Search Results (5,045)

In the context of the “dual-carbon” target, the large-scale integration of renewable energy sources leads to an increased risk of transient voltage instability at the high voltage direct current (HVDC) transmission receiving end. The HVDC transmission system possesses fast and accurate power regulation capability. After a fault occurs near the inverter station, reducing the DC current enables the reactive power from the compensation devices to be released and injected into the receiving-end power grid, thereby providing emergency voltage support for the receiving-end grid. To reduce control costs, an optimization model constrained by transient voltage violation is established, and the DC current modulation is acquired via an online solution. To maintain system stability and meet the requirements of online applications, it is crucial to rapidly solve the optimization model based on the grid operating mode and contingency information to update the emergency control strategy table in the special protection system (SPS). Conventional global orthogonal collocation (GOC) and adaptive orthogonal collocation (AOC)-based solution methods transform the optimization model in the continuous time domain into a nonlinear programming (NLP) problem for solution, which addresses the low efficiency of traditional rolling optimization. However, the GOC- and AOC-based solution methods improve the discretization accuracy of the model by pursuing global uniform densification of collocation points, making it difficult to balance solution accuracy and solution efficiency. To this end, this paper proposes an efficient interval partition dynamic adaptive orthogonal collocation (IP-DAOC)-based solution method. Firstly, the overall optimization time window is interval-partitioned into multiple initial intervals, and an interval-partitioned transient voltage stability emergency control optimization model is established. Furthermore, the interval length and the number of collocation points are dynamically adjusted according to the curvature of interpolation polynomials at collocation points in different intervals. Finally, after interval adjustment, the dynamic equations discretized in adjacent intervals are made continuous by reconstructing the differential matrix. This solution method reduces the total number of collocation points, thereby decreasing the scale of the NLP problem and narrowing the search space, significantly improving solution efficiency while ensuring solution accuracy. To verify the effectiveness of the proposed solution method, simulations are carried out on a modified IEEE 14-bus system. The results are compared with those of the traditional GOC- and AOC-based solution methods, which further demonstrate the superiority of the proposed solution method. Full article

The Chishui River Basin, a core production area for Chinese sauce-aroma Baijiu (exemplified by Moutai), supports sorghum cultivation critical to the liquor’s distinctive quality. The soil environment quality within this region, therefore, directly impacts the safety and quality of both raw material and the final distilled spirit. To underpin the safe production and sustainable development of this iconic beverage, it is essential to assess soil heavy metal contamination in the soils and quantify the contributions from various sources. In this study, 172 surface soil samples were collected from typical sorghum planting bases in the Renhuai area. Concentrations of eight heavy metals (loids) (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) were determined. The contamination status was evaluated using the geostatistical inverse distance weighting interpolation, the Nemerow pollution index (P_N), and the potential ecological risk index (RI). Source identification and quantification were performed using the positive matrix factorization receptor model (PMF). Results revealed significant enrichment of Cd and Hg in the soil, with mean concentrations 2.07 times and 2.54 times the soil background values for Guizhou Province, respectively. Pollution index results (P_i, P_N) indicated that soil Cd contamination is relatively severe, whereas contamination from other elements is minimal. Overall, approximately 86.5% of the study area was classified as clean or only slightly polluted. Cd poses a moderate ecological risk and was the primary contributor to the total ecological hazard. Other elements exhibited lower risk, resulting in a slight overall potential ecological risk. The soil environmental quality in certified organic sorghum bases was generally favorable. PMF analysis identified three principal sources: historic industrial emissions and traffic-related sources (contributing 46%), weathering of carbonate rocks combined with agricultural activities (37%), and natural background coupled with organic fertilizer application (17%). In conclusion, while the overall soil heavy metal pollution level in the sorghum planting areas is low, the notable enrichment and higher ecological risk of Cd necessitate enhanced dynamic monitoring and targeted risk control measures to ensure long-term soil health and product safety. Full article

