Search Results (1,752)

Graphite has been recognized as a critical material by the United States (US), the European Union (EU), and Australia. Owing to its unique structure and properties, it is utilized in many industries and has played a key role in the clean energy sector, particularly in the lithium-ion battery (LIB) industries. With the projected increase in global graphite demand, driven by the shift to clean energy and the use of EVs, as well as the geographically concentrated production and reserves of natural graphite, interest in graphite recycling has increased, with a specific focus on using spent LIBs and other waste carbon material. Although most established and developing LIB recycling technologies are focused on cathode materials, some have started recycling graphite, with promising results. Based on the different secondary sources and recycling paths reported, hydrometallurgy-based treatment is usually employed, especially for the purification of graphite; greener alternatives are being explored, replacing HF both in lab-scale research and in industry. This offers a viable solution to resource dependency and mitigates the environmental impact associated with graphite production. These developments signal a trend toward sustainable and circular pathways for graphite recycling. Full article

The rapid growth of electric vehicles (EVs) and new energy systems has put lithium-ion batteries at the center of the clean energy change. Nevertheless, to achieve the best battery performance, safety, and sustainability in many changing circumstances, major innovations are needed in Battery Management Systems (BMS). This review paper explores how artificial intelligence (AI) and digital twin (DT) technologies can be integrated to enable the intelligent BMS of the future. It investigates how powerful data approaches such as deep learning, ensembles, and models that rely on physics improve the accuracy of predicting state of charge (SOC), state of health (SOH), and remaining useful life (RUL). Additionally, the paper reviews progress in AI features for cooling, fast charging, fault detection, and intelligible AI models. Working together, cloud and edge computing technology with DTs means better diagnostics, predictive support, and improved management for any use of EVs, stored energy, and recycling. The review underlines recent successes in AI-driven material research, renewable battery production, and plans for used systems, along with new problems in cybersecurity, combining data and mass rollout. We spotlight important research themes, existing problems, and future drawbacks following careful analysis of different up-to-date approaches and systems. Uniting physical modeling with AI-based analytics on cloud-edge-DT platforms supports the development of tough, intelligent, and ecologically responsible batteries that line up with future mobility and wider use of renewable energy. Full article

As an efficient clean energy technology, water electrolysis for hydrogen production has its efficiency limited by the sluggish oxygen evolution reaction (OER) kinetics, which drives the demand for the development of high-performance anode OER catalysts. This work constructs bimetallic (Al, Mn) co-doped nanoporous spinel CoFe₂O₄ (np-CFO) with a tunable structure and composition as an OER catalyst through a simple two-step dealloying strategy. The as-formed np-CFO (Al and Mn) features a hierarchical flaky configuration; that is, there are a large number of fine nanosheets attached to the surface of a regular micron-sized flake, which not only increases the number of active sites but also enhances mass transport efficiency. Consequently, the optimized catalyst exhibits a low OER overpotential of only 320 mV at a current density of 10 mA cm⁻², a minimal Tafel slope of 45.09 mV dec⁻¹, and exceptional durability. Even under industrial conditions (6 M KOH, 60 °C), it only needs 1.83 V to achieve a current density of 500 mA cm⁻² and can maintain good stability for approximately 100 h at this high current density. Theoretical simulations indicate that Al and Mn co-doping could indeed optimize the electronic structure of CFO and thus decrease the energy barrier of OER to 1.35 eV. This work offers a practical approach towards synthesizing efficient and stable OER catalysts. Full article

