Search Results (17,964)

Coal gangue, as a predominant solid byproduct of the global coal industry, poses severe environmental challenges because of its massive accumulation and low utilization rate. This review systematically synthesizes and analyzes published experimental and analytical studies on the dual-pathway utilization of coal gangue in concrete, including Pathway 1 (aggregate substitution) and Pathway 2 (cementitious activity activation). While the application of coal gangue aggregates is traditionally limited by their inherent high porosity and lower mechanical strength than those of natural aggregates, this review demonstrates that performance barriers can be effectively overcome. Through multiscale modification strategies—including surface densification, biological mineralization (MICP), and matrix synergy—the interfacial defects are significantly mitigated, allowing for feasible substitution in structural concrete. Conversely, for the mineral admixture pathway, controlled thermal activation is identified as a key process to optimize the phase transformation of kaolinite, thereby significantly enhancing pozzolanic reactivity and long-term durability. According to reported studies, the partial replacement of natural aggregates or cement with coal gangue can reduce CO₂ emissions by approximately tens to several hundreds of kilograms per ton of coal gangue utilized, depending on the substitution level and activation strategy, highlighting its considerable potential for carbon reduction in the construction sector. Nevertheless, challenges related to energy-intensive activation processes and variability in raw gangue composition remain. These limitations indicate the need for future research focusing on low-carbon activation technologies, standardized classification of coal gangue resources, and long-term performance validation under realistic service environments. Based on the synthesized literature, this review discusses hierarchical utilization concepts and low-carbon activation approaches as promising directions for promoting the sustainable transformation of coal gangue from an environmental liability into a carbon-reduction asset in the construction industry. Full article

Coarse-Grained Reconfigurable Architectures (CGRAs) execute compute-intensive kernels on a reconfigurable processing mesh. Transparent CGRAs extend this model by generating configurations at runtime and storing them in a dedicated cache, removing compiler dependence and enabling adaptive behavior. Although prior work has explored mapping strategies and mesh scaling, the feasibility of the configuration cache remains unaddressed, as it is commonly treated as a generic storage block. This paper presents a feasibility study of configuration cache organizations and a design-space exploration of Transparent CGRAs, introducing a parameterized cache geometry model that relates cache parameters to the processing mesh and configuration structure. The model enables realistic estimates of area, latency, and energy at the digital system level and is applied to three Transparent CGRAs from the literature and five additional designs covering a wide range of spatial and temporal organizations. The results show that mesh scaling must be balanced with cache feasibility: wide I/O paths and large configurations lead to impractical caches, whereas well-proportioned meshes achieve competitive performance with modest overheads. Under the proposed exploration, selected expanded meshes outperform a two-issue out-of-order processor by up to 1.4× while increasing area by only 14.8% and energy by 2%. These findings demonstrate that Transparent CGRAs are viable, but their scalability depends on a realistic configuration cache design. The proposed parameterized cache model provides a structured and reproducible basis for analyzing transparency overheads and guiding future CGRA designs. Full article

Hydrogen is widely regarded as a promising clean energy carrier, and blending hydrogen into existing natural gas pipelines is considered a cost-effective and practical pathway for large-scale deployment. Supplying hydrogen-enriched natural gas to buildings requires careful consideration of the safe operation of pipelines and appliances without introducing new risks. In this study, on-site demonstrations and experimental tests were conducted in two high-rise buildings in Weifang to evaluate the impact of hydrogen addition on high-rise building natural gas distribution systems. The results indicate that hydrogen blending up to 20% by volume does not cause stratification in building risers and leads only to a relatively minor increase in additional pressure, approximately 0.56 Pa/m for every 10% increase in hydrogen addition. While hydrogen addition may increase leakage primarily in aging indoor gas systems, gas meter leakage rates under a 10% hydrogen blend remain below 3 mL/h, satisfying safety requirements. In addition, in-service domestic gas alarms remain effective under hydrogen ratios of 0–20%, with average response times of approximately 19–20 s. These findings help clarify the safety performance of hydrogen-blended natural gas in high-rise building distribution systems and provide practical adjustment measures to support future hydrogen injection projects. Full article

