of Osage orange and spearmint leaf extracts, particularly as sources of water-soluble compounds with antimicrobial properties, and support further investigation into their mechanisms of action and broader clinical relevance. Full article

Wild Ganoderma lucidum from Nepal’s high-altitude regions was studied to identify key bioactive compounds and assess the influence of solvent type—water, ethanol, methanol, and acetone—on extraction efficiency and biological activity. Extracts were evaluated for antioxidant potential, cytotoxicity against HeLa cells, and phytochemical composition via gas chromatography–mass spectrometry (GC-MS). Solvent type significantly affected both yield and bioactivity. Acetone yielded the highest crude extract (5.01%), while ethanol extract exhibited the highest total phenolic (376.5 ± 9.3 mg PG/g) and flavonoid content (30.3 ± 0.5 mg QE/g). Methanol extract was richest in lycopene (0.07 ± 0.00 mg/g) and β-carotene (0.45 ± 0.02 mg/g). Ethanol extract demonstrated consistently strong DPPH, superoxide, hydroxyl, and nitric oxide radical scavenging activity, along with high reducing power. All extracts showed dose-dependent cytotoxicity against HeLa cells, with ethanol and water extracts showing the greatest inhibition (>65% at 1000 µg/mL). GC-MS profiling identified solvent-specific bioactive compounds including sterols, terpenoids, polyphenols, and fatty acids. Notably, pharmacologically relevant compounds such as hinokione, ferruginol, ergosterol, and geranylgeraniol were detected. These findings demonstrate the therapeutic potential of G. lucidum, underscore the importance of solvent selection, and suggest that high-altitude ecological conditions may influence its bioactive metabolite profile. Full article