Search Results (65,369)

Energy-efficient wireless sensor networks (WSNs) rely on complex mathematical models to optimize critical operations such as coverage, routing, and energy harvesting. However, these equations impose diverse computational requirements: some demand rapid approximate methods to minimize overhead, while others require high-accuracy or even analytical solutions for precise optimization. This diversity introduces a key challenge: selecting the most suitable solving method for each equation type. This paper introduces the Argumentation-Based Equation-Solver Selector (ABESS), a decision-making framework that chooses a solver based on user-provided descriptors and also provides justification, by encoding rules, preferences, and contextual priorities. By leveraging computational argumentation, ABESS provides an adaptive and explainable approach to managing the resource-constrained nature of WSNs. Another contribution is a detailed functional behavior analysis of characteristic formulas in the WSN domain. This analysis on the one hand derives the descriptors for ABESS reasoning, e.g., verified localization intervals for design solutions, and on the other hand, cross-validates its performance. Thus, ABESS helps to avoid the use of failure-prone numerical methods and significantly improves computational efficiency. Empirical results across three core WSN models demonstrate the framework’s efficacy, including a 870× speedup in integer thresholding compared to uninformed exhaustive scanning. Full article

To advance sustainable development, China has introduced low-carbon city pilots (LCCP) and new energy demonstration city pilots (NEDC) as important institutional innovations. Using 2006–2023 panel data for 274 Chinese cities, we treat the dual-pilot policy of LCCP and NEDC as a quasi-natural experiment. We measure carbon emission performance (CEP) via a super-efficiency SBM-GML index incorporating social welfare and undesirable outputs, and use double machine learning (DML) to estimate the policy’s impact on CEP. We find the dual-pilot policy is associated with significantly improved urban CEP, with a stronger effect than either single pilot alone. Mechanism tests suggest the policy may contribute to improved CEP by promoting green technology innovation, industrial structure upgrading, and energy efficiency. Heterogeneity test results demonstrate that the dual-pilot policy yields more pronounced impacts in cities characterized by higher economic development, weaker path dependence, and more stringent environmental governance. Additionally, negative cross-regional spatial spillovers are identified. Different from the existing literature, this study integrates social welfare dimensions into CEP’s measurement framework and further validates that the dual-pilot policy generates more outstanding efficiency benefits compared with separate LCCP and NEDC pilots Full article

The growing demand for energy-efficient urban rail transit has led to the increasing deployment of reversible substations (RS) in traction power supply systems. These substations, equipped with bidirectional converter devices (BCDs), involve high initial costs and complex parameter optimization challenges. This paper presents a coordinated optimization method for BCD-equipped RS using a two-layer model. In the upper layer, the model determines the siting of RS and the capacity of BCD to minimize life-cycle cost (LCC). In the lower layer, it adjusts the control parameters of BCDs to reduce annual operating cost. An improved salp swarm algorithm (ISSA), incorporating Tent chaotic mapping and Levy flight, is developed to solve the model. A case study based on an 18.2 km subway line shows that the optimized configuration reduces overall cost by 5.12% and electricity cost by 10.53% compared with a conventional rectifier system. Moreover, it achieves a 1.19% reduction in electricity cost over a system with fixed control parameters, while maintaining rail potential and catenary voltage within safe limits. These findings demonstrate that the proposed method strikes an effective balance between initial investment and long-term operational benefits, contributing to improved energy efficiency and economic performance. Full article

