Search Results (1,366)

Hydrogen sulfide (H₂S), a highly toxic gas, is mainly sourced from petroleum refining, natural gas purification, and coal chemical processes. It poses significant risks to human health, causes environmental pollution, and accelerates equipment corrosion. Recent studies have demonstrated that electrochemical coupling systems offer an efficient, sustainable, and cost-effective strategy for removing sulfur-containing gaseous pollutants. These systems enable the conversion of H₂S into recoverable sulfur under mild conditions, while simultaneously harnessing the chemical energy of H₂S to drive the production of higher-value products (H₂, HCOOH, CH₄, CO, H₂O₂, etc.). Therefore, electrochemical systems for sulfur recovery have received increasing attention. This review highlights the significance of electrochemical recovery of sulfur from H₂S. It summarizes the reaction pathways and mechanisms involved in anodic sulfur oxidation, critically analyzes and discusses methods for detecting sulfur oxidation products, and summarizes the latest advances in sulfur oxidation reaction (SOR) anode materials and various electrochemical coupling systems. The aim is to enhance the fundamental understanding of electrochemical sulfur recovery and to provide insights for the design of novel SOR electrodes and integrated electrochemical coupling systems. Full article

The heavy environmental impact of the construction industry—responsible for 39% of world CO₂ emissions and consuming over 40% of natural resources—supports the need for evidence-based decision-making tools for sustainable material selection balancing environmental, economic, and social considerations. This research develops and evaluates an integrated decision support system that couples cradle-to-grave lifecycle assessment (LCA) with various multi-criteria decision-making (MCDM) methods to optimize climate-resilient material selection for schools. The methodology is an integration of hybrid Analytic Hierarchy Process–Technique for Order of Preference by Similarity to Ideal Solution (AHP-TOPSIS) and VIKOR techniques validated with eight case studies in hot-arid, hot-humid, and temperate climates. Environmental, economic, social, and technical performance indices were evaluated from primary experimental data and with the input from 22 international experts with climate change assessment expertise. Ten material options were examined, from traditional, recycled, and bio-based to advanced composite systems throughout full building lifecycles. The results indicate geopolymer–biofiber composite systems achieve 42% reduced lifecycle carbon emissions, 28% lower cost of ownership, and 35% improved overall sustainability performance compared to traditional equivalents. Three MCDM techniques’ cross-validation demonstrated a satisfactory ranking correlation (Kendall’s τ = 0.87), while Monte Carlo uncertainty analysis ensured framework stability across 95% confidence ranges. Climate-adaptive weighting detected dramatic regional optimization contrasts: thermal performance maximization in tropical climates and embodied impact emphasis in temperate climates. Three case studies on educational building projects demonstrated 95.8% accuracy in validation of environmental performance and economic payback periods between 4.2 and 6.8 years in real-world practice. Full article

This study takes the power battery pack of a pure electric vehicle as the research object, focusing on safety—a core concern widely emphasized in the automotive industry. In practical application scenarios, evaluating the safety of the power battery pack through a single operating condition fails to fully reflect its comprehensive safety performance throughout the vehicle’s entire life cycle. To overcome this limitation, a systematic analysis process was established. First, Catia geometric modeling software was used to simplify the battery pack structure, and HyperMesh was then employed for mesh generation. Second, three core analyses were conducted: static analysis, modal analysis, and extrusion condition analysis. A multi-condition safety evaluation system for electric vehicle battery packs during computer simulation analysis was proposed, which evaluates the battery pack from three dimensions: “dynamic stiffness-static strength-extrusion safety”. Results show that: modal analysis reveals the battery pack’s low-order natural frequencies exceed the vehicle’s excitation frequency (excitation point on the case cover); static analysis confirms it meets operational requirements; extrusion verification proves its safety complies with new national standards. The coupling effect of this multi-dimensional analysis breaks through the limitations of safety performance evaluation under a single operating condition, more realistically reflecting the battery pack’s comprehensive safety over its life cycle and providing a more systematic basis for power battery pack optimization. Full article