This paper explores simulation application functions for the computer monitoring system of a hydro–wind–solar integrated control center, focusing on five core areas: platform management, operational training, performance optimization, exception handling, and emergency drills. Against the “dual carbon” backdrop, multi-energy complementary system simulation faces key challenges including multi-energy coupling, real-time response, and cybersecurity protection. Research shows that integrating digital twin, heterogeneous computing, and artificial intelligence technologies markedly improve simulation accuracy and intelligent decision-making. Dispatch strategies have shifted from single-energy optimization to system-level coordination, while cybersecurity frameworks now provide comprehensive safeguards covering algorithms, data, systems, user behavior, and architecture. Intelligent operation and maintenance with fault diagnosis—powered by big data and deep learning—enables equipment condition prediction, and emergency drill platforms boost response capacity via 3D visualization and scriptless modeling. Current hurdles include absent multi-energy modeling standards, poor extreme-condition adaptability, and inadequate knowledge transfer mechanisms. Future research should prioritize hybrid physical–data-driven approaches, multi-dimensional robust scheduling, federated learning-based diagnostics, and integrated digital twin, edge computing, and decentralized ledger technologies. These advances will drive simulation platforms toward greater intelligence, interoperability, and reliability, laying the technical foundation for unified hydro–wind–solar control centers. Full article

Nanoparticle-mediated photothermal conversion exploits the unique light-to-heat transduction properties of engineered nanomaterials to address challenges in energy, water, and healthcare. This review first examines fundamental mechanisms—localized surface plasmon resonance (LSPR) in plasmonic metals and broadband interband transitions in semiconductors—demonstrating how tailored nanoparticle compositions can achieve >96% absorption across 250–2500 nm and photothermal efficiencies exceeding 98% under one-sun illumination (1000 W·m⁻², AM 1.5G). Next, we highlight advances in solar steam generation and desalination: floating photothermal receivers on carbonized wood or hydrogels reach >95% efficiency in solar-to-vapor conversion and >2 kg·m⁻²·h⁻¹ evaporation rates; three-dimensional architectures recapture diffuse flux and ambient heat; and full-spectrum nanofluids (LaB₆, Au colloids) extend photothermal harvesting into portable, scalable designs. We then survey photothermal-enhanced thermal energy storage: metal-oxide–paraffin composites, core–shell phase-change material (PCM) nanocapsules, and MXene– polyethylene glycol—PEG—aerogels deliver >85% solar charging efficiencies, reduce supercooling, and improve thermal conductivity. In biomedicine, gold nanoshells, nanorods, and transition-metal dichalcogenide (TMDC) nanosheets enable deep-tissue photothermal therapy (PTT) with imaging guidance, achieving >94% tumor ablation in preclinical and pilot clinical studies. Multifunctional constructs combine PTT with chemotherapy, immunotherapy, or gene regulation, yielding synergistic tumor eradication and durable immune responses. Finally, we explore emerging opto-thermal nanobiosystems—light-triggered gene silencing in microalgae and poly(N-isopropylacrylamide) (PNIPAM)–gold nanoparticle (AuNP) membranes for microfluidic photothermal filtration and control—demonstrating how nanoscale heating enables remote, reversible biological and fluidic functions. We conclude by discussing challenges in scalable nanoparticle synthesis, stability, and integration, and outline future directions: multicomponent high-entropy alloys, modular photothermal–PCM devices, and opto-thermal control in synthetic biology. These interdisciplinary innovations promise sustainable solutions for global energy, water, and healthcare demands. Full article

Rechargeable lithium-, sodium-, and potassium-ion batteries are utilized as essential energy storage devices for portable electronics, electric vehicles, and large-scale energy storage systems. In these systems, anode materials play a vital role in determining energy density, cycling stability, and safety of various batteries. However, the complex electrochemical reactions and dynamic changes that occur in anode materials during charge–discharge cycles generate major challenges for performance optimization and understanding failure mechanisms. In situ characterization techniques, capable of real-time tracking of microstructures, composition, and interface dynamics under operating conditions, provide critical insights that bridge macroscopic performance and microscopic mechanisms of anodes. This review systematically summarizes the applications of such techniques in studying anodes for lithium-, sodium-, and potassium-ion batteries, with a focus on their contributions across different anode types. It also indicates current challenges and future directions of these techniques, aiming to offer valuable references for relevant applications and the design of high-performance anodes. Full article

