Search Results (12,471)

In the rapidly evolving field of biomedical engineering, hydrogels have emerged as highly versatile biomaterials that bridge biology and technology through their high water content, exceptional biocompatibility, and tunable mechanical properties. This review provides an integrated overview of both natural and synthetic hydrogels, examining their structural properties, fabrication methods, and broad biomedical applications, including drug delivery systems, tissue engineering, wound healing, and regenerative medicine. Natural hydrogels derived from sources such as alginate, gelatin, and chitosan are highlighted for their biodegradability and biocompatibility, though often limited by poor mechanical strength and batch variability. Conversely, synthetic hydrogels offer precise control over physical and chemical characteristics via advanced polymer chemistry, enabling customization for specific biomedical functions, yet may present challenges related to bioactivity and degradability. The review also explores intelligent hydrogel systems with stimuli-responsive and bioactive functionalities, emphasizing their role in next-generation healthcare solutions. In modern medicine, temperature-, pH-, enzyme-, light-, electric field-, magnetic field-, and glucose-responsive hydrogels are among the most promising “smart materials”. Their ability to respond to biological signals makes them uniquely suited for next-generation therapeutics, from responsive drug systems to adaptive tissue scaffolds. Key challenges such as scalability, clinical translation, and regulatory approval are discussed, underscoring the need for interdisciplinary collaboration and continued innovation. Overall, this review fosters a comprehensive understanding of hydrogel technologies and their transformative potential in enhancing patient care through advanced, adaptable, and responsive biomaterial systems. Full article

Driven by carbon neutrality and peak carbon policies, hydrogen energy, due to its zero-emission and renewable properties, is increasingly being used in hydrogen fuel cell vehicles (H-FCVs). However, the high cost and limited durability of H-FCVs hinder large-scale deployment. Hydrogen internal combustion engine hybrid electric vehicles (H-HEVs) are emerging as a viable alternative. Research on the techno-economics of H-HEVs remains limited, particularly in systematic comparisons with H-FCVs. This paper provides a comprehensive comparison of H-FCVs and H-HEVs in terms of total cost of ownership (TCO) and hydrogen consumption while proposing a multi-objective powertrain parameter optimization model. First, a quantitative model evaluates TCO from vehicle purchase to disposal. Second, a global dynamic programming method optimizes hydrogen consumption by incorporating cumulative energy costs into the TCO model. Finally, a genetic algorithm co-optimizes key design parameters to minimize TCO. Results show that with a battery capacity of 20.5 Ah and an H-FC peak power of 55 kW, H-FCV can achieve optimal fuel economy and hydrogen consumption. However, even with advanced technology, their TCO remains higher than that of H-HEVs. H-FCVs can only become cost-competitive if the unit power price of the fuel cell system is less than 4.6 times that of the hydrogen engine system, assuming negligible fuel cell degradation. In the short term, H-HEVs should be prioritized. Their adoption can also support the long-term development of H-FCVs through a complementary relationship. Full article

This work was conducted within the framework of French university reforms undertaken since 2022. Regardless of learning level and target audience, project-based learning has proved its effectiveness as a teaching strategy for many years. The novelty of the present contribution lies in the gamification of this learning method. A popular game, Trivial Pursuit, was adapted to enable students to acquire knowledge in a playful manner while preparing for upcoming technical challenges. Various technical subjects were chosen to create new cards for the game. A total of 180 questions and their answers were created. The colored tokens were then used to trace manufactured products. This teaching experiment was conducted as part of a project-based learning program with third-year Bachelor students (Electrical Engineering and Industrial Computing Department). The game components associated with the challenge proposed to the students comprised six key elements: objectives, challenges, mechanics, components, rules, and environment. Within the framework of the Industry 4.0 concept, this pedagogical activity focused on the knowledge, understanding, development, and application of an RFID (Radio Frequency Identification) system demonstrating the capabilities of this technology. This contribution outlines the various stages of the work assigned to the students. An industrial partner was also involved in this work. Full article