Modified gravity theories with a nonminimal coupling between curvature and matter offer a compelling alternative to dark energy and dark matter by introducing an explicit interaction between matter and curvature invariants. Two of the main consequences of such an interaction are the emergence of an additional force and the non-conservation of the energy–momentum tensor, which can be interpreted as an energy exchange between matter and geometry. By adopting this interpretation, one can then take advantage of many different approaches in order to investigate the phenomenon of gravitationally induced particle creation. One of these approaches relies on the so-called irreversible thermodynamics of open systems formalism. By considering the scalar–tensor formulation of one of these theories, we derive the corresponding particle creation rate, creation pressure, and entropy production, demonstrating that irreversible particle creation can drive a late-time de Sitter acceleration through a negative creation pressure, providing a natural alternative to the cosmological constant. Furthermore, we demonstrate that the generalized second law of thermodynamics holds: the total entropy, from both the apparent horizon and enclosed matter, increases monotonically and saturates in the de Sitter phase, imposing constraints on the allowed particle production dynamics. Furthermore, we present brief reviews of other theoretical descriptions of matter creation processes. Specifically, we consider approaches based on the Boltzmann equation and quantum-based aspects and discuss the generalization of the Klein–Gordon equation, as well as the problem of its quantization in time-varying gravitational fields. Hence, gravitational theories with nonminimal curvature–matter couplings present a unified and testable framework, connecting high-energy gravitational physics with cosmological evolution and, possibly, quantum gravity, while remaining consistent with local tests through suitable coupling functions and screening mechanisms. Full article

The Strait of Malacca faces persistent maritime safety challenges due to high vessel density and complex navigational conditions. Current risk assessment methods often lean towards treating static accident analysis and dynamic traffic modeling separately, although some nascent hybrid approaches exist. However, these hybrids frequently lack the capacity for comprehensive, real-time factor integration. This study proposes an integrated framework coupling accident hotspot identification with vessel traffic network analysis. The framework combines trajectory clustering using improved DBSCAN with directional filters, Kernel Density Estimation (KDE) for accident hotspots, and Fuzzy Analytic Hierarchy Process (FAHP) for multi-factor risk evaluation, acknowledging its subjective and region-specific nature. The model was trained and tuned exclusively on the 2023 dataset (47 incidents), reserving the 2024 incidents (24 incidents) exclusively for independent, zero-information-leakage validation. Results demonstrate superior performance: Area Under the ROC Curve (AUC) improved by 0.14 (0.78 vs. 0.64; +22% relative to KDE-only), and Precision–Recall AUC (PR-AUC) improved by 0.16 (0.65 vs. 0.49); both p < 0.001. Crucially, all model tuning and parameter finalization (including DBSCAN/Fréchet, FAHP weights, and adaptive thresholds) relied solely on 2023 data, with the 2024 incidents reserved exclusively for independent temporal validation. The model captures 75.2% of reported incidents within 20% of the study area. Cross-validation confirms stability across all folds. The framework reveals accidents concentrate at network bottlenecks where traffic centrality exceeds 0.15 and accident density surpasses 0.6. Model-based associations suggest amplification through three pathways: environmental-mediated (34%), traffic convergence (34%), and historical persistence (23%). The integrated approach enables identification of both where and why maritime accidents cluster, providing practical applications for vessel traffic services, risk-aware navigation, and evidence-based safety regulation in congested waterways. Full article

Proactive management of groundwater resources is hindered by the static nature of conventional vulnerability assessments, which provide only a single temporal snapshot and lack predictive capability. To address this limitation, we developed a coupled dynamic–spatial modeling framework to forecast the spatio-temporal evolution of groundwater vulnerability. The framework integrates a βSARMA time-series model for precipitation forecasting with an enhanced M-DRASTIC-LAaRd model, which incorporates Land use, Anthropogenic activity, and River network density, weighted via the Analytical Hierarchy Process (AHP) to better capture hydrogeological complexity. The βSARMA model consistently outperformed conventional SARIMA models across the five subregions of Beijing, achieving the lowest RMSE values (0.0832–0.1617) and MAE values (0.0922–0.1372), with an average RMSE reduction of 15.3% relative to the best SARIMA baseline. These results ensure highly reliable dynamic precipitation inputs for the time-varying Net Recharge (R) parameter. Model validation against historical observations yielded a coefficient of determination (R²) of 0.87, confirming the framework’s robustness and predictive accuracy. Applied to the Beijing metropolitan area (1980–2027), the model projects a marked spatial restructuring of groundwater vulnerability: high-vulnerability zones are expected to expand from 38.65% to 46.18%, while low-vulnerability areas will decline from 42.53% to 34.63%. Emerging “hotspots” are concentrated in the southern urban plains, where urbanization and reduced recharge converge. Overall, 27.9% of the region is predicted to experience intensified vulnerability, whereas only 11.5% will show improvement. This study advances groundwater vulnerability assessment from static mapping toward dynamic forecasting, providing a quantitatively validated and spatially explicit framework that supports more informed groundwater management under future environmental change. Full article