In the renewable energy-driven “green electricity–green hydrogen–green ammonia” pathway, the development of low-temperature and low-energy-consumption ammonia synthesis technologies is of great significance. In this work, a plasma-catalytic ammonia synthesis system was established using a coaxial dielectric barrier discharge (DBD) reactor. The effects of different catalysts, including Ag, Cu, γ-Al₂O₃, BaTiO₃ and Co/BaTiO₃, Ni/BaTiO₃ on ammonia synthesis performance were systematically investigated. The reaction process was analyzed using voltage–current waveforms, Lissajous figures, and optical emission spectroscopy (OES). The results show that different catalytic systems have a significant influence on ammonia synthesis performance, with the promotional effect ranked as follows: Ni/BaTiO₃ > Co/BaTiO₃ > BaTiO₃ > Ag > γ-Al₂O₃ > Cu. Among them, Ni/BaTiO₃ exhibited the best performance. Under the conditions of N₂:H₂ = 1:1 and a gas flow rate of 2.5 L/min, the NH₃ synthesis rate reached 259.48 μmol/min, and the maximum energy efficiency reached 1.40 g-NH₃/kWh. Catalyst characterization results indicate that the BaTiO₃ support maintained a stable crystal structure, while the loaded metal species were highly dispersed and uniformly distributed on the support surface, which is beneficial for the adsorption and conversion of reactive species on the catalyst surface. Discharge characteristic analysis shows that the introduction of BaTiO₃ enhanced the local electric field and improved the uniformity of micro-discharges, while the further incorporation of metal active components strengthened the micro-discharge behavior. OES results reveal that the intensities of characteristic emission lines, such as NH, N₂⁺, and Hα, were significantly enhanced in the Ni/BaTiO₃ system, facilitating the formation and conversion of NH_x intermediates. The superior performance of Ni/BaTiO₃ is attributed to the coupling between BaTiO₃-induced dielectric enhancement and Ni-promoted surface hydrogenation and NH₃ desorption. This work provides mechanistic insight into catalyst-dependent DBD plasma-catalytic ammonia synthesis and offers an experimental basis for the further optimization of plasma-based ammonia production. Full article

As declared in the European Green Deal, the decarbonization of the EU energy system is essential for achieving Europe’s climate neutrality targets, demanding a substantial expansion of renewable energy sources and the rapid phase-out of coal and gas. It is therefore essential that newly installed PV products within the EU are designed to avoid creating additional environmental burdens due to environmental impacts during production and at the end of life (EOL) of photovoltaic (PV) modules. This study presents a life cycle assessment (LCA) of sustainable/green PV module designs in terms of recyclability using advanced high-quality recycling technologies. It compares two product systems both based on mono c-Si PV technology and the glass–glass (G–G) module design: 1. Passivated Emitter and Rear Contact (PERC) and 2. Tunnel Oxide Passivated Contact (TOPCon) cell technologies, which are assessed under production scenarios in China and Germany, and two recycling scenarios (hypothetical high-recovery recycling and partial recycling) using inventory data from eco-invent and literature sources. The results across most impact categories show that the PERC and TOPCon module designs produced in Germany with high-recovery recycling as the end-of-life strategy exhibit lower impacts than those produced in China with partial recycling as the end-of-life strategy under the adopted assumptions such as electricity mix and end-of-life modelling choices for module-only impacts (excluding BOS components). The climate change results show that TOPCon cell design under high-recovery recycling yields 10.4% lower emissions than the PERC cell design under partial recycling in Germany and 9.7% lower in China. However, both module designs emit 26.6% and 27.2% less GHG emissions when produced in Germany compared to production in China, respectively, which is line with earlier studies. With the exception of human toxicity, both PERC and TOPCon cell technologies perform better in this study than previously reported in reviewed LCA studies, reflecting the use of more recent state-of-the-art industry data concerning manufacturing requirements. The sensitivity analysis carried out on the design changes and electricity grid mix available shows that any improvements in the design process and increases in renewable energy penetration into the grid corresponds to a proportional reduction in environmental impacts across all impact categories. Full article

This perspective focuses on the field of solid waste recovery and resource utilization for end-of-life (EoL) wind turbine blades. Wind energy plays a central role in the global transition toward low-carbon energy systems owing to its technological maturity, scalability, and widespread resource availability. As global installed wind power capacity exceeded 1000 GW in 2024, improving the life-cycle energy efficiency and resource productivity of wind energy systems has become increasingly important. In this context, wind turbine blades (WTBs), the most material-intensive components with high embodied energy, are approaching large-scale end-of-life replacement, with global EoL blade waste projected to reach 2–4 million tons by 2030. Although blades may reach the end of their structural service life, they contain substantial quantities of reinforcing fibers and polymeric matrices that embody significant material and manufacturing energy. Integrating blade recycling into the wind energy value chain represents a critical opportunity to reduce dependence on energy-intensive virgin materials and lower life-cycle energy consumption and associated carbon emissions. However, the realization of energy-efficient circular utilization remains constrained by several challenges, including inefficient heat and mass transfer during blade depolymerization, limited valorization of resin-derived products, and performance degradation of recovered fibers. This perspective examines the material characteristics of blades from a life-cycle energy utilization standpoint, assesses existing recycling pathways, and identifies key technological and system-level bottlenecks. Emphasis is placed on process intensification, product upgrading, and design-for-circularity strategies to support the long-term sustainability of wind power systems. Full article

