Search Results (12,726)

Anodic aluminum oxide (AAO) is a well-known nanomaterial template formed under specific electrochemical conditions. By adjusting voltage, temperature, electrolyte type, and concentration, various microstructural modifications of AAO can be achieved within its hexagonally arranged pore array. To enable broader applications or enhance performance, post-treatment is often employed to further modify its nanostructure after anodization. Among these post-treatment techniques, AAO membrane detachment methods have been widely studied and can be categorized into traditional etching methods, voltage reduction methods, reverse bias voltage detachment methods, pulse voltage detachment methods, and further anodization techniques. Among various delamination processes, the mechanism is highly related to the selectivity of wet etching, as well as the Joule heating and stress generated during the process. Each of these detachment methods has its own advantages and drawbacks, including processing time, complexity, film integrity, and the toxicity of the solutions used. Consequently, researchers have devoted significant effort to optimizing and improving these techniques. Furthermore, through-hole AAO membranes have been applied in various fields, such as humidity sensors, nanomaterial synthesis, filtration, surface-enhanced Raman scattering (SERS), and tribo-electrical nano-generators (TENG). In particular, the rough and porous structures formed at the bottom of AAO films significantly enhance sensor performance. Depending on specific application requirements, selecting or refining the appropriate processing method is crucial to achieving optimal results. As a versatile nanomaterial template, AAO itself is expected to play a key role in future advancements in environmental safety, bio-applications, energy technologies, and food safety. Full article

Biofouling remains a critical challenge in bioelectrochemical cells (BECs), hindering their efficiency and performance. This research article reviews advances in biofouling mitigation techniques within BEC systems during the period from 2019 to 2025, focusing on membrane modifications and electro-assisted membrane technologies. Through comprehensive analysis, it is revealed that Nafion alternatives, including ceramic membranes and recycled nonwoven fabrics like polypropylene, have emerged as significant contenders due to their combination of low cost and high performance. Additionally, the incorporation of silver, zeolite, and graphene oxide onto membranes has demonstrated efficacy in mitigating biofouling under laboratory conditions. Furthermore, the application of direct current electric fields has shown potential as a chemical-free preventative measure against biofouling in BECs. However, challenges related to long-term stability, scalability, and cost-effectiveness must be addressed for widespread adoption. Full article

The increasing global demand for electricity has heightened the need for stable and reliable power distribution systems. Disruptions in power distribution can cause substantial economic losses and societal impact, underscoring the importance of accurate, timely, and scalable monitoring. The integration of Internet of Things (IoT) technologies into smart grids offers promising capabilities for real-time data collection and intelligent control. However, the application of IoT has created new challenges such as high communication overhead and insufficient user privacy protection due to the continuous exchange of sensitive data. In this paper, we propose a method for power distribution analytics in smart grids based on IoT called PSDA. PSDA collects real-time power usage data from IoT sensor nodes distributed across different grid regions. The collected data is spatially organized using Hilbert curves to preserve locality and enable efficient encoding for subsequent processing. Meanwhile, we adopt a dual-server architecture and distributed point functions (DPF) to ensure efficient data transmission and privacy protection for power usage data. Experimental results indicate that the proposed approach is capable of accurately analyzing power distribution, thereby facilitating prompt responses within smart grid management systems. Compared with traditional methods, our scheme offers significant advantages in privacy protection and real-time processing, providing an innovative IoT-integrated solution for the secure and efficient operation of smart grids. Full article

Tire–road friction is a fundamental factor in vehicle safety, energy efficiency, and environmental sustainability. This narrative review synthesizes current knowledge on the tire–road friction coefficient (TRFC), emphasizing its dynamic nature and the interplay of factors such as tire composition, tread design, road surface texture, temperature, load, and inflation pressure. Friction mechanisms, adhesion, and hysteresis are analyzed alongside their dependence on environmental and operational conditions. The study highlights the challenges posed by emerging mobility paradigms, including electric and autonomous vehicles, which demand specialized tires to manage higher loads, torque, and dynamic behaviors. The review identifies persistent research gaps, such as real-time TRFC estimation methods and the modeling of combined environmental effects. It explores tire–road interaction models and finite element approaches, while proposing future directions integrating artificial intelligence and machine learning for enhanced accuracy. The implications of the Euro 7 regulations, which limit tire wear particle emissions, are discussed, highlighting the need for sustainable tire materials and green manufacturing processes. By linking bibliometric trends, experimental findings, and technological innovations, this review underscores the importance of balancing grip, durability, and rolling resistance to meet safety, efficiency, and environmental goals. It concludes that optimizing friction coefficients is essential for advancing intelligent, sustainable, and regulation-compliant mobility systems, paving the way for safer and greener transportation solutions. Full article