A novel sodium-oxide-fluxed slag is applied in the aluminothermic reduction of manganese ore. The slag’s high Al₂O₃ solubility facilitates the recycling of Al₂O₃ through hydrometallurgical processes, where NaAlO₂ serves as a water-leachable compound. Aluminothermic reduction is gaining renewed interest as an alternative processing route for the circular economy. In addition, CO₂ emissions in aluminium production via the electrochemical Hall–Héroult process can be reduced if the process electricity is sourced from non-fossil fuels. The unique Na₂O-fluxed MnO₂ ore formulation includes a small quantity of carbon reductant to ensure rapid pre-reduction to MnO. This approach negates the need for a pre-roasting step. Feed mixture variations with different collector metal additions (Si, Cr, Cu) were made to improve alloy–slag separation efficiency. The collector metals may influence the chemistry of the slag. This work compares the phase chemistry of slags formed during aluminothermic reduction to equilibrium phase chemistries calculated for the Na₂O-SiO₂-Al₂O₃-MnO-CaO system. The slag phase morphology consists of distinct alumina-rich strands (1.5% to 2.1%) embedded within a Na₂O-SiO₂-Al₂O₃-MnO-CaO glass matrix. The alumina-rich strands appear molten, indicating that the processing temperatures were higher than their liquidus temperatures (1537 °C to 1655 °C), as high as 1921 °C and 2053 °C. These findings contribute to sustainable practices in the circular economy through the production of low-carbon ferro-manganese complex alloys. Full article

The increasing concentration of atmospheric CO₂ has intensified the urgent need for efficient and sustainable carbon capture technologies. Covalent organic frameworks (COFs) have emerged as a highly promising class of porous crystalline materials for CO₂ adsorption and separation owing to their structural tunability, high surface area, and precisely designable pore environments. This review summarizes recent advances in COF-based CO₂ capture systems, covering pristine COFs, functionalized frameworks, composite materials, and membrane-based architectures. In pristine COFs, CO₂ adsorption is mainly governed by micropore confinement and physisorption within well-defined channels, where surface area and pore size distribution play key roles. Functionalized COFs introduce additional active sites, including amine groups, heteroatoms, ionic functionalities, and alkali metal centers, which significantly enhance CO₂ affinity through stronger electrostatic and acid–base interactions, often leading to mixed physisorption–chemisorption behavior. Composite COFs and mixed-matrix membranes further improve performance through synergistic effects, interfacial engineering, and enhanced mass transport. Despite these advantages, challenges remain in achieving an optimal balance between capacity, selectivity, and regenerability under realistic conditions such as humidity, low CO₂ partial pressure, and multicomponent gas streams. Issues related to scalable synthesis, structural stability, and processability also limit practical applications. Overall, this review highlights key structure–property relationships and outlines future directions, including humid-stable COFs, direct air capture, computational design strategies, and advanced membrane technologies, for next-generation CO₂ capture materials. Full article

The conversion of bio-waste into functional energy materials provides a robust platform for addressing both environmental and energy challenges. In this paper, discarded absorbent pads are transformed into carbon-rich frameworks, which is followed by the fabrication of composites through the incorporation of Cu₄SnS₄ (CSS) for dual electrochemical applications. Integrating CSS into the waste-derived carbon matrix induces strong synergistic effects, improving electrical conductivity, increasing active-site availability, and accelerating charge-transfer kinetics. Comprehensive physicochemical analyses confirmed the successful formation of a well-integrated heterostructure composite with favorable structural and surface characteristics. Electrochemical evaluations further demonstrated that CSS-modified carbon exhibits superior bifunctional performance. In a two-electrode configuration, the composite delivers an energy density of 12.08 Wh kg⁻¹ at a power density of 250 W kg⁻¹ along with excellent cycling stability in supercapacitor applications. As an electrocatalyst, it achieves a low overpotential of 268 mV at −10 mA cm⁻² and a small Tafel slope of 75 mV dec⁻¹, reflecting efficient reaction kinetics. The strong durability observed in both systems underscores the structural integrity and long-term operational stability of the material. Overall, this paper advances a sustainable waste-to-resource strategy for fabricating multifunctional carbon-based composites, offering a promising platform for integrated energy-storage and hydrogen-generation technologies. Full article

This research examines the hydrothermal corrosion behaviour of ceramic matrix composites (CMCs) under highly alkaline conditions (pH > 11.5) in the framework of a deep geological repository for high-level radioactive waste (HLW). The study focuses on the degradation of alumina powder and fibres, key constituents of an oxide/oxide CMC material. Accelerated ageing experiments were conducted in a highly alkaline aqueous environment (pH > 11.5, T = 70 °C for 220 days and T = 150 °C for 30 days). The research used a cross-disciplinary approach integrating thermodynamic calculations and physicochemical analyses to determine the degradation mechanisms of alumina powder and fibres induced by contact with the aqueous ageing solution. Characterisation of the aged alumina powders and fibres revealed the presence of unaltered alumina, hydrated alumina, amorphous phases, and calcium carbonate precipitates from the aqueous solution. Thermodynamic calculations indicate (1) the hydrolysis of alumina to diaspore and (2) the formation of an aluminosilicate phase and calcium carbonate. However, experimental results reveal kinetic limitations, such as the preferential formation of boehmite over diaspore, and morphology-dependent degradation pathways (protective-layer formation on fibres and partial dissolution of powders). Full article