This study examines the high-temperature degradation of Hastelloy C276, a corrosion-resistant nickel-based alloy, during exposure to combustion products generated by methane and 99% cracked ammonia. Using a high-pressure optical combustor (HPOC) at 4 bar and exhaust temperatures of 815–860 °C, standard tensile specimens were exposed for five hours to fully developed post-flame exhaust gases, simulating real industrial turbine or burner conditions. The surfaces and subsurface regions of the samples were analysed using scanning electron microscopy (SEM; Zeiss Sigma HD FEG-SEM, Carl Zeiss, Oberkochen, Germany) and energy-dispersive X-ray spectroscopy (EDX; Oxford Instruments X-MaxN detectors, Oxford Instruments, Abingdon, United Kingdom), while mechanical properties were evaluated by tensile testing, and the gas-phase compositions were tracked in detail for each fuel blend. Results show that exposure to methane causes moderate oxidation and some grain boundary carburisation, with localised carbon enrichment detected by high-resolution EDX mapping. In contrast, 99% cracked ammonia resulted in much more aggressive selective oxidation, as evidenced by extensive surface roughening, significant chromium depletion, and higher oxygen incorporation, correlating with increased NO_x in the exhaust gas. Tensile testing reveals that methane exposure causes severe embrittlement (yield strength +41%, elongation −53%) through grain boundary carbide precipitation, while cracked ammonia exposure results in moderate degradation (yield strength +4%, elongation −24%) with fully preserved ultimate tensile strength (870 MPa), despite more aggressive surface oxidation. These counterintuitive findings demonstrate that grain boundary integrity is more critical than surface condition for mechanical reliability. These findings underscore the importance of evaluating material compatibility in low-carbon and hydrogen/ammonia-fuelled combustion systems and establish critical microstructural benchmarks for the anticipated mechanical testing in future work. Full article

Biomedical antennas are essential components in modern healthcare systems, supporting wireless communication, physiological monitoring, diagnostic imaging, and therapeutic energy delivery. Their performance is strongly influenced by proximity to the human body, creating challenges such as impedance detuning, signal absorption, and size constraints that motivate new materials and fabrication approaches. This work reviews recent advances enabling next-generation wearable and implantable antennas, with emphasis on printed electronics, additive manufacturing, flexible hybrid integration, and metamaterial design. Methods discussed include 3D printing and inkjet, aerosol jet, and screen printing for fabricating conductive traces on textiles, elastomers, and biodegradable substrates, as well as multilayer Flexible Hybrid Electronics that co-integrate sensing, power management, and RF components into thin, body-conforming assemblies. Key results highlight how metamaterial and metasurface concepts provide artificial control over dispersion, radiation, and near-field interactions, enabling antenna miniaturization, enhanced gain and focusing, and improved isolation from lossy biological tissue. These approaches reduce SAR, stabilize impedance under deformation, and support more efficient communication and energy transfer. The review concludes that the convergence of novel materials, engineered electromagnetic structures, and AI-assisted optimization is enabling biomedical antennas that are compact, stretchable, personalized, and highly adaptive, supporting future developments in unobtrusive monitoring, wireless implants, point-of-care diagnostics, and continuous clinical interfacing. Full article

Background: Osteoporosis and osteopenia are prevalent bone diseases characterized by reduced bone mineral density (BMD) and an increased risk of fractures, particularly in postmenopausal women. While dual-energy X-ray absorptiometry (DXA) remains the gold standard for diagnosis, it has limitations regarding accessibility, cost, and predictive capacity for fracture risk. Machine learning (ML) approaches offer an opportunity to develop automated and more accurate diagnostic models by incorporating both BMD values and clinical variables. Method: This study retrospectively analyzed BMD data from 142 postmenopausal women, classified into 3 diagnostic groups: normal, osteopenia, and osteoporosis. Various supervised ML algorithms—including Support Vector Machines (SVM), k-Nearest Neighbors (k-NN), Decision Trees (DT), Naive Bayes (NB), Linear Discriminant Analysis (LDA), and Artificial Neural Networks (ANN)—were applied. Feature selection techniques such as ANOVA, CHI2, MRMR, and Kruskal–Wallis were used to enhance model performance, reduce dimensionality, and improve interpretability. Model performance was evaluated using 10-fold cross-validation based on accuracy, true positive rate (TPR), false negative rate (FNR), and AUC values. Results: Among all models and feature selection combinations, SVM with ANOVA-selected features achieved the highest classification accuracy (94.30%) and 100% TPR for the normal class. Feature sets based on traditional diagnostic regions (L1–L4, femoral neck, total femur) also showed high accuracy (up to 90.70%) but were generally outperformed by statistically selected features. CHI2 and MRMR methods also yielded robust results, particularly when paired with SVM and k-NN classifiers. The results highlight the effectiveness of combining statistical feature selection with ML to enhance diagnostic precision for osteoporosis and osteopenia. Conclusions: Machine learning algorithms, when integrated with data-driven feature selection strategies, provide a promising framework for automated classification of osteoporosis and osteopenia based on BMD data. ANOVA emerged as the most effective feature selection method, yielding superior accuracy across all classifiers. These findings support the integration of ML-based decision support tools into clinical workflows to facilitate early diagnosis and personalized treatment planning. Future studies should explore more diverse and larger datasets, incorporating genetic, lifestyle, and hormonal factors for further model enhancement. Full article