This study proposes a comprehensive techno-economic methodology to assess the economic viability and optimal sizing of grid-connected residential photovoltaic (PV) self-consumption systems without storage in emerging economies. The model uses net present value (NPV) as the optimization criterion and estimates internal rate of return (IRR) and discounted payback time (DPBT) as complementary profitability indicators. It integrates hourly PV generation, synthesized hourly demand profiles, local tariff structures, surplus-energy remuneration, investment and operating costs, inflation, performance losses, and discount-rate assumptions, while explicitly accounting for context-specific limitations related to data availability, storage-free operation, and financing assumptions. The methodology is applied to 30 Colombian residential scenarios, covering five cities and six socioeconomic strata, and is complemented with a replicability case in Jaén, Spain. In Colombia, PV self-consumption is economically viable in all cases, but profitability is highly uneven: maximized NPV ranges from 2.8 € in the least favorable low-income case to 2816 € in the best high-income case, IRR ranges from 5.0% to 14.7%, and DPBT ranges from 8 to 24 years. From an energy-justice perspective, tariff subsidies improve affordability but may reduce PV attractiveness for low-income users, highlighting the need for capital grants, low-interest loans, or community solar schemes. Full article

Anaerobic digesters (ADs) are widely used for the recovery of energy from biomass waste, while performance deterioration of ADs sometimes occurs under high organic loads. Microbial electrolysis cells (MECs) have been examined for incorporation into ADs to improve methane production, while responses of MEC-assisted ADs (MEC-ADs) to changes in operational conditions have yet to be sufficiently examined. Here we operated laboratory ADs and MEC-ADs with food waste as a feed, and organic loading rates (OLRs) were varied by changing hydraulic residence times (HRTs). Analyses of AD performances, including methane production and chemical oxygen demand (COD) removal, show that MEC-ADs exhibit higher performances than ADs at OLRs of 7 g COD L⁻¹ D⁻¹ or higher (HRT of 10 days or less). In addition, pH was stably maintained in MEC-ADs at high OLRs. Metabarcoding of rRNA gene amplicons showed that Desulfuromonadaceae bacteria were enriched at the anodes in MEC-ADs, while Methanobacteriaceae archaea were increased at the cathodes. It is suggested that the MEC system is useful for stably operating ADs at high OLRs and/or short HRTs. Full article

Machine learning’s computational demands necessitate optimal performance and utilization across diverse hardware architectures. This research compares computing as spiking neural networks (CSNNs, or simulated neuromorphic computing) and regular CNNs on Apple Silicon M3 Pro with Metal Performance Shaders (MPS), and NVIDIA RTX 3070 GPU with CUDA. We run Convolutional Spiking Neural Networks (CSNNs) and traditional CNNs on two datasets (frame-based CIFAR-10; and sequential event-based DVS) to evaluate the suitability of neural net architectures and platforms for different data problems. For both CSNNs and traditional CNNs, Apple Silicon with MPS delivers better energy efficiency but longer processing times for training and inference. NVIDIA with CUDA offers faster computation in training and inference at higher energy costs for CNNs. For CSNNs, frame-based data (CIFAR-10) significantly degraded performance when proper temporal encoding was absent, while event-based data (DVS) proved more naturally suited to the CSNN architecture than frame-based inputs. Though CNNs still achieved higher empirical accuracy in the reported experiments. CSNNs also performed better on Apple Silicon (with MPS) for the sequential event-based data. RAM utilization patterns favored Apple Silicon (with MPS) across both data experiments. The CSNN architecture demanded higher memory resources than CNN, regardless of platform and dataset. NVIDIA (with CUDA) was less energy efficient for spiking neural networks (CSNNs) as compared to Apple Silicon (with MPS). We also compared how the number of time steps affects accuracy and energy consumption across hardware platforms, finding that higher accuracy correlates with energy costs as time steps increase; the accuracy-energy relation seems linear for frame-based data, while for event-based data the energy consumption remains stable increasing at higher time steps. Our cross-platform performance analysis of spiking and regular neural network architectures highlight the importance of matching platform-architecture combinations to a dataset and application requirements. Full article

