Search Results (8,324)

The growing demand for lithium, driven by its key role in rechargeable batteries and its use in electric vehicles, highlights the need for sustainable and environmentally friendly recovery strategies. Conventional methods, such as pyrometallurgy and hydrometallurgy, are effective but costly and harmful as they emit toxic compounds. Biohydrometallurgy has emerged as a promising alternative, as it uses microorganisms and their metabolites to solubilize metals under milder conditions. Biohydrometallurgy has emerged as a promising alternative, as it relies on microorganisms and their metabolites to solubilize metals under mild operating conditions. Nevertheless, challenges related to process efficiency and selectivity remain, particularly for lithium recovery. In this context, recent advances in metal-binding peptides have attracted increasing attention due to their inherent selectivity and the possibility of rational design and heterologous expression in well-established microbial hosts such as Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae. This review critically analyzes current biotechnological strategies and explores the integration of microbial bioleaching with peptide-based approaches as a complementary and environmentally friendly framework for the selective recovery of lithium and other metals from spent batteries and waste electrical and electronic equipment. Overall, this review provides an integrative conceptual framework that highlights the potential of combining microbial processes with metal-binding peptides to guide the development of more selective and sustainable biotechnological strategies for lithium recovery from secondary sources. Full article

The increasing electrification of mobility within smart cities has accelerated the need for intelligent energy management strategies that jointly address cost, emissions, and battery health. This study develops a health-aware hybrid reinforcement–predictive energy manager (H-RPEM) designed for photovoltaic–electric vehicle (PV-EV) microgrids. The proposed controller unifies model-based predictive optimisation with adaptive reinforcement learning to achieve both short-term operational efficiency and long-term asset preservation. A comprehensive dataset of solar generation, EV charging behaviour, and stochastic load profiles was employed to train and validate the hybrid control framework under realistic operating conditions. Quantitative results indicate that the proposed H-RPEM controller achieves an 18.7% reduction in total operating cost and a 22.5% decrease in carbon emissions, whilst maintaining the battery state-of-health above 0.95 throughout a 24 h operational cycle. When benchmarked against standard predictive control, the hybrid strategy converges 30–40 episodes faster and delivers a 25% improvement in reward stability, demonstrating enhanced robustness and learning efficiency. The results confirm that H-RPEM achieves robust and balanced performance across economic, environmental, and technical domains, establishing it as a scalable and health-conscious control solution for next-generation smart city microgrids. Full article

Dust accumulation on photovoltaic (PV) modules is a major factor contributing to reduced power output, lower efficiency, and accelerated material degradation, particularly in arid and industrialized regions. This study presents a comprehensive review and analysis of the influence of dust deposition on PV performance, covering its optical, thermal, and electrical impacts. Findings from global literature indicate that dust-induced efficiency losses typically range from 10% to 70%, depending on particle characteristics, environmental conditions, and surface orientation. Experimental and modeled I–V and P–V characteristics further reveal significant declines in current and power output as soiling levels increase. Through an extensive literature assessment, this paper identifies Machine Learning (ML)-based approaches as emerging and highly effective techniques for dust detection and mitigation. Recent studies demonstrate the integration of image processing, drone-assisted monitoring, and convolutional neural networks (CNNs) to enable automated, real-time soiling assessment. These intelligent methods outperform conventional manual and time-based cleaning strategies in accuracy, scalability, and cost efficiency. By synthesizing current research trends, this review highlights the growing role of ML and data-driven technologies in enhancing PV system reliability, informing predictive maintenance, and supporting sustainable solar energy generation. Full article

