Search Results (12,455)

Lignin, the most abundant renewable aromatic biopolymer on Earth, is rapidly emerging as a powerful enabler of next-generation sustainable technologies. This review shifts the focus to the latest industrial breakthroughs that exploit lignin’s multifunctional properties across energy, agriculture, healthcare, and environmental sectors. Lignin-derived carbon materials are offering scalable, low-cost alternatives to critical raw materials in batteries and supercapacitors. In agriculture, lignin-based biostimulants and controlled-release fertilizers support resilient, low-impact food systems. Cosmetic and pharmaceutical industries are leveraging lignin’s antioxidant, UV-protective, and antimicrobial properties to create bio-based, clean-label products. In water purification, lignin-based adsorbents are enabling efficient and biodegradable solutions for persistent pollutants. These technological leaps are not merely incremental, they represent a paradigm shift toward a materials economy powered by renewable carbon. Backed by global sustainability roadmaps like the European Green Deal and China’s 14th Five-Year Plan, lignin is moving from industrial residue to strategic asset, driven by unprecedented investment and cross-sector collaboration. Breakthroughs in lignin upgrading, smart formulation, and application-driven design are dismantling long-standing barriers to scale, performance, and standardization. As showcased in this review, lignin is no longer just a promising biopolymer, it is a catalytic force accelerating the global transition toward circularity, climate resilience, and green industrial transformation. The future of sustainable innovation is lignin-enabled. Full article

As the largest freshwater lake in China, Poyang Lake plays a crucial role in hydrological processes. Conventional models often fail to capture the time-lagged relationships between meteorological drivers and runoff responses, while lacking regional generalization capability. To address these limitations, this study proposes a novel XAJ-LSTM-TFM hybrid model that accounts for time-lagged hydrological responses and enhances the regional applicability of the Xinanjiang model. The model innovatively integrates the physical mechanisms of the Xinanjiang model with the temporal learning capacity of LSTM networks. By incorporating intermediate hydrological variables (including interflow and groundwater flow) along with 1–3 day lagged meteorological features, the model achieves an average 15.3% improvement in Nash–Sutcliffe Efficiency (NSE) across five sub-basins, with the Ganjiang Basin attaining an NSE of 0.812 and a 25.7% reduction in flood peak errors. The results demonstrate superior runoff simulation performance and reliable generalization capability under intensive anthropogenic activities. Full article

In the stage of high-quality development, the functional coordination between transportation systems and territorial space is a key issue for improving urban spatial efficiency. This paper breaks through the traditional volume-to-capacity ratio analysis paradigm and innovatively integrates the “production-living-ecological space” theory. By introducing an improved accessibility evaluation model and developing a coordination measurement algorithm, a three-dimensional evaluation mechanism covering development potential assessment, service efficiency diagnosis, and resource allocation optimization is established. Empirical research indicates that the improved accessibility indicators can precisely identify the transportation location value of regional functional cores, while the composite coordination indicators can deconstruct the spatiotemporal matching characteristics of “transportation facilities—spatial functions,” providing a dual decision-making basis for the redevelopment of existing space. This measurement system innovatively realizes the integration of planning transmission mechanisms with multi-scale application scenarios, guiding both overall spatial planning and urban renewal area re-optimization. The methodology, applied to the urban villages of Guangzhou, can significantly increase land utilization intensity and value. The research results offer a technical tool for cross-scale collaboration in land space planning reforms and provide theoretical innovations and practical guidance for the value reconstruction of existing spaces under the context of new urbanization. Full article

The Blockchain-based Decentralized Identity Management System (BDIMS) is an innovative framework designed for digital identity management, utilizing the unique attributes of blockchain technology. The BDIMS categorizes entities into three distinct groups: identity providers, service providers, and end-users. The system’s efficiency in identifying and extracting information from identification cards is enhanced by the integration of artificial intelligence (AI) algorithms. These algorithms decompose the extracted fields into smaller units, facilitating optical character recognition (OCR) and user authentication processes. By employing Merkle Trees, the BDIMS ensures secure authentication with service providers without the need to disclose any personal information. This advanced system empowers users to maintain control over their private information, ensuring its protection with maximum effectiveness and security. Experimental results confirm that the BDIMS effectively mitigates identity fraud while maintaining the confidentiality and integrity of sensitive data. Full article