The rapid growth in the use of carbon fiber-reinforced polymers (CFRPs) and fused-deposition-modeled (FDM) polylactic acid (PLA) has generated substantial non-biodegradable and thermoplastic waste streams, creating urgent needs for scalable recycling and valorization strategies. This study develops and evaluates an integrated route that chemically recovers carbon fibers (CFs) from CFRP waste and converts them into high-performance reinforcements for recycled PLA matrices. CFRP fragments were pre-swollen in acetic acid (120 °C, 1 h), then depolymerized by means of oxidation with 1 M KMnO₄ (100 °C, 2 h), washed, dried (100 °C, 24 h), and size-reduced by means of cryogenic milling. Recycled CFs (treated) and untreated CFRP fragments were blended with 3D-printing PLA waste at 10, 20 and 30 wt.% via melt mixing (175 °C, 5 min, 70 rpm) and molded into ASTM D638 dog-bone specimens. Materials were characterized via XRD, FTIR, Raman, SEM and mechanical testing. XRD and Raman confirmed retention of the graphitic backbone after treatment; FTIR and Raman revealed oxygen-containing surface functionalization consistent with oxidation, while SEM showed effective removal of epoxy and improved fiber surface cleanliness. Compared with neat PLA (tensile strength 45.4 MPa; modulus 2.6 GPa; elongation 6.3%), composites reinforced with chemically recycled CFs exhibited marked mechanical enhancement: at 30 wt.% treated CF, the tensile strength increased to 102.6 MPa (+126%), elastic modulus to 11.7 GPa (+350%), and toughness to 250.3 MPa, while ductility decreased to 2.9%. Equivalent composites with untreated CFRP exhibited smaller gains (30 wt.%: tensile 87.3 MPa; modulus 10.3 GPa), highlighting the benefit of epoxy removal and surface activation for fiber–matrix adhesion. The proposed chemical recycling pathway is operationally simple and cost-effective, produces reusable CFs with preserved graphitic structure and enhanced surface chemistry, and enables the fabrication of high-performance, waste-derived PLA composites suitable for structural and engineering applications. This work demonstrates a viable waste-to-value approach that advances circularity for both CFRP and 3D-printing polymer waste streams. Full article

Per- and polyfluoroalkyl substances (PFASs) are persistent emerging contaminants characterized by high environmental stability and biotoxicity. Ubiquitous detection of these contaminants across aquatic environments poses severe threats to ecosystem stability and human health, while constructed wetlands (CWs) serve as a sustainable low-carbon alternative for the remediation of PFAS-laden wastewater. However, traditional mechanisms such as matrix adsorption, phytoaccumulation, and microbial transformation often suffer from low efficiency, rapid saturation, and incomplete degradation. To overcome the above drawbacks, the arbuscular mycorrhizal fungi (AMF)–plant–microbe synergistic consortium has become a promising remediation candidate, which facilitates PFAS immobilization and biodegradation via symbiotic crosstalk among three components. This paper reviews recent advancements in PFAS remediation within AMF-facilitated systems, examining fundamental synergistic mechanisms, treatment efficiencies, and key influencing factors. We propose several optimization strategies, including substrate modification, operational parameter refinement, and the integration of advanced technologies. Furthermore, we emphasize the necessity of elucidating the molecular pathways governing long-chain PFAS degradation and addressing current bottlenecks in engineering applications. Future research should prioritize molecular interaction level interaction mechanisms, the development of anti-interference systems, and field-scale validation. This review provides a theoretical foundation and technical framework for leveraging AMF–plant–microbe synergism to enhance PFAS removal in CWs. Full article

Weak grid infrastructure and the absence of flexible storage are among the principal barriers to reliable, low-carbon energy access in sub-Saharan transmission systems. This paper proposes a hierarchical multi-objective framework for the optimal siting and sizing of battery energy storage systems (BESSs), applied to the 130-bus Mali transmission network within the EMERGE project. The upper level employs NSGA-II to simultaneously maximize daily price arbitrage revenue and minimize active power losses; the lower level solves a network-constrained DC optimal power flow with thermal branch limits enforced as hard linear inequalities via the Power Transfer Distribution Factor (PTDF) matrix. Over 500 generations, the framework identifies Bus 91 (SIRAKORO II, 150 kV) as the dominant storage location, achieving a maximum daily revenue of approximately €10,033 at a marginal loss increment of $6.7\times {10}^{-3}$ MWh. The resulting Pareto front gives Mali system planners a quantitative tool for trading off private investment returns against grid-level environmental impact, demonstrating that rigorous network-constrained BESS planning is technically tractable and economically viable in the resource-constrained context of sub-Saharan energy transitions. Full article