For the removal of hexavalent chromium [Cr(VI)] from drinking water, a hybrid biosorbent designated chitosan–natural diatomaceous earth (CNDE) was developed and thoroughly characterized. The material couples the ion-exchange and chelating capacity of chitosan—applied at an 85% degree of deacetylation—with the high-surface-area mineral framework of natural diatomaceous earth, onto which the polymer was deposited as a conformal coating. Surface morphology and internal microstructure were examined by scanning and transmission electron microscopy (SEM/TEM), while elemental composition across the hybrid matrix was resolved by energy-dispersive X-ray spectroscopy (EDX). Fourier transform infrared (FTIR) spectroscopy was employed to identify the surface functional groups responsible for chromate binding, and streaming current measurements established the pH of zero charge (pH_pzc), which governs the electrostatic environment at the sorbent–solution interface. Specific surface area was quantified by the Brunauer–Emmett–Teller (BET) method, and the balance of surface acidic and basic sites was determined through titrimetric analysis of total acidity and alkalinity. Thermogravimetric analysis (TGA) was conducted to assess thermal stability. Batch equilibrium isotherm experiments were performed to evaluate Cr(VI) uptake from model drinking water prepared using dilute potassium dichromate solutions adjusted to target pH levels. The effects of solution pH and competing anions (chloride and sulfate) were also investigated. Kinetic studies were conducted to determine the rate of Cr(VI) adsorption, and residual metal concentrations were measured using inductively coupled plasma mass spectrometry (ICP-MS). Results indicated that CNDE containing 30% chitosan (CNDE30) achieved effective Cr(VI) removal at pH 5. Adsorption was strongly pH-dependent, decreasing as pH increased from 5 to 8. Equilibrium data were well described by both Langmuir and Freundlich isotherm models, while kinetic data followed a pseudo-second-order model. The presence of chloride ions (15 mg/L) reduced adsorption capacity by approximately one-third, whereas sulfate at the same concentration significantly inhibited Cr(VI) removal. Overall, the isotherm results suggest that CNDE30 is a promising material for Cr(VI) removal from drinking water. Its cost-effectiveness, ease of synthesis, and potential for reuse make it particularly attractive for small-scale and decentralized water treatment applications. Full article

SiO₂ aerogels are promising candidates for energy-efficient glazing because of their low thermal conductivity and optical transparency; however, conventional formulations often fail to reconcile optical, thermal, and mechanical performance. This work aimed to resolve this bottleneck via controllable sol–gel synthesis and ambient pressure drying. Using methyltrimethoxysilane (MTMS) as the single silicon source, this study systematically explored the effects of alkaline catalyst type, water-to-MTMS ratio, and surfactant selection, and further developed an MTMS–dimethyl dimethoxy silicane (DMDMS) composite silicon source. Tetramethylammonium hydroxide (TMAOH) catalysis, a water-to-MTMS molar ratio of 7:1, and Pluronic F-127 (F127) surfactant yielded a uniform, hydrophobic aerogel with 93.50% porosity and 89.74% transmittance at 800 nm. The optimized composite system (MTMS:DMDMS = 9:1, 6 mL water, 2.0 g F127) enhanced compressive strength by 22.4% relative to pure MTMS aerogel, with 70.15% visible transmittance and thermal conductivity of 0.027 W/(m·K). These results demonstrate that multi-parameter formulation control can achieve a practical balance among mechanical robustness, optical transparency, and thermal insulation. This study provides a theoretical and process foundation for the engineering application of high-performance transparent thermal insulation materials. Full article