Pre-embedded sensors for concrete structure monitoring face bottlenecks in power supply and data transmission. Existing power supply solutions such as photovoltaic systems and batteries suffer from drawbacks including energy randomness and structural damage to concrete caused by their installation methods. Additionally, commercial wireless communication signals exhibit issues like strong attenuation and poor security during propagation. This paper proposes a hybrid electromagnetic field decoupled parallel transmission technology for power and signals. It utilizes the inherent decoupling characteristic of electric and magnetic fields within the near-field range to construct independent power/signal transfer channels, and achieves independent full-duplex transmission of uplink/downlink data via orthogonal coupling plates. Mathematical models for the power and signal channels are established, and finite element simulations are conducted. A parameter design method for the power compensation network and signal filtering circuit is also proposed. An experimental setup is built, with a coupler outer dimension of 200 mm × 200 mm, a coupling distance of 10 mm, and a thickness of 16 mm for both the transmitting and receiving sides. Experimental results show that the system achieves power transmission with a power of 100 W and an efficiency of 82%, while simultaneously realizing full-duplex communication with a bidirectional rate of 9600 bit/s. Moreover, no bit errors occur within 300,000 characters of bidirectional data. Full article

The application of efficient optical-electrical sorting technology for the automatic separation of copper mine waste rocks not only enables the recovery of valuable copper metals and promotes the resource utilization of non-ferrous mine waste, but also conserves large areas of land otherwise used for waste disposal and alleviates associated environmental issues. However, the process is challenged by the low copper content, fine dissemination of copper-bearing minerals, and complex mineral composition and associated relationships. To address these challenges, this study leverages dual-energy X-ray imaging and multi-modal learning, proposing a lightweight twin-tower convolutional neural network (CNN) designed to fuse high- and low-energy spectral information for the automated sorting of copper mine waste rocks. Additionally, the study integrates an emerging Kolmogorov-Arnold network as a classifier to enhance the sorting performance. To validate the efficacy of our approach, a dataset comprising 31,057 pairs of copper mine waste rock images with corresponding high- and low-energy spectra was meticulously compiled. The experimental results demonstrate that the proposed lightweight method achieves competitive, if not superior, performance compared to contemporary mainstream deep learning networks, yet it requires merely 1.32 million parameters (only 6.2% of ResNet-34), thereby indicating extensive potential for practical deployment. Full article

In this paper, the torsional stiffness simulation and validation process for a fully electric Formula Student car are reported. The optimization of the performance and efficiency of the cars affects various aspects of both the powertrain and the car body. Three crucial themes can be identified for the development of the cars: the power maps the inverter uses to manage the electric motor, the aerodynamic kit installed onboard, and the overall weight of the car. In this regard, in fact, it is not obvious that a higher value of chassis torsional stiffness leads to better performance in terms of speed or energy consumption. To achieve the best balance between torsional stiffness and weight, different simulations are needed. In this paper, we report a way to validate the simulation of the torsional stiffness value, reproducing the forces exchanged between the chassis and the suspension system. The forces used to simulate the torsion are obtained from track tests. To achieve the goal, the analysis is conducted with several experimental tests on two different chassis: the 2021 steel frame tube and the 2023 carbon fiber monocoque of the “Sapienza Fast Charge” Formula Student Electric team. The main result of the research presented here has been achieved; the numerical calculation procedure for the stiffness of Formula Student-type frames has been experimentally validated, allowing design modifications and developments to be studied by quickly verifying their influence on the stiffness of the new frame. A realistic comparison was also made between the two frames, the 2021 frame with space-frame technology and the 2023 frame with a carbon fiber monocoque. The results obtained, both in simulations and experimentally, clearly show that the monocoque frame has 350% greater torsional stiffness than the space-frame type. This result was obtained with the two bare chassis having the same weight. Full article