Background: Land use change fundamentally alters soil microbial communities and biochemical processes, yet the integrated effects on rhizosphere microbiome–metabolome networks remained poorly understood. Objective: This study investigated land uses as forest, grassland and intermediary edge shape the rhizosphere biochemical networks of naturally grown Barbarea vulgaris. Methods: Rhizosphere soils of Barbarea vulgaris were analysed for microbial community structure abundance, and metabolomic profile applying phospholipid fatty acid (PLFA) profiling and mass spectrometric untargeted metabolomics (GC–MS/MS and MALDI–TOF/TOF MS). These were coupled with co–inertia analysis to assess microbiome–metabolome interactions. Results: Microbial community analysis revealed significant effects of land use on bacterial community structure (G+/G−, p < 0.001). Untargeted metabolomics identified 248 metabolites, of which 161 were mapped to KEGG pathways. Amino acids and derivatives (21.1%) followed by organic acids (16.8%) were the most representative among identified metabolites. Pathway enrichment analysis revealed coordinated reprogramming of central carbon and nitrogen metabolism across land use gradients, particularly in the amino acid metabolism, TCA cycle, and glycolysis/gluconeogenesis pathways. Microbiome–metabolome coupling analysis revealed distinct correlation patterns between microbial phenotypes and metabolite classes, with forest environments showing the strongest biochemical network integration (RV = 0.91). Edge habitats presented intermediate signatures, supporting their role as transitional zones with unique biochemical properties. Conclusions: The environmental context fundamentally shapes rhizosphere biochemical network organization through coordinated shifts in bacterial community structure and metabolic pathway activity. These habitat-specific metabolic signatures suggest that land use change triggers adaptive biochemical responses that may influence plant performance and ecosystem functioning across environmental gradients. Full article

Floods are among the most destructive natural hazards, with damages expected to intensify under climate change and socio-economic pressures. Effective reservoir operation remains a critical yet challenging strategy for mitigating downstream impacts, as operators must navigate nonlinear system dynamics, uncertain inflow forecasts, and trade-offs between competing objectives. This study proposes a novel end-to-end data-driven framework that integrates process-based hydraulic simulations, a Transformer-based surrogate model for flood damage prediction, and reinforcement learning (RL) for reservoir gate operation optimization. The framework is demonstrated using the Coralville Reservoir (Iowa, USA) and two major historical flood events (2008 and 2013). Hydraulic and impact simulations with HEC-RAS and HEC-FIA were used to generate training data, enabling the development of a Transformer model that accurately predicts time-varying flood damages. This surrogate is coupled with a Transformer-enhanced Deep Q-Network (DQN) to derive adaptive gate operation strategies. Results show that the RL-derived optimal policy reduces both peak and time-integrated damages compared to expert and zero-opening benchmarks, while maintaining smooth and feasible operations. Comparative analysis with a genetic algorithm (GA) highlights the robustness of the RL framework, particularly its ability to generalize across uncertain inflows and varying initial storage conditions. Importantly, the adaptive RL policy trained on perturbed synthetic inflows transferred effectively to the hydrologically distinct 2013 event, and fine-tuning achieved near-identical performance to the event-specific optimal policy. These findings highlight the capability of the proposed framework to provide adaptive, transferable, and computationally efficient tools for flood-resilient reservoir operation. Full article

In response to the growing complexity of global exploration targets, traditional Euclidean geometric and linear statistical methods reveal inherent theoretical limitations in characterizing hydrocarbon reservoirs as complex geological bodies that exhibit simultaneous local disorder and global order. Fractal theory, with its core parameter systems such as fractal dimension and scaling exponents, provides an innovative mathematical–physics toolkit for quantifying spatial heterogeneity and resolving the multi-scale characteristics of reservoirs. This review systematically consolidates recent advancements in the application of fractal theory to oil and gas resource assessment, with the aim of elucidating its transition from a theoretical concept to a practical tool. We conclusively demonstrate that fractal theory has driven fundamental methodological progress across four critical dimensions: (1) In reservoir classification and evaluation, fractal dimension has emerged as a robust quantitative metric for heterogeneity and facies discrimination. (2) In pore structure characterization, the theory has successfully uncovered structural self-similarity across scales, from nanopores to macroscopic vugs, enabling precise modeling of complex pore networks. (3) In seepage behavior analysis, fractal-based models have significantly enhanced the predictive capacity for non-Darcy flow and preferential migration pathways. (4) In fracture network modeling, fractal geometry is proven pivotal for accurately characterizing the spatial distribution and connectivity of natural fractures. Despite significant progress, current research faces challenges, including insufficient correlation with dynamic geological processes and a scarcity of data for model validation. Future research should focus on the following directions: developing fractal parameter inversion methods integrated with artificial intelligence, constructing dynamic fractal–seepage coupling models based on digital twins, establishing a unified fractal theoretical framework from pore to basin scale, and expanding its application in low-carbon energy fields such as carbon dioxide sequestration and natural gas hydrate development. Through interdisciplinary integration and methodological innovation, fractal theory is expected to advance hydrocarbon resource assessment toward intelligent, precise, and systematic development, providing scientific support for the efficient exploitation of complex reservoirs and the transition to green, low-carbon energy. Full article