The growing global demand for food and energy requires land-use strategies that support agricultural production and renewable energy generation. Agrivoltaic (APV) systems allow farmland to be used for both agriculture and solar power generation. The aim of this study is to critically synthesize the interactions between the key dimensions of APV implementation—technical, agronomic, legal, and economic—in order to create a multidimensional framework for designing an APV optimization model. The analysis covers APV system topologies, appropriate types of photovoltaic modules, installation geometry, shading conditions, and micro-environmental impacts. The paper categorizes quantitative indicators and critical thresholds that define trade-offs between energy production and crop yields, including a discussion of shade-tolerant crops (such as lettuce, clover, grapevines, and hops) that are most compatible with APV. Quantitative aspects were integrated in detail through a review of mathematical approaches used to predict yields (including exponential-linear, logistic, Gompertz, and GENECROP models). These models are key to quantitatively assessing the impact of photovoltaic modules on the light balance, thus enabling the simultaneous estimation of energy efficiency and yields. Technical solutions that enhance synthesis, such as dynamic tracking systems, which can increase energy production by up to 25–30% while optimizing light availability for crops, are also discussed. Additionally, the study examines regional legal frameworks and the economic factors influencing APV deployment, highlighting key challenges such as land use classification, grid connection limitations, investment costs and the absence of harmonised APV policies in many countries. It has been shown that APV systems can increase water retention, mitigate wind erosion, strengthen crop resilience to extreme weather conditions, and reduce the levelized cost of electricity (LCOE) compared to small rooftop PV systems. A key contribution of the work is the creation of a coherent analytical design framework that integrates technical, agronomic, legal and economic requirements as the most important input parameters for the APV system optimization model. This indicates that wider implementation of APV requires clear regulatory definitions, standardized design criteria, and dedicated support mechanisms. Full article

The use of full-battery electric vehicles is an essential strategy for reducing greenhouse gas emissions and mitigating climate change. This study examined the transition to full-battery electric vehicles by conducting a cross-sectional household survey in 2023 that collected information on vehicle preferences, evaluations, purchase intentions, environmental attitudes, and socioeconomic and demographic characteristics. The results show that among households using a vehicle as their primary mode of transportation, approximately 89% relied on fossil fuel vehicles, whereas only 6% used electric vehicles. The study further finds that acceptance of vehicles during inter-vehicle transitions is closely linked to energy type: households currently owning fossil fuel vehicles exhibited a high likelihood of repurchasing a fossil fuel vehicle, while electric vehicle owners were more inclined to choose another electric vehicle across cities and areas of different sizes. Households that own electric vehicles tend to report higher levels of well-being compared with those that own fossil fuel vehicles. In addition, sufficient charging infrastructure, stronger knowledge of environmental issues, participation in altruistic donation activities, and cooperative behavior positively influenced electric vehicle adoption. These findings suggest several policy implications, including the expansion of charging stations for business and public use, setting reasonable vehicle prices, improving charging speed, developing electric vehicles suitable for large families, and encouraging individuals to gain initial driving experience with electric vehicles to promote adoption. Full article

This paper links the UN Sustainable Development Goal (SDG) of “Affordable and Clean Energy” (nr. 7) to “Partnerships” (nr. 17). These partnerships refer to stakeholders’ participation in renewable energy networks. Given that renewable energy is environmentally superior to fossil fuels and the participatory approaches foster well-being, this paper addresses economic sustainability. Therefore, the costs and benefits of electric power on the grid are compared to the distributed power networks in the EU, the USA, and India. Firstly, the present (dis)incentives for distributed energy networks are identified, concerning power generation, transmission, distribution, and consumption on the grid. Second, the costs of mini-grids and microgrids are assessed based on the existing literature. Thirdly, the benefits of such networks for individual and collective interests of producers and consumers of power are indicated. Although these partnerships are often as yet costly, incorporating those benefits into electricity prices enables price parity with the grid. Policies that pursue those benefits foster the realization of SDGs and improve the balance on the grid. Full article