Discarded NdFeB permanent magnets will become a significant source of rare earth elements (REEs) in the future. Electric vehicle (EV) motors utilize 2–5 kg of NdFeB magnets, and researchers are prioritizing the development of suitable extraction technologies. The objective of our research is to separate metal materials (Al, Cu, Fe and FEEs) from EV motors, based on their melting temperatures. REE magnets that pose the greatest challenge are melted together with the electrical steel of the motor, and the potential for extracting REEs in a selective manner from the molten steel was examined based on their significant oxidation potential using FeO–SiO₂ compounds, which act as an oxidizing slag-forming agent, to test the extraction method. Fayalite (2FeO·SiO₂) is the most easily created and ideal eutectic compound for carrying oxygen (FeO) and forming slag (${\mathrm{S}\mathrm{i}\mathrm{O}}_4^{4^{-}}$), typically generated during copper smelting. In this experiment, copper slag was used and the results were compared to a smelting test, which had previously used a synthesized fayalite flux as a model. The smelting test, utilizing synthesized fayalite flux, yielded a 91% Nd recovery rate. The Nd recovery rate in the smelting test with copper slag hit a high of 64.81%, influenced by the smelting’s holding time. The steel contained 0.08% Nd. Iron was recovered from the copper slag at a rate of 73%. During the smelting test, it was observed that the reaction between Nd₂O₃ and the Al₂O₃ crucible resulted in the formation of a layer on the surface of the crucible, diffusion into the crucible itself, and a subsequent reduction in the efficiency of Nd recovery. Full article

Mannitol dehydration is routinely used to prevent and treat cerebral damage after total aortic arch replacement (TAAR), but existing neuroimaging technologies cannot achieve bedside real-time quantitative assessment of its impact on cerebral perfusion in different patients. This study applied dynamic cerebral perfusion electrical impedance tomography (DCP-EIT), a non-invasive neuroimaging technique, for bedside cerebral perfusion monitoring in TAAR patients during dehydration. Seventeen patients with normal neurological function and nineteen with neurological dysfunction (ND) were enrolled. The variation patterns and differences in perfusion impedance, images, and the relative ratios (RY) of mean perfusion velocity (MV), height of systolic wave (Hs), inflow volume velocity (IV), and angle between the ascending branch and baseline (A_ab) were analyzed. Results showed DCP-EIT could visualize cerebral perfusion changes, with detected poorly perfused regions showing good consistency with ischemic areas identified by computed tomography (CT). RY of normal patients fluctuated around 0.97–1.04, with no significant difference from baseline. RY of ND patients peaked at 14–20 min after dehydration and remained higher than baseline even at 100 min (p < 0.001). DCP-EIT holds potential to optimize individualized cerebral protection strategies for other cerebral damage scenarios and neurocritical care. Full article

Ultra-bandgap semiconductor material, β-gallium oxide (β-Ga₂O₃), has great potential for fabricating the next generation of high-temperature, high-voltage power devices due to its superior material properties and cost competitiveness. In addition, β-Ga₂O₃ has the advantages of high-quality, large-size, low-cost, and controllable doping, which can be realized by the melt method. It has a wide bandgap of 4.7–4.9 eV, a large breakdown field strength of 8 MV/cm, and a Baliga figure of merit (BFOM) as high as 3000, which is approximately 10 and 4 times that of SiC and GaN, respectively. These properties enable β-Ga₂O₃ to be strongly competitive in power diodes and metal-oxide-semiconductor field-effect transistor (MOSFET) applications. Most of the current research is focused on electrical characteristics of those devices, including breakdown voltage (V_BR), specific on-resistance (R_ON,SP), power figure of merit (PFOM), etc. Considering the rapid development of β-Ga₂O₃ diode technology, this review mainly introduces the research progress of different structures of β-Ga₂O₃ power diodes, including vertical and lateral structures with various advanced techniques. A detailed analysis of Ga₂O₃-based high-voltage power diodes is presented. This review will help our theoretical understanding of β-Ga₂O₃ power diodes as well as the development trends of β-Ga₂O₃ power application schemes. Full article

This study focuses on first-generation crystalline silicon photovoltaic (PV) cells, which remain the core of the PV industry. It outlines the structure and operation of single-junction cells, distinguishing between monocrystalline and polycrystalline technologies. A literature review was conducted using databases such as Web of Science and Scopus to identify research trends and inform future research directions. PV cell classification by generation is also presented based on production methods and materials. The experimental section includes both electrical and structural characterisation of crystalline silicon solar cells, with particular emphasis on the influence of the number and geometry of front-side busbars on metal-semiconductor contact resistance and electrical properties. Additionally, the paper highlights the use of dedicated laboratory equipment—such as a solar simulator (for determining photovoltaic cell parameters from current-voltage characteristics) and Corescan equipment (for determining layer parameters using the single-tip probe method)—in evaluating PV cell properties. This equipment is part of the Photovoltaics and Electrical Properties Laboratory at the Silesian University of Technology. The findings demonstrate clear structural correlations that can contribute to optimising the performance and longevity of silicon-based PV cells. Full article

