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The rapid demand for sustainable and efficient energy storage solutions has prompted the pursuit of eco-friendly electrode materials. Biomass-derived carbons from food waste offer a promising pathway to meet this need by combining waste valorization, environmental benefits, and high electrochemical performance. This review highlights that food waste biomass is an effective and inexpensive source of precursors for producing high-performance carbon materials for supercapacitors. Food waste, which includes fruit peels and vegetable residues, cereal husks, and oilseed residues, is a good source of lignocellulosic components, heteroatoms, and structural features that determine the electrochemical characteristics of the derived carbons. These wastes produce hierarchically porous carbons with high surface areas (>1500 m² g⁻¹) on pyrolysis and activation that provide superior ion transport, wettability and pseudocapacitive behaviour. Their electrochemical performance includes capacitances up to 520 F g⁻¹ and energy densities of 35–70 Wh kg⁻¹ in optimized systems, particularly under extended voltage windows or in hybrid supercapacitor configurations, and high cycling stability is equal to or even better than traditional carbons such as activated carbon and graphene. Additionally, biomass valorization contributes to a high level of greenhouse gas capture, decreases landfill, and correlates with the idea of a circular economy. The commercialization potential of biomass-based supercapacitors is supported by recent developments in AI-based optimization, combined with scalable synthesis methods, which would support ecologically, economically, and technologically sustainable energy storage on a large scale. Full article

Soil moisture critically governs terrestrial energy and water cycles. Precise monitoring of soil water content is essential for precision agriculture, drought early warning, and water resource management. Ground-based observations offer limited spatial coverage, and satellite remote sensing generally lacks high spatial resolution. Unmanned aerial vehicle (UAV) remote sensing, which provides centimeter-level spatial detail, can effectively address this gap and has therefore attracted considerable attention in soil moisture inversion research. Using CiteSpace, we performed a bibliometric analysis of 97 Chinese papers from the China National Knowledge Infrastructure (CNKI) and 321 English papers from the Web of Science Core Collection (2014–2025). The field has expanded rapidly since 2018, with China occupying a leading role. Domestically, Northwest A&F University represents a major research cluster, while the Chinese Academy of Sciences leads internationally. Key research topics include UAVs, soil moisture, machine learning, hyperspectral sensing, canopy temperature, and precision agriculture. Research themes have progressed from reliance on vegetation indices and temperature data toward the integration of hyperspectral and thermal infrared measurements, and toward the use of machine learning approaches to improve inversion models and achieve more accurate estimations. This study delineates the classification and developmental context of a knowledge system for soil moisture inversion using UAV remote sensing. Current work concentrates on integrating multi-sensor data with machine learning, while future efforts will emphasize coupling physical mechanisms with deep learning. These findings offer researchers a clear view of the field’s frontiers and a basis for planning future studies. Full article

This research was motivated by the urgent need to address resource shortages and high energy costs in concrete production by replacing an energy-intensive traditional curing method with a new, more sustainable solution. By exploring solar heat treatment with composite binders and THACs, the study aimed to develop sustainable, cost-effective alternatives that harness renewable energy sources and optimize natural cement hydration processes for accelerated hardening. This article explores the potential application of solar energy in the production of precast concrete products using a composite binder. The effectiveness of the composite binder in solar thermal treatment of concrete using translucent heat-accumulating coatings is tested. The results of laboratory studies are presented, and the feasibility of using concrete based on composite binder at the laboratory scale for the production of concrete and reinforced concrete products, both with steaming and with solar thermal treatment, is established. The study of the structural features and basic physical and mechanical properties of hardened concrete under various conditions indicates that, under the investigated laboratory conditions, solar-thermally treated concrete exhibits physical and mechanical properties comparable to those of normally cured concrete. Laboratory studies confirmed the effectiveness of both steaming and solar heat treatment methods under controlled experimental conditions. Within the scope of the performed laboratory tests, the structure and properties of these concretes were comparable to those of normally cured concretes and, in several aspects, superior to those obtained under conventional steam curing regimes, which indicates the effectiveness of the described method, not only from the point of view of significant savings in fuel and energy resources. When producing products based on composite binders using solar thermal treatment, the consumption of the clinker portion of the binder is reduced by 50% (composition of the composite binder itself) and the consumption of conventional fuel during heat and moisture treatment is reduced by 70–100 kg per 1 m³ of concrete (reflecting process-level comparisons), which is of significant value for external energy demand. These findings confirm the technical feasibility and environmental advantages of the proposed method at the laboratory scale and highlight its potential for broader industrial application in precast concrete production. Full article