The stretch film production is highly energy intensive. The components of the technological line are powered by electrical energy, and the heat is used to change the physical state of the raw material (granules). The raw material is poured into FCR (the first calender roller). To solidify the liquid raw material, the calendar must be cooled. The low-temperature heat, treated as waste heat, has dissipated in the atmosphere. Technological innovations were proposed: (a) the raw material comprises raw material (primary) and up to 80% recyclate (waste originating mainly from agriculture), (b) the use of low-temperature waste heat (the cooling of FCR in the process of foil stretch production). A heat recovery line based on two compressor heat pumps (HP, hydraulically coupled) was designed. The waste heat (by low-temperature HP) was transformed into high-temperature heat (by high-temperature HP) and used to prepare the raw material. The proposed technological line enables the management of difficult-to-manage post-production waste (i.e., agriculture and other economic sectors). It reduces energy consumption and raw materials from non-renewable sources (CO₂ and other greenhouse gas emissions are reducing). It implements a closed-loop economy based on renewable energy sources (according to the European Green Deal). Full article

Shaded-pole induction motors are the most frequently used single-phase electric motors in low power applications. Their main advantages are reliability, robustness, low level of noise and vibration, relatively simple manufacturing technology and cost effectiveness. These motors are the driving units of choice in the applications where the variable speed and high starting torque are not of utmost importance, in spite of the fact that they are characterized by inferior efficiency, power factor and starting torque compared to their single-phase counterparts. They are equipped with auxiliary massive copper coils at the stator side, which makes them self-starting, and strongly influence the motor characteristics. This study deals with the numerical modeling and analysis of a shaded-pole induction motor with a C-shaped stator frame. The analysis was performed using 2D finite element-based transient magnetic numerical modeling. The primary objective was to investigate the influence of the number and size of the auxiliary shaded coils on the output torque speed characteristic. We explored the possibility of reducing the amount of material used while preserving the crucial/nominal properties of the motor. Our results have important implications in manufacturing simplification, which may be important for the eco-design of small motors and actuators, including their recycling and/or reuse process. Full article

Virtual fencing (VF) offers a promising alternative to conventional or electrified fences for managing livestock grazing distribution. This study evaluated the behavioral responses of 25 Rarámuri Criollo cows fitted with Nofence^® collars in Pine Valley, CA, USA. The VF system was deployed in chaparral rangeland pastures. The study included a 14-day training phase followed by an 18-day testing phase. The collar-recorded variables, including audio warnings and electric pulses, animal movement, and daily typical behavior patterns of cows classified into a High or Low virtual fence response group, were compared using repeated-measure analyses with mixed models. During training, High-response cows (i.e., resistant responders) received more audio warnings and electric pulses, while Low-response cows (i.e., active responders) had fewer audio warnings and electric pulses, explored smaller areas, and exhibited lower mobility. Despite these differences, both groups showed a time-dependent decrease in the pulse-to-warning ratio, indicating increased reliance on audio cues and reduced need for electrical stimulation to achieve similar containment rates. In the testing phase, both groups maintained high containment with minimal reinforcement. The study found that Rarámuri Criollo cows can effectively adapt to virtual fencing technology, achieving over 99% containment rate while displaying typical diurnal patterns for grazing, resting, or traveling behavior. These findings support the technical feasibility of using virtual fencing in chaparral rangelands and underscore the importance of accounting for individual behavioral variability in behavior-based containment systems. Full article

Measurable changes in electrophysiology have been documented in spaceflight, creating a pathway for disease genesis and progression in astronauts. These electrophysiology changes can be measured using potential difference (PD). A probe to measure PD was developed and is used clinically on Earth; this probe relies on fluid perfusion to establish an electrical connection to make PD measurements. The changes to fluid behavior in microgravity and partial gravity (including lunar and Martian gravity) drives the need to test this probe in a spaceflight environment. Here, we test the PD probe in a novel nasal cavity phantom in parabolic flight, simulating microgravity, lunar gravity, Martian gravity, and hypergravity conditions across 37 parabolas. The results are evaluated across gravity conditions using the Wilcoxon Rank Sum test. We record no statistically significant difference in probe PD measurements in 1 g, microgravity, lunar gravity, and hypergravity (approximately 1.8 g) conditions, reaching a NASA Technology Readiness Level 6. Martian gravity findings are inconclusive. Perfusion-based PD probes are therefore successfully demonstrated for use in spaceflight operation in microgravity, lunar gravity, and hypergravity environments; this establishes a foundation for moving towards the in-space testing of perfusion-based probes in astronauts. Full article