In the context of achieving low-carbon goals, building low-carbon energy systems is a crucial development direction and implementation pathway. Renewable energy is favored because of its clean characteristics, but the access may have an impact on the power grid. Microgrid technology provides an effective solution to this problem. Uncertainty exists in single microgrids, so multiple microgrids are introduced to improve system stability and robustness. Electric carbon trading and profit redistribution among multiple microgrids have been challenges. To promote energy commensurability among microgrids, expand the types of energy interactions, and improve the utilization rate of renewable energy, this paper proposes a cooperative operation optimization model of multi-microgrids based on the green certificate and carbon trading mechanism to promote local energy consumption and a low carbon economy. First, this paper introduces a carbon capture system (CCS) and power-to-gas (P2G) device in the microgrid and constructs a cogeneration operation model coupled with a power-to-gas carbon capture system. On this basis, a low-carbon operation model for multi-energy microgrids is proposed by combining the local carbon trading market, the stepped carbon trading mechanism, and the green certificate trading mechanism. Secondly, this paper establishes a cooperative game model for multiple microgrid electricity carbon trading based on the Nash negotiation theory after constructing the single microgrid model. Finally, the ADMM method and the asymmetric energy mapping contribution function are used for the solution. The case study uses a typical 24 h period as an example for the calculation. Case study analysis shows that, compared with the independent operation mode of microgrids, the total benefits of the entire system increased by 38,296.1 yuan and carbon emissions were reduced by 30,535 kg through the coordinated operation of electricity–carbon coupling. The arithmetic example verifies that the method proposed in this paper can effectively improve the economic benefits of each microgrid and reduce carbon emissions. Full article

Accurately predicting how quickly people will adopt electric vehicles (EVs) is vital for planning charging stations, managing supply chains, and shaping climate policy. We present a forecasting model that uses three separate Long Short-Term Memory (LSTM) branches—one for past EV sales, one for infrastructure and policy signals, and one for economic trends. An attention mechanism first highlights the most important weeks in each branch, then decides which branch matters most at any point in time. Trained end-to-end on publicly available data, the model beats traditional statistical methods and newer deep learning baselines while remaining small enough to run efficiently. An ablation study shows that every branch and both attention steps improve accuracy, and that adding policy and economic data helps more than relying on EV history alone. Because the network is modular and its attention weights are easy to interpret, it can be extended to produce confidence intervals, include physical constraints, or forecast adoption of other clean-energy technologies. Full article

The growing global demand for electricity, driven by the development of electromobility, data centers, and smart technologies, necessitates innovative approaches to energy generation. Wind power, as a clean and renewable energy source, plays a pivotal role in the global transition towards low-carbon power systems. This paper presents a comprehensive review of generator technologies used in wind turbine applications, ranging from conventional synchronous and asynchronous machines to advanced concepts such as low-speed direct-drive (DD) generators, axial-flux topologies, and superconducting generators utilizing low-temperature superconductors (LTS) and high-temperature superconductors (HTS). The advantages and limitations of each design are discussed in the context of efficiency, weight, reliability, scalability, and suitability for offshore deployment. Special attention is given to HTS-based generator systems, which offer superior power density and reduced losses, along with challenges related to cryogenic cooling and materials engineering. Furthermore, the paper analyzes selected modern generator designs to provide references for enhancing the performance of grid-synchronized hybrid microgrids integrating solar PV, wind, battery energy storage, and HTS-enhanced generators. This review serves as a valuable resource for researchers and engineers developing next-generation wind energy technologies with improved efficiency and integration potential. Full article

The current paper presents a comprehensive intelligent system designed to optimize the performance of a barrier eddy current separator (BECS), comprising a conveyor belt, a vibration feeder, and a magnetic drum. This system was trained and validated on real-world industrial data gathered directly from the working separator under 81 different operational scenarios. The intelligent models were used to recommend optimal settings for drum speed, belt speed, vibration intensity, and drum angle, thereby maximizing separation quality and minimizing energy consumption. the smart separation module utilizes YOLOv11n-seg and achieves a mean average precision (mAP) of 0.838 across 7163 industrial instances from aluminum, copper, and plastic materials. For shape classification (sharp vs. smooth), the model reached 91.8% accuracy across 1105 annotated samples. Furthermore, the thermal monitoring unit can detect iron contamination by analyzing temperature anomalies. Scenarios with iron showed a maximum temperature increase of over 20 °C compared to clean materials, with a detection response time of under 2.5 s. The architecture integrates a Digital Twin using Azure Digital Twins to virtually mirror the system, enabling real-time tracking, behavior simulation, and remote updates. A full connection with the PLC has been implemented, allowing the AI-driven system to adjust physical parameters autonomously. This combination of AI, IoT, and digital twin technologies delivers a reliable and scalable solution for enhanced separation quality, improved operational safety, and predictive maintenance in industrial recycling environments. Full article