Offshore wind energy is an important source of clean energy. Single-post platforms, due to their simple structure and strong stability, can adapt to deep water environments through buoyancy and ballast systems, have small motion responses, and have low construction and maintenance costs. They are suitable for offshore wind energy development in deep-sea areas and help expand the application of offshore wind power. This paper conducts a coupled response analysis of offshore wind turbine foundations and mooring systems, as well as an optimization study on the form and number of mooring lines. Under the premise of considering the safety and economy of floating wind turbines, the mooring lines have been optimally arranged. The study calculates frequency-domain responses, time-domain responses, and mooring line forces under the constraints of the original three-line mooring system. Based on this benchmark, the study further optimizes the mooring forms and numbers for the same platform, analyzing four, six, and eight single mooring lines, as well as three groups of single-line, double-line, and triple-line mooring configurations. Finally, using AQWA software (2024 R1), the responses and mooring line forces of different mooring configurations were calculated, and the preferred mooring arrangement for this stepped single-post platform was determined to be a three-group, three-line system (a total of nine mooring lines). The mooring line tension decreased substantially from the original 3.2 × 10⁶ N to 1.8 × 10⁶ N, while the dynamic response was reduced to one-sixth of its original level. Meanwhile, this study provides strong support for the utilization of offshore wind energy and the construction of offshore wind turbine platforms and mooring systems. Full article

In most amorphous materials, the concentration of Urbach tail states is larger than the concentration of dangling bond states. However, absorption accounting for the Urbach tail while disregarding the dangling bonds is commonly used or derived by spectroscopic characterizations of amorphous films from a single spectrum, mostly due to the insufficient accuracy of such characterizations. This paper proposes an advanced envelope method (AEM) for transmittance spectrum T(λ), aiming to resolve this problem. The novelties in AEM are: improved preprocessing of T(λ), extending the envelopes deeper into the region of strong absorption (RSA), enhanced determination of the refractive index n(λ) in the region of weak absorption, optimization of both n(λ) and the extinction coefficient k(λ) in RSA, as well as analysis of the types of electron transitions and calculation of their energy gaps. Three single magnetron sputtered a-Si films deposited on glass substrates are characterized by AEM, and three other relevant methods that disregard deep-levels. The best accuracy is achieved when these films are characterized by AEM. It is demonstrated that the absorption coefficient α(λ) of each of these films distinguishes electron transitions via dangling bond states from those via tails states, and the DOS corresponds to the Mott–Davis model of amorphous materials. Full article

The article provides a comprehensive overview of the role of hydrogen as a key vector in the decarbonization of the global transport sector. The study situates hydrogen within the broader context of energy transition and climate neutrality targets, emphasizing its potential to replace fossil fuels in road, rail, maritime, and aviation applications. The analysis integrates a review of current technological, infrastructural, and policy developments, covering both combustion-based and fuel-cell hydrogen propulsion systems. Quantitative and qualitative data were assessed from international reports, scientific publications, and ongoing industrial projects to evaluate performance, efficiency, safety, and cost parameters such as Levelized Cost of Hydrogen (LCOH) and Total Cost of Ownership (TCO). The results indicate that while hydrogen remains economically challenging, technological progress in electrolysis, fuel cells, and refueling infrastructure significantly improves its competitiveness, particularly in heavy-duty and long-range transport. The paper highlights the critical role of international strategies, including the European Hydrogen Strategy and Fit for 55 package, in driving market adoption and regulatory alignment. The conclusions suggest that by 2050, hydrogen could contribute up to one-quarter of total transport energy demand, positioning it as a cornerstone of sustainable mobility and a bridge toward a fully decarbonized transport ecosystem. Full article