Estuaries represent quintessential coupled human–natural systems (CHNS) where the dynamic interplay between ecological processes and anthropogenic pressures (e.g., shipping, water use exploitation) challenges conventional static spatial planning approaches. Focusing on the Yangtze River Estuary—a globally significant yet intensely utilized ecosystem—this study develops an adaptive management (AM)-oriented spatial planning framework for estuarine protected areas. Our methodology integrates systematic identification of optimal zones using multi-criteria assessments of biodiversity indicators (e.g., flagship species habitats), ecological metrics (e.g., ecosystem services), and management considerations; delineation of a three-tier adaptive zoning system (Control–Functional–Seasonal) to address spatiotemporal pressures; and dynamic management strategies to mitigate human-environment conflicts. The proposed phased conservation boundary (Phase I: 664.38 km²; Phase II: 1721.94 km²) effectively balances ecological integrity with socio-economic constraints. Spatial–temporal analysis of shipping activities over five years demonstrates minimal operational interference, confirming the framework’s efficacy in reconciling conservation and development priorities. By incorporating ecological feedback mechanisms into spatial planning, this work advances a transferable model for governing contested seascapes, contributing to CHNS theory through practical tools for adaptive, conflict-sensitive conservation. The framework’s implementation in the Yangtze context provides empirical evidence that science-driven, flexible spatial planning can reduce sectoral conflicts while maintaining ecosystem functionality, offering a replicable pathway for sustainable water management of similarly complex human–natural systems worldwide. Full article

The reconfiguration of distribution networks plays a crucial role in minimizing active power losses and enhancing reliability, but the problem becomes increasingly complex with the integration of distributed generation (DG). Traditional optimization methods and even earlier hybrid metaheuristics often suffer from premature convergence or require problem reformulations that compromise feasibility. To overcome these limitations, this paper proposes a novel hybrid algorithm that couples Particle Swarm Optimization (PSO) with Simulated Annealing (SA) through an adaptive inertia weight mechanism derived from the Lundy–Mees cooling schedule. Unlike prior hybrid approaches, our method directly addresses the original non-convex, combinatorial nature of the Distribution Network Reconfiguration (DNR) problem without convexification or post-processing adjustments. The main contributions of this study are fourfold: (i) proposing a PSO-SA hybridization strategy that enhances global exploration and avoids stagnation; (ii) introducing an adaptive inertia weight rule tuned by SA, more effective than traditional schemes; (iii) applying a stagnation-based stopping criterion to speed up convergence and reduce computational cost; and (iv) validating the approach on 5-, 33-, and 69-bus systems, with and without DG, showing robustness, recurrence rates above 80%, and low variability compared to conventional PSO. Simulation results confirm that the proposed PSO-SA algorithm achieves superior performance in both loss minimization and solution stability, positioning it as a competitive and scalable alternative for modern active distribution systems. Full article

Energy consumption and environmental pollution pose significant challenges to sustainable development. This study develops a comprehensive coupled framework model that advances the quantitative integration of carbon (C), nitrogen (N), and phosphorus (P) cycles driven by multiple anthropogenic pollution sources. This paper used Panjin city as a case study to analyze the dynamic changes and interconnections among C, N, and P. Results indicated that net anthropogenic carbon inputs (NAI_C) increased by 33% from 2016–2020, while net anthropogenic nitrogen inputs (NAI_N) and net anthropogenic phosphorus inputs (NAI_P) decreased by 14% and 28%, respectively. The primary driver of NAI_C was energy consumption, while wetlands were the dominant carbon sequestration sink. Agricultural production was identified as the primary source of NAI_N and NAI_P, and approximately 4.5% of NAI_N and 2.9% of NAI_P were discharged into receiving water bodies. We demonstrate that human activities and natural processes exhibit dual attributes, producing positive and negative environmental effects. The increase in carbon emissions drives economic growth and industrial restructuring; however, the enhanced economic capacity also strengthens the ability to mitigate pollution through environmental protection measures. Similarly, natural ecosystems, including forests and grasslands, contribute to carbon sequestration and the release of non-point source pollution. The comprehensive environmental impact assessment of C, N, and P revealed that the comprehensive environmental index for Panjin city exhibited an improved trend. The factors of energy structure, energy efficiency, and economic scale promoted NAI_C growth, with the economic scale factor alone accounting for 93% of the total increment. Environmental efficiency factor and population size factor were the primary drivers in reducing NAI_N and NAI_P discharges into the receiving water bodies. We propose a novel management model, ecological restoration, clean energy utilization, resource recycling, and pollution source reduction to achieve systemic governance of C, N, and P inputs. Full article