Global energy supply remains, to this day, mainly dominated by fossil fuels, aggravating climate change. To increase and diversify the share of renewable energy sources, there is an urgent need to expand the use of biofuels that could help in decarbonizing the energy mix. Biomethane, obtained by upgrading biogas, simultaneously allows the local production of clean energy, waste valorization, and greenhouse gas emissions mitigation. Among various upgrading technologies, the use of activated carbons in adsorption-based separation systems has attracted significant attention due to their versatility, cost-effectiveness, and sustainability potential. The present review offers a comprehensive analysis of the factors that influence the efficiency of activated carbons on carbon dioxide adsorption and separation for biogas upgrading. The influence of activation methods, activation conditions, and precursors on the biogas adsorption performance of activated carbons is revised. Additionally, the role of adsorbent textural and chemical properties on gas adsorption behavior is highlighted. By synthesizing current knowledge and perspectives, this work provides guidance for future research that could help in developing more efficient, cost-effective, and sustainable adsorbents for biogas upgrading. Full article

The transition to clean and renewable energy sources is critically dependent on efficient hydrogen production technologies. This review surveys recent advances in photocatalytic water splitting, focusing on MNb₂O₆ nanomaterials, which have emerged as promising photocatalysts due to their tunable band structures, chemical robustness, and tailored morphologies. The objectives of this work are to (i) encompass the current synthesis strategies for MNb₂O₆ compounds; (ii) assess their structural, electronic, and optical properties in relation to photocatalytic performance; and (iii) elucidate the mechanisms underpinning enhanced hydrogen evolution. Main data collection methods include a literature review of experimental studies reporting bandgap measurements, structural analyses, and hydrogen production metrics for various MNb₂O₆ compositions—especially those incorporating transition metals such as Mn, Cu, Ni, and Co. Novelty stems from systematically detailing the relationships between synthesis routes (hydrothermal, solvothermal, electrospinning, etc.), crystallographic features, conductivity type, and bandgap tuning in these materials, as well as by benchmarking their performance against more conventional photocatalyst systems. Key findings indicate that MnNb₂O₆, CuNb₂O₆, and certain engineered heterostructures (e.g., with g-C₃N₄ or TiO₂) display significant visible-light-driven hydrogen evolution, achieving hydrogen production rates up to 146 mmol h⁻¹ g⁻¹ in composite systems. The review spotlights trends in heterojunction design, defect engineering, co-catalyst integration, and the extension of light absorption into the visible range, all contributing to improved charge separation and catalytic longevity. However, significant challenges remain in realizing the full potential of the broader MNb₂O₆ family, particularly regarding efficiency, scalability, and long-term stability. The insights synthesized here serve as a guide for future experimental investigations and materials design, advancing the deployment of MNb₂O₆-based photocatalysts for large-scale, sustainable hydrogen production. Full article

In the framework of hydrogen production and storage for clean energy generation, the resistance to hydrogen embrittlement of a newly developed austenitic stainless steel is presented. Gas-atomized metal powders prepared from secondary-sourced metals were employed to manufacture test specimens with Laser Powder Bed Fusion (LPBF) technology. After machining and exposure to a controlled, pressurized hydrogen atmosphere at high temperature, the effect of hydrogen charging on the mechanical performance under static and dynamic conditions was investigated. The stabilizing effect of the optimized chemical composition is reflected in the absence of degradation effects on Yield Stress (YS), Ultimate Tensile Stress (UTS), and fatigue life observed for specimens exposed to hydrogen. Moreover, despite a moderate reduction in the elongation at fracture observed by increasing the hydrogen charging time, ductility loss calculated as Relative Reduction of Area (RRA) remains substantially unaffected by the duration of exposure to hydrogen and demonstrates that the austenitic steel is capable of resisting hydrogen embrittlement (HE). Full article