Direct ocean carbon capture (DOC) has emerged as a promising strategy for mitigating atmospheric CO₂ levels and addressing ocean acidification. Unlike direct air carbon capture methods, DOC leverages the ocean’s vast carbon storage capacity, offering a scalable and efficient route for carbon dioxide removal. This systematic comparative review categorizes existing DOC methods into three types: (1) biological carbon capture, which relies on photosynthesis by microalgae and marine microorganisms; (2) electrochemical carbon capture, which utilizes water electrolysis to generate H⁺ and OH⁻ ions for pH-driven CO₂ removal; and (3) physical carbon capture, which employs hollow fiber membranes to directly separate CO₂ from seawater. For each technology, we evaluate efficiency, energy consumption, cost, technology readiness level (TRL), scalability, and major challenges. By integrating recent pilot data and providing a critical assessment, this review offers a roadmap for future research in direct seawater CO₂ capture. The comparative analysis reveals that electrochemical methods achieve the highest efficiency (60–85%) but face membrane fouling and electrode degradation challenges, while biological methods offer low-energy operation but suffer from slow kinetics and high harvesting costs, and membrane-based methods provide high removal rates (up to 94%) but require improved fouling resistance. Full article

High-frequency volatility and extreme tail risks in offshore wind power pose severe challenges to grid stability and economic operation. Conventional storage planning often relies on deterministic profiles or static allocation rules, failing to capture the non-stationary temporal dynamics of marine wind resources. To bridge this gap, this paper proposes a closed-loop framework that integrates ultra-short-term probabilistic forecasting with dynamic hybrid energy storage optimization. A novel Dual-Channel Residual Network is developed to provide well-calibrated predictive uncertainty quantification, which explicitly drives a Prediction-Guided Dynamic Hybrid Storage Optimization Framework. By dynamically coordinating lithium-ion batteries and liquid air energy storage based on evidential predictive variance, the proposed approach achieves superior synergy between short-term power response and long-duration energy shifting. Case studies on an offshore wind farm validate that the framework significantly reduces the Levelized Cost of Energy and loss-of-load risks while enhancing frequency regulation capabilities compared to state-of-the-art benchmarks. Full article

This study presents a combined numerical and experimental investigation of transient multiphase compressible flow inside a profiled-rotor rotary volumetric compressor. While most existing studies rely on high-fidelity CFD approaches, a low-order thermodynamic chamber-based model implemented in MATLAB Release 2023a is proposed to predict the temporal evolution of pressure, temperature, and vapor volume fraction during the compression cycle. The model is based on mass and energy conservation applied to variable-volume control chambers and incorporates a simplified cavitation criterion derived from local pressure relative to saturation vapor pressure. An open-loop experimental test bench was developed to measure air mass flow rate, suction and discharge pressures, temperatures, torque, and shaft power under controlled operating conditions. These measurements are used to validate the numerical predictions. The results show good agreement between measured and simulated pressure levels and global performance indicators, with deviations quantified using mean absolute percentage error values remaining below 5% over the investigated operating range. The numerical analysis further reveals the occurrence of localized low-pressure zones during the suction phase, indicating incipient cavitation or microbubble formation at specific rotor positions. The proposed modeling approach provides a computationally efficient alternative to full CFD simulations and enables rapid parametric analysis of rotor geometry and operating conditions. The cavitation formulation does not aim to resolve detailed bubble dynamics or erosion mechanisms, but rather to identify cavitation tendency based on thermodynamic pressure thresholds. Full article