Neuropathic pain is a significant global clinical issue that poses substantial challenges to both public health and the economy due to its complex underlying mechanisms. It has emerged as a serious health concern worldwide. Recent studies involving dorsal root ganglion (DRG) stimulation have provided strong evidence supporting its effectiveness in alleviating chronic pain and its potential for sustaining long-term pain relief. In addition to that, there has been ongoing research with clinical evidence relating to the role of small non-coding ribonucleic acids known as microRNAs in regulating gene expressions affecting pain signals. The signal pathway involves alterations in neuronal excitation, synaptic transmission, dysregulated signaling, and subsequent pro-inflammatory response activation and pain development. When microRNAs are dysregulated in the dorsal root ganglia neurons, they polarize macrophages from anti-inflammatory M2 to inflammatory M1 macrophages causing pain signal generation. By reversing this polarization, a therapeutic activity can be induced. However, the direct delivery of these nucleotides has been challenging due to limitations such as rapid clearance, degradation, and reduction in half-life. Therefore, safe and efficient carrier vehicles are fundamental for microRNA delivery. Here, we present a comprehensive analysis of miRNA-based nano-systems for chronic neuropathic pain, focusing on their impact in dorsal root ganglia. This review provides a critical evaluation of various delivery platforms, including viral, polymeric, lipid-based, and inorganic nanocarriers, emphasizing their therapeutic potential as well as their limitations in the treatment of chronic neuropathic pain. Innovative strategies such as hybrid nanocarriers and stimulus-responsive systems are also proposed to enhance the prospects for clinical translation. Serving as a roadmap for future research, this review aims to guide the development and optimization of miRNA-based therapies for effective and sustained neuropathic pain management. Full article

The low-carbon transition of the global energy system is an urgent necessity to address climate change and meet growing energy demand. As a major source of energy consumption and emissions, buildings play a key role in this transition. This study systematically analyzes the flexible resources of building energy systems and vehicle-to-grid (V2G) interaction technologies, and mainly focuses on the regulation characteristics and coordination mechanisms of distributed energy supply (renewable energy and multi-energy cogeneration), energy storage (electric/thermal/cooling), and flexible loads (air conditioning and electric vehicles) within regional energy systems. The study reveals that distributed renewable energy and multi-energy cogeneration technologies form an integrated architecture through a complementary “output fluctuation mitigation–cascade energy supply” mechanism, enabling the coordinated optimization of building energy efficiency and grid regulation. Electricity and thermal energy storage serve as dual pillars of flexibility along the “fast response–economic storage” dimension. Air conditioning loads and electric vehicles (EVs) complement each other via thermodynamic regulation and Vehicle-to-Everything (V2X) technologies, constructing a dual-dimensional regulation mode in terms of both power and time. Ultimately, a dynamic balance system integrating sources, loads, and storage is established, driven by the spatiotemporal complementarity of multi-energy flows. This paper proposes an innovative framework that optimizes energy consumption and enhances grid stability by coordinating distributed renewable energy, energy storage, and flexible loads across multiple time scales. This approach offers a new perspective for achieving sustainable and flexible building energy systems. In addition, this paper explores the application of demand response policies in building energy systems, analyzing the role of policy incentives and market mechanisms in promoting building energy flexibility. Full article

The innovation in thermal storage systems for solar thermal power generation is crucial for achieving efficient utilization of new energy sources. Molten salt has been extensively studied as a phase change material (PCM) for latent heat thermal energy storage systems. In this study, a two-dimensional model of a vertical shell-and-tube heat exchanger is developed, utilizing water-steam as the heat transfer fluid (HTF) and phase change material for heat transfer analysis. Through numerical simulations, we explore the interplay between PCM solidification and HTF boiling. The transient results show that tube length affects water boiling duration and PCM solidification thickness. Higher heat transfer fluid flow rates lower solidified PCM temperatures, while lower heat transfer fluid inlet temperatures delay boiling and shorten durations, forming thicker PCM solidification layers. Adding fins to the tube wall boosts heat transfer efficiency by increasing contact area with the phase change material. This extension of boiling time facilitates greater PCM solidification, although it may not always optimize the alignment of bundles within the thermal energy storage system. Full article

A novel multi-scale copula-based model predictive control (MPC) method is proposed to address the core regulation challenges of runoff hydropower and distributed photovoltaic systems within high-penetration renewable energy grids. Complex spatio-temporal complementarity under ecological constraints and the limitations of conventional methods were critically analyzed. The core innovation lies in integrating copula theory with MPC, enabling adaptive spatio-temporal optimization and weight adjustment to significantly enhance the efficiency of complementary regulation and overcome traditional performance bottlenecks. Key nonlinear dependencies of water–solar resources were investigated, and mainstream techniques (copula analysis, MPC, rolling optimization, adaptive weighting) were evaluated for their applicability. Future directions for improving modeling precision and intelligent adaptive control are outlined. Full article