In applications where it is crucial that a battery is recharged from the partially discharged state in the minimum time, it is crucial to honor the technological constraints related to maximum safe battery terminal voltage and maximum continuous charging current prescribed by the battery cell manufacturer. To this end, this contribution outlines the design and comprehensive simulation analysis of an adaptive battery charging system relying on battery open-circuit voltage estimation in real time. A pseudo-random binary sequence test signal and model reference adaptive system are used for the estimation of lithium titanate battery cell electrical circuit model parameters, with the design methodology based on the Lyapunov stability criterion. The proposed adaptive charger is assessed against the conventional constant-current/constant-voltage charging system. The effectiveness of the real-time parameter estimator, along with both the adaptive and traditional charging systems for the lithium titanate battery cell, is validated through simulations and experiments on a dedicated battery test bench. Full article

In the context of the dual-carbon goals, this study proposes a cooperative game-theoretic optimization strategy to enhance the energy utilization efficiency, operational efficiency, and cost-effectiveness of integrated energy systems (IESs) while simultaneously reducing carbon emissions, improving operational flexibility, and mitigating renewable energy variability. To achieve these goals, an IES framework integrating power-to-gas (P2G) technology and carbon capture and storage (CCS) facilities is established to regulate carbon emissions. The system incorporates P2G conversion units and thermal components—specifically, hydrogen fuel cells, electrolyzers, reactors, and electric boilers—aiming to maximize energy conversion efficiency and asset utilization. A cooperative game-theoretic optimization model is developed to facilitate collaboration among multiple stakeholders within the coalition, which employs the Shapley value method to ensure equitable distribution of the cooperative surplus, thereby maximizing collective benefits. The model is solved using an improved gray wolf optimizer (IGWO). The simulation results demonstrate that the proposed strategy effectively coordinates multi-IES scheduling, significantly reduces carbon emissions, facilitates the efficient allocation of cooperation gains, and maximizes overall system utility. Full article

This paper presents a high-fidelity multi-physics dynamic model for electric vehicles, serving as a fundamental building block for intelligent vehicle-to-grid (V2G) integration systems. The model accurately captures complex vehicle dynamics of the powertrain, battery, and regenerative braking, enabling precise energy consumption evaluation, including in AI-driven V2G scenarios. Validated using real-world data from a Citroën Ami operating on urban routes in Naples, Italy, it achieved exceptional accuracy with a root mean square error (RMSE) of 1.28% for dynamic state of charge prediction. This robust framework provides an essential foundation for AI-driven digital twin technologies in V2G applications, significantly advancing sustainable transportation and smart grid integration through predictive simulation. Its versatility supports diverse fleet applications, from residential energy management and coordinated charging optimization to commercial car sharing operations, leveraging backup power during peak demand or grid outages, so to maximize distributed battery storage utilization. Full article

With the increasing integration of renewable energy and smart technologies in residential energy systems, proactive household energy management (HEM) have become critical for reducing costs, enhancing grid stability, and achieving sustainability goals. This study proposes a ultra-short-term forecasting-driven proactive energy consumption optimization strategy that integrates advanced forecasting models with multi-objective scheduling algorithms. By leveraging deep learning techniques like Graph Attention Network (GAT) architectures, the system predicts ultra-short-term household load profiles with high accuracy, addressing the volatility of residential energy use. Then, based on the predicted data, a comprehensive consideration of electricity costs, user comfort, carbon emission pricing, and grid load balance indicators is undertaken. This study proposes an enhanced mixed-integer optimization algorithm to collaboratively optimize multiple objective functions, thereby refining appliance scheduling, energy storage utilization, and grid interaction. Case studies demonstrate that integrating photovoltaic (PV) power generation forecasting and load forecasting models into a home energy management system, and adjusting the original power usage schedule based on predicted PV output and water heater demand, can effectively reduce electricity costs and carbon emissions without compromising user engagement in optimization. This approach helps promote energy-saving and low-carbon electricity consumption habits among users. Full article

Electrostatic separation is a promising technology for the recovery of valuable metals from electronic waste, particularly from printed circuit boards (PCBs). This study explores the application of electrostatic separation for the selective recovery of metallic and non-metallic fractions from crushed PCBs (PCBs). The process exploits the differences in electrical properties between conductive metals and non-conductive polymers and ceramics, facilitating their separation through applied electric fields. The raw materials were pre-treated via mechanical comminution using shredders and hammer mills to achieve an optimal particle size distribution (<3 mm), which enhances separation efficiency. Ferrous materials were removed prior to electrostatic separation to improve process selectivity. Key operational parameters, including particle size, charge accumulation, environmental conditions, and separation efficiency, were systematically analysed. The results demonstrate that electrostatic separation effectively recovers high-value metals such as copper and gold while minimizing material losses. Additionally, the process contributes to the sustainability of e-waste recycling by enabling the recovery of non-metallic fractions for potential secondary applications. This work underscores the significance of electrostatic separation as a viable technique for e-waste management and highlights optimization strategies for enhancing its performance in large-scale recycling operations. Full article