This study offers a comprehensive in situ measurement and assessment of electromagnetic field (EMF) exposure in the central urban districts of Samsun, Türkiye, focusing on low-frequency magnetic flux density (B_LF) and radiofrequency electric field strength (E_RF). Drive-test measurements were performed across Atakum, İlkadım, and Canik districts to capture spatial variability and identify primary exposure sources. Band-selective analysis revealed that downlink (DL) transmissions are the main contributors to total E_RF exposure, indicating that base station emissions dominate the exposed E_RF levels in the environment. Six-minute averaged B_LF and E_RF values account for temporal fluctuations and confirm that exposure remains well below recommended limits. A one-way ANOVA test indicated that the differences in exposure levels among the three districts were not statistically significant. These findings provide a detailed spatial evaluation of EMF exposure in a large metropolitan region, demonstrating the value of integrated B_LF and E_RF measurements for environmental monitoring. Full article

The growing demand for advanced health-monitoring technologies has intensified the need for early diagnosis of incurable diseases and timely detection of life-threatening conditions. Among various detection modalities, electrochemical sensing has emerged as a particularly promising approach due to its simplicity, cost-effectiveness, high sensitivity, rapid response, ease of miniaturization, and compatibility with portable, wearable, and implantable platforms. The performance of electrochemical sensors is strongly governed by the morphology and physicochemical properties of electrode materials. In this context, MXenes, 2D transition-metal carbides, nitrides, and carbonitrides have attracted increasing attention for sensing applications owing to their high electrical conductivity, large surface area, hydrophilicity, and rich surface chemistry. However, their practical implementation is hindered by oxidation and environmental instability, while surface modification strategies, although improving stability, may compromise intrinsic electrochemical activity and biocompatibility. Notably, MXene-based hybrids consistently demonstrate enhanced sensing performance, underscoring their potential for flexible and wearable electrochemical devices. Despite rapid progress in this field, a comprehensive review addressing the significance of MXene hybrids, their structure–property–performance relationships, and their role in electrochemical detection remains limited. Therefore, this review summarizes recent advances in MXene-based hybrid materials for electrochemical sensing and biosensing of biologically relevant analytes, with an emphasis on design strategies, functional enhancements, and their prospects for next-generation health-monitoring technologies. Full article

To promote the sustainable utilization of desert sand as a regional resource in the infrastructure construction of saline-alkali areas, this paper proposes an accelerated test method based on the coupling of an external electric field (60 V) and a 2% Na₂SO₄ solution for rapid evaluation of its sulfate erosion resistance. The optimal mix proportion (FA 10%, water-to-binder ratio 0.33, cement-to-sand ratio 1:1.5, SF 10%) was determined through orthogonal experiments. By employing multi-scale analytical techniques including electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM), X-ray diffraction (XRD) and thermal analysis (TG-DTG), the differentiated deterioration mechanisms driven by the electric field were systematically revealed. The results show that the charge-transfer resistance (Rct) decreased by about 95% within 28 d, demonstrating the characteristic of “micro-scale deterioration preceding macro-scale strength loss.” The anode region was dominated by dissolution of hydration products (porosity 5.1%), while the cathode region, due to enrichment of sulfate ions (S content 3.37 wt.%), generated a large amount of expansive products, leading to more pronounced structural damage (porosity 8.3%) and greater mass loss (cathode 12.56% > anode 9.85%). This study not only elucidates the deterioration mechanisms of desert sand concrete under coupled environmental action, but also provides a mechanism-explicit, rapid and efficient laboratory evaluation method for its sulfate resistance, offering practical guidance for durability design and prevention in engineering structures exposed to saline-alkali conditions. Full article

This article presents a comprehensive analysis of the primary electrical power distribution system in hybrid-electric aircraft, with particular emphasis on its environmental performance assessed through Life Cycle Assessment (LCA). High-resolution Life Cycle Inventory (LCI) data were developed in collaboration with industry partners and refined to reflect current production standards. The results indicate that printed circuit boards (PCBs), magnets, precious metals (gold and silver), and copper are the primary contributors to environmental impact, with PCBs alone accounting for over 50% of material-related emissions. Although precious metals constitute only 0.014% of the product’s mass, they account for nearly 9% of total emissions due to the energy-intensive nature of their mining and refining processes. Additionally, manufacturing stages involving thermal treatments—such as surface coating of iron cores at 850 °C for 14 h—significantly increase energy consumption and associated emissions. The study concludes with recommendations for reducing the carbon footprint of future aircraft power systems through improved material efficiency, process optimization, and supply chain sustainability. Full article