The encapsulation of hydrophobic substances remains a significant challenge due to limitations such as low loading efficiency, leakage, and poor distribution within microcapsules. This study introduces a novel strategy utilizing colloidosomes assembled from polyelectrolyte microcapsules (PMCs). PMCs were fabricated via layer-by-layer (LbL) assembly on manganese carbonate (MnCO₃) or calcium carbonate (CaCO₃) cores, followed by core dissolution. A solvent gradient replacement method was employed to substitute the internal aqueous phase of PMCs with kerosene, enabling the formation of colloidosomes through self-assembly upon resuspension in water. Comparative analysis revealed that MnCO₃-based PMCs with smaller diameters (2.5–3 µm vs. 4.5–5.5 µm for CaCO₃) exhibited 3.5-fold greater stability, attributed to enhanced inter-capsule interactions via electrostatic and hydrophobic forces. Confocal microscopy confirmed the structural integrity of colloidosomes, featuring a liquid kerosene core encapsulated within a PMC shell. Temporal stability studies indicated structural degradation within 30 min, though 5% of colloidosomes retained integrity post-water evaporation. PMC-based colloidosomes exhibit significant application potential due to their integration of colloidosome functionality with PMC-derived structural features—semi-permeability, tunable shell thickness/composition, and stimuli-responsive behavior—enabling their adaptability to diverse technological and biomedical contexts. This innovation holds promise for applications in drug delivery, agrochemicals, and environmental technologies, where controlled release and stability are critical. The findings highlight the role of core material selection and solvent engineering in optimizing colloidosome performance, paving the way for advanced encapsulation systems. Full article

Accurate State of Charge (SOC) estimation is challenged by battery aging and complex internal dynamics. This work introduces a novel framework, Mamba-PG, that leverages the Mamba architecture to integrate internal gas pressure—a direct indicator of electrochemical state—for high-accuracy SOC estimation. The core innovation is a specialized pressure-aware gating mechanism designed to adaptively fuse the pressure signal with conventional electrical data. On a public dataset, our model achieved a state-of-the-art Mean Absolute Error (MAE) of 0.386%. Furthermore, we demonstrate that the gating mechanism learns a physically-plausible and interpretable strategy, dynamically adjusting the pressure signal’s influence based on its magnitude and the battery’s aging state. This study validates that the synergy of novel physical signals with efficient, interpretable architectures like Mamba presents a robust path toward next-generation Battery Management Systems. Full article

Zirconium-89 (⁸⁹Zr) is a widely used radionuclide in immune-PET imaging due to its physical decay characteristics. Despite its importance, the production of ⁸⁹Zr radiopharmaceuticals remains largely manual, with limited cost-effective automation solutions available. To address this, we developed an automated system for the agile and reliable production of radiopharmaceuticals. The system performs transmutations, dissolution, and separation for a range of radioisotopes. Steps in the production of ⁸⁹Zr-oxalate are used as an exemplar to illustrate its use. Three-dimensional (3D) printing was exploited to design and manufacture a target holder able to include solid targets, in this case an ⁸⁹Y foil. Spot welding was used to attach ⁸⁹Y to a refractory tantalum (Ta) substrate. A commercially available CPU chiller was repurposed to efficiently cool the metal target. Furthermore, a commercial resin (ZR Resin) and compact peristaltic pumps were employed in a compact (10 × 10 × 10 cm³) chemical separation unit that operates automatically via computer-controlled software. Additionally, a standalone 3D-printed unit was designed with three automated functionalities: photolabelling, vortex mixing, and controlled heating. All components of the assembly, except for the target holder, are housed inside a commercially available hot cell, ensuring safe and efficient operation in a controlled environment. This paper details the design, construction, and modelling of the entire assembly, emphasising its innovative integration and operational efficiency for widespread radiopharmaceutical automation. Full article

The increasing presence of ECs in aquatic environments has drawn significant attention to the need for innovative, accessible, and sustainable solutions in wastewater treatment. This review provides a comprehensive overview of the use of agricultural residues—often discarded and undervalued—as raw materials for the development of efficient bioadsorbents. Based on a wide range of recent studies, this work presents various types of materials, such as rice husks, sugarcane bagasse, and açaí seeds, that can be transformed through thermal and chemical treatments into advanced bioadsorbents capable of removing pharmaceuticals, pesticides, dyes, and in some cases, even addressing highly persistent pollutants such as PFASs. The main objectives of this review are to (1) assess agricultural-residue-derived bioadsorbents for the removal of ECs; (2) examine physical and chemical modification techniques that enhance adsorption performance; (3) evaluate their scalability and applicability in real-world treatment systems. The review also highlights key adsorption mechanisms—such as π–π interactions, hydrogen bonding, and ion exchange—alongside the influence of parameters like pH and ionic strength. The review also explores the kinetic, isothermal, and thermodynamic aspects of the adsorption processes, highlighting both the efficiency and reusability potential of these materials. This work uniquely integrates microwave-assisted pyrolysis, magnetic functionalization, and hybrid systems, offering a roadmap for sustainable water remediation. Finally, comparative performance analyses, applications using real wastewater, regeneration strategies, and the integration of these bioadsorbents into continuous treatment systems are presented, reinforcing their promising role in advancing sustainable water remediation technologies. Full article