The integration of embedded software in multi-sensor wearable devices has revolutionized real-time monitoring across health, fitness, industrial, and environmental applications. This paper presents a comprehensive approach to designing and implementing embedded software architectures that enable efficient, low-power, and high-accuracy data acquisition and processing from heterogeneous sensor arrays. We explore key challenges such as synchronization of sensor data streams, real-time operating system (RTOS) integration, power management strategies, and wireless communication protocols. The reviewed framework supports modular scalability, allowing for seamless incorporation of additional sensors or features without significant system overhead. Future research directions of the embedded software include Hardware-in-the-Loop and real-world validation, on-device machine learning and edge intelligence, adaptive sensor fusion, energy harvesting and power autonomy, enhanced wireless communications and security, standardization and interoperability, as well as user-centered design and personalization. By adopting this focus, we can highlight the potential of the embedded software to support proactive decision-making and user feedback through edge-level intelligence, paving the way for next-generation wearable monitoring systems. Full article

A magnetic vortex, characterized by curling in-plane magnetization, is generally unstable in two-dimensional (2D) ferromagnetic thin films. Here, we demonstrated that this vortex could be stable in three-dimensional (3D) pyramid-shaped Fe thin films and elucidated mechanistic origin of the stable vortex. Magnetization measurements reveal characteristic $M-H$ hysteresis loops with a pronounced bending and a gradual slope near zero magnetization, contrasting strongly with the abrupt switching seen in 2D films. By decomposing the magnetization processes on each facet in pyramid, we identify the sequence of vortex formation, stabilization, and annihilation. The key factor is the 3D geometry: non-coplanar facet junctions at the ridge lines act as structural singularities that naturally pin domain walls (DWs). These ridge lines restrict DW motion, confine local magnetic structures, and mediate inter-facet interactions, creating geometrical constraints enhancing vortex stability. Vortex formation is driven by magnetostatic energy minimization, as in 2D films. However, ridge-induced weakening of inter-facet exchange becomes the dominant factor in the 3D pyramidal structure. Overall, the interplay of shape anisotropy, magnetostatic, exchange, and Zeeman energies under 3D constraints provides a clear framework for vortex stability, offering the first mechanistic insight into stable vortices in 3D ferromagnetic films and supporting future 3D magnetic devices. Full article

Rapid decarbonization and decentralization of power systems are driving the integration of renewable generation, energy storage and digital technologies into unified energy ecosystems. In this context, photovoltaic (PV) systems combined with battery and hydrogen storage and blockchain-based platforms represent a promising pathway toward sustainable and transparent energy management. This study evaluates the techno-economic performance and operational feasibility of integrated PV systems combining battery and hydrogen storage with a blockchain-based peer-to-peer (P2P) energy trading platform. A simulation framework was developed for two representative consumer profiles: a scientific–educational institution and a residential household. Technical, economic and environmental indicators were assessed for PV systems integrated with battery and hydrogen storage. The results indicate substantial reductions in grid electricity demand and CO₂ emissions for both profiles, with hydrogen integration providing additional peak-load stabilization under current cost constraints. Blockchain functionality was validated through smart contracts and a decentralized application, confirming the feasibility of P2P energy exchange without central intermediaries. Grid electricity consumption is reduced by up to approximately 45–50% for residential users and 35–40% for institutional buildings, accompanied by CO₂ emission reductions of up to 70% and 38%, respectively, while hydrogen integration enables significant peak-load reduction. Overall, the results demonstrate the synergistic potential of integrating PV generation, battery and hydrogen storage and blockchain-based trading to enhance energy independence, reduce emissions and improve system resilience, providing a comprehensive basis for future pilot implementations and market optimization strategies. Full article