With the advancement of Internet of Things (IoT) technology, flexible sensors with dual optoelectronic sensing modes have emerged as a research hotspot for next-generation smart devices, further driving the urgent demand for environmentally friendly functional materials. Here, we innovatively integrated wastepaper recycling technology with a polyethyleneimine (PEI)-assisted pulping strategy to develop a novel cellulose-based sustainable photo-triboelectric hybrid nanogenerator (PT-HNG). Based on the working mechanism of a freestanding triboelectric nanogenerator (TENG), the PT-HNG can directly convert pressure stimuli into electrical energy and triboelectrification-induced electroluminescence (TIEL) signals. It achieves luminescence brightness of 0.06 mW cm⁻² (3.84 cd m⁻²) and simultaneously delivers excellent electrical output performance (172.4 V, 6.36 μA, 43.7 nC) under sliding motion. More importantly, compatible with existing industrial papermaking processes, the PT-HNG is scalable for large-scale production. By combining PT-HNG with deep learning algorithms, a handwritten e-book system based on trajectory recognition was constructed, with a recognition accuracy of up to 95.5%. In addition, real-time intelligent control of PowerPoint presentations via PT-HNG was demonstrated. This study provides a new pathway for converting wastepaper into intelligent products and presents a novel idea for the interdisciplinary integration of the circular economy and advanced electronic technology. Full article

The global transition towards a clean energy system underscores the critical role of Green Electricity Certificates (GECs), yet their effectiveness is often hampered by an inability to credibly trace environmental attributes from generation to consumption. This study provides a systematic review of technological pathways and policy implications for enhancing GEC markets through real-time electricity-carbon traceability, using China’s large-scale and rapidly evolving market as a central case. Through comparative international analysis and examination of China’s market data (2023–2025), we identified a severe oversupply of certificates and a reliance on policy-driven demand as core structural dilemmas. The aim of this study was to clarify how real-time traceability can fundamentally enhance the credibility, temporal precision, and policy applicability of GEC mechanisms, particularly under China’s rapid institutional reforms. The findings indicate that a fundamental transition towards hourly granularity in certificate issuance and matching is critical to enhance credibility, prevent double-counting, and enable high-value applications like 24/7 clean energy matching. Furthermore, deep integration between the GEC market and the carbon emission trading (CET) scheme is necessary to expand value propositions. We conclude that the synergistic integration of market design (mandatory quotas), cross-market coupling (GEC-carbon market linkage), and robust digital traceability represents the most effective pathway to transform GECs into a credible instrument for driving additional renewable energy consumption and supporting global carbon mitigation goals. Full article

Permanent magnet synchronous machines (PMSMs) are the preferred choice for electric vehicles (EVs), hybrid EVs, and wind turbines because of their high torque density, efficiency, and wide constant-power speed range. Conventional PMSMs rely heavily on rare-earth (RE) permanent magnets like Nd-Fe-B, which offers high remanence and coercivity but comes with high costs, supply chain issues, and environmental concerns. To address these challenges, this paper explores the potential of tetragonal Fe₂Ni₂N, a newly developed RE-free permanent magnet, as a replacement for commercial Nd-Fe-B (N35) in high-performance PMSMs. Fe₂Ni₂N shows a remanent flux density of 1.2 T and coercivity of 0.957 MA/m, closely matching those of commercial N35 magnets. Finite element analysis (FEA) in Ansys Maxwell was performed on both surface-mounted (SPM) and interior-mounted (IPM) PMSMs under EV-representative operating conditions. Results demonstrate that Fe₂Ni₂N-based machines have similar demagnetization resistance, torque, and efficiency to those with N35 magnets, with slight performance advantages at low speeds and nearly identical performance at high speeds. Furthermore, system-level parameters such as DC bus voltage and stator current were analyzed, showing that increased voltage extends the constant torque region while higher current enhances torque output but can slightly reduce efficiency at elevated speeds. These findings confirm that Fe₂Ni₂N is a promising RE-free alternative to Nd-Fe-B for sustainable, high-performance PMSMs. Results show that Fe₂Ni₂N-based machines have similar demagnetization resistance, torque, and efficiency to those with N35 magnets, with slight performance benefits at low speeds and nearly identical results at high speeds. Furthermore, system-level parameters, such as DC bus voltage and stator current, were analyzed. The results show that increased voltage extends the constant-torque region, while higher current enhances torque output but can slightly reduce efficiency at elevated speeds. These findings confirm that Fe₂Ni₂N is a promising RE-free alternative to Nd-Fe-B for sustainable, high-performance PMSMs. Full article