In response to the sustainability challenges of mining, restrictive policies aimed at improving ecological quality have been enacted in various countries and regions. The purpose of this study is to examine the environmental changes in the Ningdong mining area, located on the Loess Plateau, over the past 25 years, due to many factors, such as coal mining, using the area as a case study. In this study, Landsat satellite images from 2000 to 2024 were used to derive the remote sensing ecological index (RSEI), while the RSEI results were comprehensively analyzed using the Sen+Mann-Kendall method with Geodetector, respectively. Simultaneously, this study utilized land use datasets to calculate the ecological grade (EG) index. The EG index was then analyzed in conjunction with the RSEI. The results show that in the time dimension, the ecological quality of the Ningdong mining area shows a non-monotonic trend of decreasing and then increasing during the 25-year period; The RSEI average reached its lowest value of 0.279 in 2011 and its highest value of 0.511 in 2022. In 2024, the RSEI was 0.428; The coupling matrix between the EG and RSEI indicates that the ecological environment within the mining area has improved. Through ecological factor-driven analysis, we found that the ecological environment quality in the study area is stably controlled by natural topography (slope) and climate (precipitation) factors, while also being disturbed by human activities. This experimental section demonstrates that ecological and environmental evolution is a complex process driven by the nonlinear synergistic interaction of natural and anthropogenic factors. The results of the study are of practical significance and provide scientific guidance for the development of coal mining and ecological environmental protection policies in other mining regions around the world. Full article

As the scaling of silicon-based CMOS technology approaches its physical limits, two-dimensional (2D) materials have emerged as promising alternatives for future electronic devices. Among them, MoS₂ is a leading candidate due to its fascinating semiconducting nature and compatibility with CMOS processes. However, high contact resistance at the metal–MoS₂ interface remains a major bottleneck, limiting device performance. In this study, we report the fabrication and characterization of graphene–MoS₂ (Gr–MoS₂) lateral heterostructure FETs, where monolayer graphene, synthesized by inductively coupled plasma chemical vapor deposition (ICP-CVD), is directly used as the source and drain. Bilayer MoS₂ is selectively grown along graphene edges via edge-guided CVD, forming a chemically bonded in-plane junction without transfer steps. Electrical measurements reveal that the Gr–MoS₂ FETs exhibit a threefold increase in average field-effect mobility (3.9 vs. 1.1 cm² V⁻¹ s⁻¹) compared to conventional MoS₂ FETs. Y-function analysis shows that the contact resistance is significantly reduced from 85.8 kΩ to 20.5 kΩ at V_G = 40 V. These improvements are attributed to the replacement of the conventional metal–MoS₂ contact with a graphene–metal contact. Our results demonstrate that lateral heterostructure engineering with graphene provides an effective and scalable strategy for high-performance 2D electronics. Full article

Distressed fabric is a popular fashion trend that adds a distinct visual appeal to garments. Distressing involves acid washing with pumice stones containing potassium permanganate. This approach is inappropriate for knitted textiles, which can generate holes and reduce quality. This project seeks to create an Elasto Ball (EB) as an alternative to pumice stones in the acid-washing procedure of knitted materials. The Elasto Ball consists of natural rubber foam filled with silica and a silica–lignin hybrid derived from rice husks. The efficacy of the filler is enhanced during the manufacturing of Elasto Ball by employing the NXT silane coupling agent throughout the silanization process. The silanized elasto ball exhibits thermal stability up to 400 °C and a porosity of up to 5%. In garment washing assessments, the Elasto Ball can diminish the fabric’s color by 40–50% without causing damage. The findings of this study indicate that Elasto Ball can function as an efficient, eco-friendly substitute for washing balls in garment washing procedures. Full article