Advanced ceramics are known for their lightweight, high-temperature resistance, corrosion resistance, and biocompatibility. They are crucial in energy conversion, environmental protection, and aerospace fields. This review highlights the recent advancements in ceramic matrix composites, high-entropy ceramics, and polymer-derived ceramics, alongside various fabrication techniques such as three-dimensional printing, advanced sintering, and electric-field-assisted joining. Beyond the fabrication process, we emphasize how different processing methods impact microstructure, transport properties, and performance metrics relevant to catalysis. Additive manufacturing routes, such as direct ink writing, digital light processing, and binder jetting, are discussed and normalized based on factors such as relative density, grain size, pore architecture, and shrinkage. Cold and flash sintering methods are also examined, focusing on grain-boundary chemistry, dopant compatibility, and scalability for catalyst supports. Additionally, polymer-derived ceramics (SiOC, SiCN, SiBCN) are reviewed in terms of their catalytic performance in hydrogen evolution reaction, oxygen evolution reaction, oxygen reduction reaction, and CO₂ reduction reaction. CeO₂-ZrO₂ composites are particularly highlighted for their use in environmental catalysis and high-temperature gas sensing. Furthermore, insights on the future industrialization, cross-disciplinary integration, and performance improvements in catalytic applications are provided. Full article

Background: The family Cyprinidae is predominantly restricted to freshwater habitats, making the evolution of diadromy and seawater adaptation exceptionally rare within this group. Pseudaspius hakonensis, a rare anadromous cyprinid, and its strictly freshwater congener P. leptocephalus, provide an ideal comparative model to investigate the molecular mechanisms underlying salinity adaptation. This study aimed to elucidate the tissue-specific transcriptional reprogramming, identify candidate genes and key pathways, and explore their association with seawater acclimation in P. hakonensis. Methods: We performed comparative transcriptomic analyses of gill, liver, and kidney tissues from both species using RNA-Seq. Sequencing reads were aligned to a high-quality reference genome of P. hakonensis. Differential expression analysis was conducted using DESeq2, followed by functional enrichment analyses (GO and KEGG) to identify significant biological processes and pathways. Results: A total of 8784, 5965, and 5719 differentially expressed genes (DEGs) were identified in gill, kidney, and liver tissues, respectively, with the gill showing the highest differences. Functional enrichment revealed tissue-specific roles: gill DEGs were associated with protein synthesis and energy metabolism; kidney DEGs with transport and detoxification; and liver DEGs with metabolic regulation and stress signaling. Cross-tissue analysis highlighted three core pathways consistently enriched: MAPK signaling, ABC transporters, and glutathione metabolism. Key candidate genes, including DUSP10, SLC38A2, ATP8B1, GSTA4, and MGST1, were significantly upregulated in P. hakonensis. Conclusions: This first multi-tissue transcriptomic comparison of an anadromous and a freshwater cyprinid reveals pervasive, tissue-specific molecular reprogramming underlying seawater adaptation in P. hakonensis. The coordinated activation of MAPK signaling, glutathione metabolism, and transporter pathways suggests an integrated regulatory network for osmoregulation and stress resistance. These findings provide novel insights into the genetic basis of salinity adaptation in cyprinids and identify candidate genes for future functional validation. Full article

Environmental, Social, and Governance (ESG) factors have become central to international trade, transforming how firms, industries, and governments engage in global markets. This study conducts a systematic literature review to synthesize current knowledge on the ESG–trade nexus. Using content analysis, three key thematic clusters were identified: (i) ESG in supply chains and logistics, (ii) ESG in export performance and international competitiveness, and (iii) ESG and trade within geopolitics, energy, and resource security. The synthesis reveals that ESG has evolved from a voluntary corporate initiative into a structural determinant of global competitiveness, resilience, and legitimacy. Building on these findings, the study proposes an integrative ESG–Trade framework, which conceptualizes ESG as a multidimensional governance ecosystem comprising (i) institutional and regulatory, (ii) technological and operational, and (iii) geopolitical and strategic dimensions. This framework explains how sustainability regulations, digital transformation, and global political economy dynamics co-evolve to shape trade flows and industrial upgrading. The study highlights the need for greater regulatory coherence and strategic ESG integration while offering a foundation for future interdisciplinary and empirical research on sustainable trade governance. Full article