Compressed air systems (CASs) represent a significant portion of energy consumption in large-scale built environments and manufacturing facilities, suffering from both micro-level physical pipeline leaks and macro-level operational inefficiencies. This paper proposes a unified, dual-action artificial intelligence framework aimed at advancing building decarbonization by systematically integrating acoustic-vision leak quantification with schedule-aware machine learning. Specifically, the framework targets pneumatic pipe connection leaks, fitting leaks, and joint degradation faults within compressed air distribution networks, which are the primary sources of micro-level volumetric energy losses in industrial building systems. First, a probabilistic multimodal fusion algorithm (MPSF) using an ultrasonic camera is developed to detect and geometrically quantify physical leaks, successfully translating pixel areas into physical facility energy loss metrics (estimating 11.0 kW of wasted power from detected severe leaks). Second, to optimize the compressor’s supply matching the actual facility demand without risking data leakage from internal flow sensors, an eXtreme Gradient Boosting (XGBoost) model is proposed. By utilizing only external building environmental conditions and the real-time operational schedules of 13 distinct zones, the model achieves highly accurate dynamic power prediction (R² = 0.9698). Finally, comprehensive simulations based on real-world digital monitoring data from a facility-scale built environment demonstrate that only the concurrent application of both modules ensures stable end-point pressure. The integrated framework achieves a substantial system-wide building energy reduction of over 20% to 40% compared to baseline constant-pressure operations, yielding an estimated annual reduction of 116 tons of CO₂ emissions, thereby providing a direct pathway toward carbon-neutral building operations. Full article

Coastal ecosystems, particularly semi-enclosed gulfs, are increasing anthropogenic pressures from urbanization and industrialization with profound impacts on biodiversity maintenance, energy transfer, and biogeochemical cycling. However, how metazoan communities—key components of marine food webs—respond to spatiotemporal variability and human disturbance remains insufficiently understood. This study applied eDNA metabarcoding targeting the mitochondrial COI gene to investigate metazoan communities across 68 stations in the Beibu Gulf, spanning bay, coastal, and island regions, during wet and dry seasons. In total, 878 metazoan ASVs from 13 phyla were detected. Arthropoda dominated both seasons (wet: 85%; dry: 55%), whereas Chordata increased during the dry season (wet: 0.16%; dry: 37%). At the α-diversity level, diversity peaked in the bay region during the dry season and shifted toward the coastal region during the wet season. At the β-diversity level, community composition differed significantly between seasons and spatial regions, with seasonal variation exerting a stronger influence than spatial differentiation. Co-occurrence networks revealed higher complexity during the dry season. β-diversity was overwhelmingly driven by species turnover (94.4%). The island region exhibited the highest community uniqueness, while the human-impacted bay region showed reduced distinctiveness. Redundancy analysis further identified anthropogenically influenced inorganic nitrogen, together with water temperature, transparency, and salinity, as key environmental drivers shaping community structure. βNTI analysis indicated that community assembly was governed by the combined effects of deterministic and stochastic processes. Overall, this study highlights how environmental gradients and human pressures jointly regulate metazoan dynamics, providing insights for biodiversity conservation in human-impacted coastal seas. Full article

This study develops an integrated vessel-level framework for assessing logistics performance and operational energy efficiency in container shipping. The novelty of the study lies in the development of a unified analytical approach that explicitly integrates logistics indicators with fuel consumption and emissions within a consistent system boundary, including auxiliary engine operation during both sea passages and port stays. The framework is applied to four medium-sized container vessels (6000–7500 TEU; 20-foot equivalent unit) under normalised operating conditions. The results show that higher capacity utilisation and economies of scale significantly improve both cost and energy performance, while emissions intensity varies by more than twofold across vessels. A deterministic sensitivity analysis is applied to evaluate the influence of key operational parameters. The analysis identifies service speed as the dominant driver, followed by vessel loading rate, while port-related parameters—such as auxiliary engine load and port productivity—have a lower yet still measurable influence, reducing emissions by up to 5% under improved conditions. The main contribution of the study is the development of a practical vessel-level benchmarking tool that captures logistics–energy interactions and supports operational decision-making under current regulatory frameworks, including EU ETS, FuelEU Maritime, and the IMO Carbon Intensity Indicator (CII). Full article