A novel approach to managing domestic heating systems through IoT technologies is introduced in this paper. The system optimizes energy consumption by dynamically adapting to electricity and fuel price fluctuations while maintaining user comfort. Integrating smart devices significantly reduce energy costs and offer a favorable payback period, positioning the solution as both sustainable and economically viable. Efficient heating management is increasingly critical amid growing energy and environmental concerns. This strategy uses IoT devices to collect real-time data on prices, consumption, and user preferences. Based on this data, the system adjusts heating settings intelligently to balance comfort and cost savings. IoT connectivity manages continuous monitoring and dynamic optimization in response to changing conditions. This study includes a real-case comparison between a conventional central heating system and an IoT-managed electric radiator setup. By applying automation rules linked to energy pricing and user habits, the system enhances energy efficiency, especially in cold climates. The economic evaluation shows that using low-cost IoT devices yields meaningful savings and achieves equipment payback within approximately three years. The results demonstrate the system’s effectiveness, demonstrating that smart, adaptive heating solutions can cut energy expenses without sacrificing comfort, while offering environmental and financial benefits. Full article

Excessive reliance on traditional energy sources such as coal, petroleum, and gas leads to a decrease in natural resources and contributes to global warming. Consequently, the adoption of renewable energy sources in power systems is experiencing swift expansion worldwide, especially in offshore areas. Floating solar photovoltaic (FPV) technology is gaining recognition as an innovative renewable energy option, presenting benefits like minimized land requirements, improved cooling effects, and possible collaborations with hydropower. This study aims to assess the levelized cost of electricity (LCOE) associated with floating solar initiatives in offshore and onshore environments. Furthermore, the LCOE is assessed for initiatives that utilize floating solar PV modules within aquaculture farms, as well as for the integration of various renewable energy sources, including wind, wave, and hydropower. The LCOE for FPV technology exhibits considerable variation, ranging from 28.47 EUR/MWh to 1737 EUR/MWh, depending on the technologies utilized within the farm as well as its geographical setting. The implementation of FPV technology in aquaculture farms revealed a notable increase in the LCOE, ranging from 138.74 EUR/MWh to 2306 EUR/MWh. Implementation involving additional renewable energy sources results in a reduction in the LCOE, ranging from 3.6 EUR/MWh to 315.33 EUR/MWh. The integration of floating photovoltaic (FPV) systems into green hydrogen production represents an emerging direction that is relatively little explored but has high potential in reducing costs. The conversion of this energy into hydrogen involves high final costs, with the LCOH ranging from 1.06 EUR/kg to over 26.79 EUR/kg depending on the complexity of the system. Full article

Transparent conductive oxides (TCOs) have become essential components in a broad range of modern devices, including smartphones, flat-panel displays, and photovoltaic cells. Currently, indium tin oxide (ITO) is used in approximately 90% of these devices. However, ITO prices continue to rise due to the limited supply of indium (In), making the development of alternative materials for TCOs indispensable. Therefore, this study highlights the latest advances in creating new, affordable materials, with a focus on aluminum-doped zinc oxide (AZO). Over the last few decades, this material has been widely studied to improve its physical properties, particularly its low electrical resistivity, which can affect the performance of various devices. Now, it is close to replacing ITO due to several advantages including cost-effectiveness, stability under hydrogen plasma, low processing temperatures, and lack of toxicity. Besides that, in comparison to other TCOs such as IZO, IGZO, or IZrO, AZO achieved a low electrical resistivity (10⁻⁵ ohm cm) while maintaining a high transparency across the visible spectrum (over 85%). Additionally, due to the increasing development of technologies utilizing such materials, it is essential to develop more effective techniques for producing TCOs on a larger scale. Additionally, due to the increasing development of technologies utilizing such materials, it is essential to develop more effective techniques for producing TCOs on a larger scale. This review emphasizes the potential of AZO as a cost-effective and scalable alternative to ITO, highlighting key advancements in deposition techniques such as pulsed laser deposition (PLD). Full article