Hydrogen is widely recognized as a key enabler of the clean energy transition, but the lack of safe, efficient, and scalable storage technologies continues to hinder its broad deployment. Conventional hydrogen storage approaches, such as compressed hydrogen storage, cryo-compressed hydrogen storage, and liquid hydrogen storage, face limitations, including high energy consumption, elevated cost, weight, and safety concerns. In contrast, solid-state hydrogen storage using carbon-based adsorbents has gained growing attention due to their chemical tunability, low cost, and potential for modular integration into energy systems. This review provides a comprehensive evaluation of hydrogen storage using carbon-based materials, covering fundamental adsorption mechanisms, classical materials, emerging architectures, and recent advances in computationally AI-guided material design. We first discuss the physicochemical principles driving hydrogen physisorption, chemisorption, Kubas interaction, and spillover effects on carbon surfaces. Classical adsorbents, such as activated carbon, carbon nanotubes, graphene, carbon dots, and biochar, are evaluated in terms of pore structure, dopant effects, and uptake capacity. The review then highlights recent progress in advanced carbon architectures, such as MXenes, three-dimensional architectures, and 3D-printed carbon platforms, with emphasis on their gravimetric and volumetric performance under practical conditions. Importantly, this review introduces a forward-looking perspective on the application of artificial intelligence and machine learning tools for data-driven sorbent design. These methods enable high-throughput screening of materials, prediction of performance metrics, and identification of structure–property relationships. By combining experimental insights with computational advances, carbon-based hydrogen storage platforms are expected to play a pivotal role in the next generation of energy storage systems. The paper concludes with a discussion on remaining challenges, utilization scenarios, and the need for interdisciplinary efforts to realize practical applications. Full article

Waste-to-energy (WtE) are clean technologies that support a circular economy by providing solutions to managing non-recyclable waste while generating alternative energy sources. Despite the promising benefits, technology adoption is challenged by financing constraints, technical maturity, environmental impacts, supporting policies, and public acceptance. A growing number of studies analyzed the acceptability of WtE and identified the factors affecting the adoption of WtE technologies. This study aims to analyze these research hotspots, technologies, and acceptability factors by combining bibliometric and systematic analyses. An initial search from the Web of Science and Scopus databases identified 817 unique documents, and the refinement resulted in 109 for data analysis. The results present a comprehensive overview of the state-of-the-art, providing researchers a basis for future research directions. Among the WtE technologies in the reviewed literature are incineration, anaerobic digestion, gasification, and pyrolysis, with limited studies about refuse-derived fuel and landfilling with gas recovery. The identified common factors include perceived risks, trust, attitudes, perceived benefits, “Not-In-My-BackYard” (NIMBY), awareness, and knowledge. Moreover, the findings present valuable insights for policymakers, practitioners, and WtE project planners to support WtE adoption while achieving sustainable, circular, and low-carbon economies. Full article