Ultra-high-performance concrete (UHPC) is known for its exceptional compressive strength and durability; however, its brittle nature requires fiber reinforcement to improve toughness and tensile performance. This study investigates the synergistic effects of triple fiber reinforcement, including desized and sized carbon fibers (0.2–1.0 vol%), steel fibers (1.0 vol%), and polypropylene fibers (0.2 vol%) on the fresh, mechanical, durability, microstructure, and fire resistance properties of UHPC. The experimental program included workability, compressive and flexural strength, load-deflection behavior, electrical resistivity, dynamic modulus of elasticity, SEM analysis, and fire resistance at elevated temperatures (425 and 900 °C). The results showed that desized carbon fibers performed better than sized fibers by improving workability, fiber dispersion, flexural behavior, and fiber–matrix bonding. The optimal triple-fiber composition, DC1.0P0.2S1.0, achieved the highest flexural strength of 24 MPa while maintaining compressive strength above 141 MPa. The triple-fiber system provided effective multi-scale crack control, where PP fibers prevented explosive spalling, carbon fibers bridged meso-crack control, and steel fibers enhanced macro-crack load transfer and ductility. SEM analysis further confirmed better dispersion and stronger interfacial bonding of desized carbon fibers. Overall, the optimized triple-fiber system significantly improved flexural performance, toughness, workability, and fire resistance without notably reducing compressive strength, demonstrating strong potential for advanced structural applications. Full article

This study investigated the production of spodumene concentrate and lithium carbonate from a low-grade pegmatite ore containing approximately 0.26 wt.% Li₂O. The ore consisted predominantly of a quartz–feldspar aluminosilicate matrix with dispersed spodumene mineralization, which complicates conventional processing approaches. Preliminary lithium concentration was performed by dense media separation (DMS) using an industrially applicable ferrosilicon-based suspension. The highest separation efficiency was achieved for the −4.0/+2.8 mm fraction, producing a DMS concentrate containing 5.77 wt.% Li₂O with 98% lithium recovery. The obtained spodumene concentrate was subjected to decrepitation at 1000–1100 °C to convert α-spodumene into the more reactive β-modification, followed by sulfation roasting with concentrated sulfuric acid at 250–270 °C. The productive leach solution obtained after water leaching contained up to 12.1 g/L Li₂O. After purification from iron-bearing impurities and precipitation with sodium carbonate, a lithium carbonate product containing at least 98.8 wt.% Li₂CO₃ was obtained. Approximately 53% of the lithium contained in the original ore was recovered into the DMS feed fraction, whereas the overall lithium recovery into lithium carbonate reached about 45% relative to the ore and approximately 70% relative to the concentrate. Full article

The development of low-cost and highly sensitive electrochemical sensing platforms for pesticide monitoring has attracted significant attention in recent years. In this study, coke-derived carbon (CDC) was successfully synthesized from petroleum coke through high-temperature carbonization under a nitrogen atmosphere. Subsequently, a CDC@CuO-NP nanocomposite was fabricated by depositing copper oxide nanoparticles onto the CDC matrix. The morphology, structure, and elemental composition of the synthesized materials were characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDS), and elemental mapping analyses, confirming the successful formation of the composite and the uniform distribution of CuO nanostructures on the carbon surface. Electrochemical characterization demonstrated that the incorporation of CuO significantly enhanced the electrochemical performance of CDC by increasing the electroactive surface area and facilitating electron transfer. The CDC@CuO-NP-modified glassy carbon electrode was applied for the electrochemical detection of dichlorvos (DDVP) using electrochemical impedance spectroscopy (EIS). The sensor exhibited a concentration-dependent increase in charge-transfer resistance and showed a linear response in the concentration range of 247–3770 nM, with the regression equation y = 47.1458C + 111.8162 and a correlation coefficient of R² = 0.9832. The developed sensor achieved a low limit of detection (LOD) of 2.3 nM, demonstrating high sensitivity toward DDVP. These results indicate that the CDC@CuO-NP nanocomposite is a promising, low-cost, and efficient electrode material for the sensitive determination of organophosphorus pesticides and has considerable potential for environmental monitoring and food safety applications. Full article