The city of Al Ain is a fast-developing area. With building typology varying from low-rise to mid-rise, sustainable design in buildings is needed. As the majority of the city’s population is Emirati Citizens, the percentage of expats is increasing. The expats tend to live in mid-rise buildings. One of the central midrise areas is AL Ain Square. This study aims to investigate how an optimized mashrabiya pattern can impact the energy and the Predicted Mean Vote (PMV) in a 3-bedroom apartment, fully oriented to the south, of an expat family. The methodology is as follows: case study selection, Weather analysis, Modeling/Validation of the base case scenario, Optimization of the mashrabiya pattern, Simulation of various scenarios, and Results. Analyzing the selected case study is the initial step of the methodology. This analysis begins with the district, building typology, and the chosen apartment. The weather analysis is relevant for using the mashrabiya (screen device) and the need to improve energy consumption and thermal comfort. The modeling of the base case shall be performed in Rhino Grasshopper. The validation is based on a one-year electricity bill provided by the owner. The optimization of mashrabiya patterns is an innovative process, where various designs are compared and then optimized to select the most efficient pattern. The solutions to the selected scenarios will then yield the results of the optimal scenario. This study is relevant to industry, academia, and local authorities as an innovative approach to retrofitting buildings. Additionally, the research presents a creative vision that suggests optimized mashrabiya patterns can significantly enhance energy savings, with the hexagonal grid configuration demonstrating the highest efficiency. This finding highlights the potential for geometry-driven shading optimization tailored to specific climatic and building conditions. Contrasting earlier mashrabiya studies that assess one static pattern, we couple a geometry-agnostic evolutionary solver with a utility-calibrated EnergyPlus model to test thousands of square, hexagonal, and triangular permutations. This workflow uncovers a previously undocumented non-linear depth perforation interaction. It validates a hexagonal screen that reduces annual cooling energy by 12.3%, establishing a replicable, grid-specific retrofit method for hot-arid apartments. Full article

Additive manufacturing (AM) has brought significant breakthroughs to the construction sector, such as the ability to fabricate complex geometries, enhance efficiency, and reduce both material usage and construction waste. However, several challenges must still be addressed to fully transition from conventional construction practices to innovative and sustainable green alternatives. This study investigates the use of non-cementitious traditional mixtures for green construction applications through 3D printing using Liquid Deposition Modeling (LDM) technology. To explore the development of mixtures with enhanced physical and mechanical properties, natural pine and cypress wood shavings were added in varying proportions (1%, 3%, and 5%) as sustainable additives. The aim of this study is twofold: first, to demonstrate the printability of these eco-friendly mortars that can be used for conservation purposes and overcome the challenges of incorporating bio-products in 3D printing; and second, to develop sustainable composites that align with the objectives of the European Green Deal, offering low-emission construction solutions. The proposed mortars use hydrated lime and natural pozzolan as binders, river sand as an aggregate, and a polycarboxylate superplasticizer. While most studies with bio-products focus on traditional methods, this research provides proof of concept for their use in 3D printing. The study results indicate that, at low percentages, both additives had minimal effect on the physical and mechanical properties of the tested mortars, whereas higher percentages led to progressively more significant deterioration. Additionally, compared to molded specimens, the 3D-printed mortars exhibited slightly reduced mechanical strength and increased porosity, attributable to insufficient compaction during the printing process. Full article

This study explores the impact of graphene integration on lithium niobate (LiNbO₃, LN) ridge waveguides and directional couplers, focusing on coupling efficiency, polarization-dependent light absorption, and temperature sensitivity. Experimental and simulation results reveal that graphene loading significantly alters the effective mode refractive index and enhances waveguide coupling, enabling precise control over light transmission and power distribution. The temperature-dependent behavior of graphene–LN structures demonstrates strong thermal sensitivity, with notable changes in output power ratios between cross and through ports under varying temperatures. These findings highlight the potential of graphene–LN hybrid devices for compact, high-performance photonic circuits and temperature sensing applications. This study provides valuable insights into the design of advanced integrated photonic systems, paving the way for innovations in optical communication, sensing, and quantum technologies. Full article