Access to clean water is a pressing global concern and membrane technologies play a vital role in addressing this challenge. Thin-film composite membranes prepared via interfacial polymerization (IPol) using meta-phenylenediamine (MPD) and trimesoyl chloride (TMC) exhibit excellent separation performance, but face limitations such as fouling and low hydrophilicity. This study investigated the interaction between MPD and sulfonated zinc phthalocyanine, Zn(SO₂⁻)₄Pc, as a potential strategy for enhancing membrane properties. Using Density Functional Theory (DFT) and Time-Dependent DFT (TD-DFT), we analyzed the optimized geometries, electronic structures, UV–Vis absorption spectra, FT-IR vibrational spectra, and molecular electrostatic potentials of MPD, Zn(SO₂⁻)₄Pc, and their complexes. The results show that MPD/Zn(SO₂⁻)₄Pc exhibits reduced HOMO-LUMO energy gaps and enhanced charge delocalization, particularly in aqueous environments, indicating improved stability and reactivity. Spectroscopic features confirmed strong interactions via hydrogen bonding and π–π stacking, suggesting that Zn(SO₂⁻)₄Pc can act as a co-monomer or additive during IPol to improve polyamide membrane functionality. A conformational analysis of MPD/Zn(SO₂⁻)₄Pc was conducted using density functional theory (DFT) to evaluate the impact of dihedral rotation on molecular stability. The 120° conformation was identified as the most stable, due to favorable π–π interactions and intramolecular hydrogen bonding. These findings offer computational evidence for the design of high-performance membranes with enhanced antifouling, selectivity, and structural integrity for sustainable water treatment applications. Full article

Rail transit as a high-energy consumption field urgently requires the adoption of clean energy innovations to reduce energy consumption and accelerate the transition to new energy applications. As an energy-saving fluid machinery, the ejector exhibits significant application potential and academic value within this field. This paper reviewed the recent advances, technical challenges, research hotspots, and future development directions of ejector applications in rail transit, aiming to address gaps in existing reviews. (1) In waste heat recovery, exhaust heat is utilized for propulsion in vehicle ejector refrigeration air conditioning systems, resulting in energy consumption being reduced by 12~17%. (2) In vehicle pneumatic pressure reduction systems, the throttle valve is replaced with an ejector, leading to an output power increase of more than 13% and providing support for zero-emission new energy vehicle applications. (3) In hydrogen supply systems, hydrogen recirculation efficiency exceeding 68.5% is achieved in fuel cells using multi-nozzle ejector technology. (4) Ejector-based active flow control enables precise ± 20 N dynamic pantograph lift adjustment at 300 km/h. However, current research still faces challenges including the tendency toward subcritical mode in fixed geometry ejectors under variable operating conditions, scarcity of application data for global warming potential refrigerants, insufficient stability of hydrogen recycling under wide power output ranges, and thermodynamic irreversibility causing turbulence loss. To address these issues, future efforts should focus on developing dynamic intelligent control technology based on machine learning, designing adjustable nozzles and other structural innovations, optimizing multi-system efficiency through hybrid architectures, and investigating global warming potential refrigerants. These strategies will facilitate the evolution of ejector technology toward greater intelligence and efficiency, thereby supporting the green transformation and energy conservation objectives of rail transit. Full article

Carbon capture technologies are largely considered to play a crucial role in meeting the climate change and global warming target set by Net Zero Emission (NZE) 2050. These technologies can contribute to clean energy transitions and emissions reduction by decarbonizing the power sector and other CO₂ intensive industries such as iron and steel production, natural gas processing oil refining and cement production where there is no obvious alternative to carbon capture technologies. While the progress of carbon capture technologies has fallen behind expectations in the past, in recent years there has been substantial growth in this area, with over 700 projects at various stages of development. Moreover, there are around 45 commercial carbon capture facilities already in operation around the world in different industrial processes, fuel transformation and power generation. Carbon capture technologies including pre/post-combustion, oxyfuel and chemical looping combustion have been widely exploited in the recent years at different Technology Readiness level (TRL). Although, a large number of review studies are available addressing different carbon capture strategies, however, studies related to the commercial status of the carbon capture technologies are yet to be conducted. In this review article, we summarize the state-of-the-art of different carbon capture technologies applied to different emission sources, focusing on emission reduction, net-zero emission, and negative emission. We also highlight the commercial status of the different carbon capture technologies including economics, opportunities, and challenges. Full article