A structurally simple three-layer optical absorber is proposed and systematically investigated, consisting of a continuous Ti ground plane, a SiO₂ dielectric spacer, and a Ti tetrahedral nanostructure. The absorber is constructed on a periodic square unit cell, where the lateral dimension directly determines the base width and sidewall inclination angle of the tetrahedral structure, thereby enabling effective modulation of the optical response. Full-wave electromagnetic simulations performed using COMSOL Multiphysics (version 6.0) are employed to evaluate the influence of geometric parameters on broadband absorption behavior. The optimized structure achieves a near-unity absorptivity of 0.9999 at 200 nm and maintains an effective absorption bandwidth (absorptivity > 0.9) spanning 200–3000 nm, covering the ultraviolet, visible, and near-infrared spectral regions. Parametric analysis reveals that the tetrahedral height primarily governs long-wavelength extension through enhanced optical path length, graded-index transition, and improved electromagnetic field confinement, while the unit cell width strongly influences impedance matching and localized field localization. In contrast, the Ti ground layer thickness exhibits minimal influence once it exceeds the optical skin depth, confirming its primary role as a transmission-blocking reflective substrate. Impedance retrieval analysis shows that the real part of the normalized impedance remains close to unity and the imaginary part approaches zero over most of the operating range, demonstrating that the ultrabroadband absorption behavior is dominated by effective impedance matching rather than isolated narrowband resonances. Furthermore, electric and magnetic field distribution analyses reveal that electromagnetic energy dissipation is concentrated near the tetrahedral apex and metal–dielectric interfaces, indicating the coexistence of localized plasmonic modes, cavity-assisted absorption, and multi-scale optical confinement. Full article

The relationship between the position of the thiazole-5H proton signal and the presence of various substituents in the molecule was investigated in detail from an experimental and theoretical point of view. For this purpose, twenty 2,4-disubstituted thiazole derivatives were carefully chosen and synthesized, and their NMR spectra were recorded. Density functional theory calculations of ¹H NMR chemical shifts, frontier molecular orbitals, and molecular electrostatic potential surfaces were performed. The position of the thiazole-5H proton signal in the NMR spectrum is shown to strongly depend on the type and position of substituents in the molecule. Based on the obtained results, we can conclude that compounds with the smallest values of thiazole-5H proton shift are simultaneously those with small electron affinity, ionization potential and molecular electronegativity values, while compounds with the largest values of thiazole-5H proton shift have large electron affinity, ionization potential, and molecular electronegativity and a small HOMO-LUMO energy gap. These relationships become less clear in the case of compounds with intermediate values of the proton shift. Present research is a step towards an easy-to-use tool for predicting electronic effects in materials containing thiazole, based on the position of the thiazole-5H proton NMR signal. Full article

Industrial maintenance has increasingly evolved into a strategic function for improving asset reliability, extending asset lifecycle, and supporting sustainability objectives. However, the literature remains fragmented, with limited integration between digital twins, maintenance practices, and sustainability-oriented decision-making. To address this gap, the study performs a systematic review of 49 publications indexed in Scopus and Web of Science and introduces an integrative conceptual framework for Sustainable Maintenance 4.0. The analysis explores the role of digital twins, as a key enabling technology within the Industry 4.0 landscape, in supporting the shift from reactive and schedule-based maintenance toward predictive and prescriptive strategies. The findings suggest that digital twins can enhance maintenance decision-making, improve asset reliability, and contribute to lifecycle optimization. The reviewed studies also report improvements in operational and energy performance, although these effects vary according to digital maturity, system configuration, and implementation scope. In addition, digital twins may support safer operations and workforce development through data-driven and immersive environments. Despite these benefits, challenges remain, including high investment requirements, interoperability limitations, cybersecurity risks, and the need for interdisciplinary skills. The proposed framework positions digital twins as a mediating element between physical assets, data acquisition, advanced analytics, maintenance services, and sustainability outcomes. Full article

Synchronous machines used in wind turbines typically use rare earth permanent magnets (PMs) due to the possibility of high power densities and efficiencies. However, alternative non-PM topologies are gaining popularity due to the cost and supply volatility of PMs. Wound-field flux-switching machines (WFFSMs), although boasting high torque densities and being PM-free, have lower power densities than PM machines. However, a double-stator wound-field flux-switching machine (DSWFFSM) exemplifies even greater power density. This study investigates the application of DSWFFSMs for direct-drive wind applications. Furthermore, the performance of an optimized 3 MW DSWFFSM design is compared with a single-stator WFFSM design. Both designs are based on the volume of a single-stator PM flux-switching machine from the literature. Although the torque per weight for the DSWFFSM and the single-stator WFFSM are similar, the torque per volume for the DSWFFSM is shown to be significantly exceptional. The torque ripple in the DSWFFSM is also smaller, but the efficiency is slightly lower than the single-stator WFFSM. The DSWFFSM design, which is shown to be comparable to PM-based topologies in terms of power density, highlights a low-cost, sustainable, clean energy generator topology. Full article