Polyhydroxyalkanoates (PHAs) are bio-based, biodegradable polyesters increasingly explored as sustainable biomaterials for regenerative medicine. This review summarizes recent advances in PHA-based bone substitute materials, highlighting their properties, fabrication methods, and biological performance. PHAs combine biocompatibility, tunable mechanical behavior, and degradation into non-toxic metabolites, while copolymerization and monomer selection modulate the stiffness, crystallinity, and resorption rate. Processing techniques such as solvent casting, electrospinning, and additive manufacturing allow the production of porous architectures that mimic bone extracellular matrix. Electrospinning is particularly suitable for nanoscale fibrous matrices, whereas 3D printing enables patient-specific scaffolds with controlled geometry and interconnected porosity. Scaffold performance can be further improved through the incorporation of osteoconductive fillers, including hydroxyapatite, β-tricalcium phosphate, bioactive glasses, graphene oxide, and carbon nanotubes, as well as through drug-delivery and pro-angiogenic functionalization. In vitro and in vivo studies consistently report favorable cytocompatibility, enhanced osteogenic differentiation, vascularization, and effective repair of bone defects in animal models. However, clinical translation remains limited by production costs, variability in polymer quality, thermal processing constraints, and regulatory challenges. Future progress will rely on more efficient biosynthesis, medical-grade purification, multifunctional scaffold design, and stronger collaboration between academia, industry, and clinicians to unlock the full potential of PHAs in regenerative bone therapies. Full article

This study proposes a hybrid machine learning model based on full-spectrum pulsed neutron logging data to address the monitoring challenges of Carbon Capture, Utilization, and Storage (CCUS) under complex geological conditions. Traditional interpretation models for sequestered CO₂ saturation (e.g., macroscopic capture cross-section model, characteristic peak count model, and ratio model) heavily rely on prior parameters such as porosity, formation water salinity, and lithology. Acquiring these parameters in real time during practical engineering is often costly and difficult. To reduce the rigid dependence of accurate CO₂ saturation monitoring on complex prior parameters like porosity and salinity under heterogeneous geological settings, this research focuses on the Pearl River Mouth Basin, a core carbon sequestration target area in the Guangdong-Hong Kong-Macao Greater Bay Area, based on the evaluation results of offshore carbon sequestration macro-regions in China. Taking the primary reservoirs of the Enping and Wenchang Formations as typical geological prototypes, a high-fidelity, full-spectrum neutron–gamma response database was constructed using Monte Carlo simulations. Two machine learning strategies are proposed: a direct regression model (NMF+SVR) and a joint model (NMF+SVC/KMeans+SVR). Based on Monte Carlo simulated data, experimental results demonstrate that, compared with traditional petrophysical baseline models and simple machine learning models, the proposed joint learning method effectively reduces the dependence of CO₂ saturation monitoring on lithology and porosity. Furthermore, it is proven that even with a single-detector tool configuration, the method exhibits high prediction accuracy under complex lithological conditions. Notably, the two-step joint model achieves a Root Mean Square Error (RMSE) as low as 4.200%, significantly outperforming traditional physics-based models and single machine learning models such as MLP and RF. This study provides a physically interpretable and accurate technical reference for applying machine learning to pulsed neutron-logging-based CO₂ geological sequestration monitoring. Full article

This study developed a sustainable and cost-effective method for producing alginate-encapsulated activated carbon hydrogel beads from almond shell waste biomass, aimed at the efficient removal of methylene blue (MB) dye from aqueous solutions. The activated carbons were developed by heating biomass to different temperatures (500, 600, and 700 °C) and then mixing them with a calcium alginate matrix biopolymer to make composite hydrogel beads labeled AC500@Alg, AC600@Alg, and AC700@Alg. Zeta potential measurement, SEM, EDS, and FTIR analyses were carried out to evaluate the structural, morphological, chemical, and surface properties of the beads. Adsorption experiments showed that raising the activation temperature greatly improved porosity, surface carbon content, and adsorption performance. Among the adsorbent beads, AC700@Alg hydrogel beads had the best ability to adsorb MB, with a maximum Langmuir monolayer capacity of 316.46 mg/g. The pH of the solution and the charge on the surface had a great effect on the adsorption process. The best removal was achieved at alkaline pH due to the electrostatic attractions. The pseudo-second-order model best explained the kinetic data, which meant that surface interactions controlled the adsorption process. Thermodynamic analysis verified that MB adsorption was spontaneous and endothermic. Also, AC700@Alg beads were reusable, keeping their removal efficiency at over 80% after four cycles of adsorption and desorption. These results show that alginate-encapsulated activated carbon made from agricultural waste could be a good, eco-friendly, and reusable adsorbent for cleaning up wastewater. Full article