This study assesses the environmental implications of reusing used electrical and electronic equipment (UEEE) in Slovenia. Reuse operations at four centres Ponovne Uporabe were analysed by integrating material flow analysis with a simplified life cycle assessment approach. Four scenarios were evaluated: S1 (optimistic reuse), S2 (conservative reuse), S3 (no reuse), and S4 (full reuse), each varying in allocation of materials to reuse, recycling, and incineration, as well as in the assumed reuse effectiveness. The results show that S4 (full reuse) achieved the highest emissions reduction of 7.87 kg CO₂-eq per kg of material input, highlighting the substantial environmental benefits of reuse over recycling. Optimistic reuse (S1), which assumes full substitution, also yields significant environmental benefits of 7.82 kg CO₂-eq per kg of material input. In contrast, S3 (the no-reuse scenario), in which materials are diverted mainly to recycling, results in an emission reduction of 5.2 kg CO₂-eq per kg of material input. S2 (conservative reuse), applying a conservative reuse factor, shows the lowest emission avoided at 4.1 kg CO₂-eq per kg of material input. Although based in Slovenia, this study offers transferable insights for countries aiming to scale reuse systems. The results highlight that maximizing environmental benefits within the circular economy model requires system supports, including design for reuse, durability, reparability, effective preparation for reuse operations, supportive policy frameworks and adequate financial and infrastructural capacity. Full article

The paper introduces a real-time digital-twin controller that manages evacuation routes while operating GEEM for emergency energy management during building fires. The system consists of three interconnected parts which include (i) a physics-based hazard surrogate for short-term smoke and temperature field prediction from sensor data (ii), a router system that manages path updates for individual users and controls exposure and network congestion (iii), and an energy management system that regulates the exchange between PV power and battery storage and diesel fuel and grid electricity to preserve vital life-safety operations while reducing both power usage and environmental carbon output. The system operates through independent modules that function autonomously to preserve operational stability when sensors face delays or communication failures, and it meets Industry 5.0 requirements through its implementation of auditable policy controls for hazard penalties, fairness weight, and battery reserve floor settings. We evaluate the controller in co-simulation across multiple building layouts and feeder constraints. The proposed method achieves superior performance to existing AI/RL baselines because it reduces near-worst-case egress time (\(T_{95}\) and worst-case exposure) and decreases both event energy \(E_{\mathrm{event}}\) and CO₂-equivalent \(CO_{\mathrm{2event}}\) while upholding all capacity, exposure cap, and grid import limit constraints. A high-VRE, tight-feeder stress test shows how reserve management, flexible-load shedding, and PV curtailment can achieve trade-offs between unserved critical load \(U_{\mathrm{energy}}\) and emissions. The team delivers implementation details together with reporting templates to assist researchers in reaching reproducibility goals. The research shows that emergency energy systems, which integrate evacuation systems, achieve better safety results and environmental advantages that enable smart-city integration through digital thread operations throughout design, commissioning, and operational stages. Full article