The recent updates to the Single Day-Ahead Coupling (SDAC) framework in the European energy market, along with new rules for providing manual frequency restoration reserve (mFRR) products in the Nordic Energy Activation Market (EAM), have introduced a finer Market Time Unit (MTU) resolution. These developments underscore the growing importance of flexible assets, such as power-to-hydrogen (PtH) facilities, in delivering system flexibility. However, to successfully participate in such markets, well-designed and accurate bidding strategies are essential. To fulfill this aim, this paper proposes a Mixed Integer Linear Programming (MILP) model to determine the optimal bidding strategies for a typical PtH facility, accounting for both the technical characteristics of the involved technologies and the specific participation requirements of the mFRR EAM. The study also explores the economic viability of sourcing electricity from nearby wind turbines (WTs) under a Power Purchase Agreement (PPA). The simulation is conducted using a case study of a planned PtH facility at the Port of Hirtshals, Denmark. Results demonstrate that participation in the mFRR EAM, particularly through the provision of downward regulation, can yield significant economic benefits. Moreover, involvement in the mFRR market reduces power intake from the nearby WTs, as capacity must be reserved for downward services. Finally, the findings highlight the necessity of clearly defined business models for such facilities, considering both technical and economic aspects. Full article

Blue hydrogen technology, generated from natural gas through carbon capture and storage (CCS) technology, is a promising solution to mitigate greenhouse gas emissions and meet the growing demand for clean energy. To improve the sustainability of blue hydrogen, it is crucial to explore alternative feedstocks, production methods, and improve the efficiency and economics of carbon capture, storage, and utilization strategies. Two established technologies for hydrogen synthesis are Steam Methane Reforming (SMR) and Autothermal Reforming (ATR). The choice between SMR and ATR depends on project specifics, including the infrastructure, energy availability, environmental goals, and economic considerations. ATR-based facilities typically generate hydrogen at a lower cost than SMR-based facilities, except in cases where electricity prices are elevated or the facility has reduced capacity. Both SMR and ATR are methods used for hydrogen production from methane, but ATR offers an advantage in minimizing CO₂ emissions per unit of hydrogen generated due to its enhanced energy efficiency and unique process characteristics. ATR provides enhanced utility and flexibility regarding energy sources due to its autothermal characteristics, potentially facilitating integration with renewable energy sources. However, SMR is easier to run but may lack flexibility compared to ATR, necessitating meticulous management. Capital expenditures for SMR and ATR hydrogen reactors are similar at the lower end of the capacity spectrum, but when plant capacity exceeds this threshold, the capital costs of SMR-based hydrogen production surpass those of ATR-based facilities. The less profitably scaled-up SMR relative to the ATR reactor contributes to the cost disparity. Additionally, individual train capacity constraints for SMR, CO₂ removal units, and PSA units increase the expenses of the SMR-based hydrogen facility significantly. Full article

A transition from fossil fuels to renewable energy is underway to achieve net-zero emissions. The institutional arrangements in Indonesia’s energy transportation sector are crucial for various stakeholders involved in the energy transition. This study combines historical institutionalism with a multi-level perspective to analyze how policy formulation, critical junctures, and path dependence shape institutional changes toward sustainable mobility. The evolution of institutional arrangements can be categorized into three phases: the establishment of fuel-oil-based infrastructure and dependency (1970–2003); the diversification of cleaner fuels through compressed natural gas and biofuels (2004–2014); and the development of affordable and clean energy, focusing on biofuels and electrification (2015 to present). In parallel, a quantitative total cost of ownership analysis of vehicles using different fuel types demonstrates how institutional reforms, fiscal incentives, and regulatory support reshape the economic feasibility of low-carbon technologies. Landscape pressures—such as global decarbonization, fuel import dependence, and energy security challenges—interact with niche innovations, including biofuels, electric vehicles, and hybrid systems, to drive systemic transformation. The findings indicate that institutional changes, supported by quantitative economic evidence and technology diffusion, play a pivotal role in realigning Indonesia’s transport energy regime toward a more resilient, inclusive, and sustainable transition. Full article

Advances in motor technology and the application of distributed electric propulsion systems have greatly promoted the development of electric vertical take-off and landing aircraft. As a critical safety component of eVTOL aircraft, the motor system design must satisfy both performance requirements and stringent airworthiness standards. This paper studies the lift–thrust unit drive motor system of an eVTOL aircraft and proposes an architecture that utilizes analytical redundancy to enhance system-level reliability. This paper focuses on threshold optimization in analytical redundancy systems. Through simulations and reliability analyses, the performance of the analytical redundancy system is quantified, with false alarm and missed detection probabilities evaluated, fault detection thresholds optimized, and overall system reliability enhanced analytical redundancy systems is improved. Simulation and calculation results demonstrate that the proposed fault detection method can effectively meet the requirements for rapid detection and achieve optimal reliability at the given optimal threshold. Full article