This paper examines the subjective annoyance associated with shared-bike electronic alert sounds (SBeASs), an emerging urban noise source. A study was conducted by employing extensive questionnaire surveys and psychoacoustic experiments. A preliminary survey (N = 1340) indicated that 90.6% of participants reported being impacted by SBeASs, with pronounced effects on nighttime rest and daytime work efficiency. In this study, SBeAS samples were taken from three prominent Chinese bike-sharing brands: Hello Bike, Meituan Bike, and DiDi Bike. Under laboratory conditions, subjective annoyance assessments (N = 28) for SBeASs were conducted at controlled sound pressure levels (SPLs) ranging from 45 to 65 dBA, with occurrence frequencies of 1, 3, and 5 s. Simultaneously, annoyance assessments were also conducted for two reference noise types: traffic noise and street noise. The results indicated a notable increase in annoyance levels related to SBeASs with rising SPL and increased occurrence frequency. Minor variations in annoyance were identified among different bike-sharing brands, which can be attributed to their distinct acoustic features. When the SPL was above 55 dBA, the DiDi Bike SBeASs produced considerably higher annoyance than those of other brands. This can be attributed to its elevated low-frequency energy, loudness, and roughness. Moreover, individuals exhibiting increased sensitivity to noise reported notably higher annoyance ratings on the SBeAS scale (p = 0.019). Under low-SPL conditions (45–55 dBA), the annoyance attributed to frequent SBeASs can exceed that caused by traffic noise and street noise at comparable SPLs, highlighting the distinct disruptive impact of abrupt sound sources. Full article

Urban agglomerations have become the dominant spatial platform of urbanization, regional coordination, and economic transformation in China. Yet whether the expansion of agglomeration scale at the urban-agglomeration level alleviates or intensifies energy use remains insufficiently understood. Extending the scale of analysis from individual cities to integrated urban agglomerations, this study investigates 64 cities in four major Chinese urban agglomerations, including Beijing–Tianjin–Hebei, the Yangtze River Delta, the Pearl River Delta, and Chengdu–Chongqing, over the period 2006–2023. Using panel data models, this study examines the impact of the scale agglomeration within urban agglomeration on urban energy intensity. The results show that the overall agglomeration scale generated by urban agglomeration formation significantly suppresses energy intensity while indicating a robust energy-saving effect: every 10% increase in agglomeration scale is associated with a decline of approximately 0.0893 million tons of standard coal per CNY 100 million of GDP. This finding remains stable after addressing endogeneity concerns and performing a series of robustness checks. Mechanism analyses further suggest that this effect operates primarily through talent agglomeration, technological progress, and public transportation expansion. In addition, the energy-saving effect is more pronounced in smaller cities, cities with lower administrative rank, cities with weaker factor mobility, and cities characterized by poorer air quality but stronger public environmental attention. These findings contribute to the literature on urban agglomeration and green development by showing that the agglomeration scale within urban agglomerations can generate inclusive energy-efficiency gains, especially for relatively disadvantaged cities, thereby offering important implications for spatial governance and low-carbon transition in rapidly urbanizing economies. Full article

Asymmetric Cascaded Multilevel Inverters (ACMLIs) have emerged as a prominent solution for medium- and high-power applications due to their ability to provide an increased number of output voltage levels with fewer power switches. However, maintaining low total harmonic distortion (THD) and ensuring robust stability under varying operating conditions remain significant challenges. This study experimentally validates a voltage-feedback Proportional-Resonant (PR) control strategy for a seven-level ACMLI. Unlike conventional current-feedback methods, the proposed approach directly regulates the output voltage, providing superior harmonic suppression and enhanced steady-state accuracy. The stability and dynamic performance of the controller were theoretically analyzed using Bode diagrams and root locus methods, and further verified through the MATLAB Curve Fitting Tool (CFT) with a high correlation (R² = 0.9989). Experimental results demonstrate that the integration of the PR controller significantly improves power quality, reducing the current THD from 6.55% to 3.68% and the voltage THD to 2.94%. These findings confirm that the system fully complies with IEEE 519 standards and outperforms several existing strategies in the literature. The results establish the voltage-feedback PR control as a robust, high-precision, and practical alternative for power quality-oriented multilevel inverter applications in modern energy systems. Full article