Search Results (16,698)

Excess fluoride originating from phosphate mining activities poses a significant environmental and public health challenge, particularly in arid and semi-arid regions where water resources are limited. This study presents a comparative evaluation of four conventional defluoridation technologies for the treatment of real phosphate mine waters collected from two major Moroccan phosphate mining sites (Youssoufia and Khouribga). The investigated processes included coagulation–flocculation using aluminum sulfate and ferric chloride, chemical precipitation with calcium hydroxide and calcium chloride, adsorption on aluminum oxide (Al₂O₃) and zirconium oxide (ZrO₂), and fluoride removal using calcined bovine bone apatite under both batch and continuous-flow conditions. Adsorption equilibrium was interpreted using Langmuir and Freundlich isotherm models, while the effects of adsorbent dosage, contact time, and water matrix composition were systematically investigated. Among the coagulation processes, aluminum sulfate achieved fluoride removal of up to approximately 82.5% in phosphate washing water and approximately 76.3% in mine drainage water, whereas ferric chloride removed about 52% of the dissolved fluoride under the reported conditions. Lime and calcium chloride exhibited moderate removal efficiencies of 66% and 61%, respectively. Aluminum oxide showed the highest equilibrium adsorption capacity (q_m = 7.14 mg g⁻¹), while zirconium oxide displayed faster fluoride uptake because of its higher surface affinity for fluoride ions. The presence of competing ions in real mine waters was associated with lower adsorption performance compared with synthetic fluoride solutions. Calcined bone apatite proved to be the most effective material, achieving approximately 83% fluoride removal within 20 min under batch conditions and maintaining good performance during continuous fixed-bed operation, producing treated water with fluoride concentrations below the World Health Organization guideline value. Overall, the results demonstrate that calcined bone apatite provides the highest fluoride-removal performance among the investigated materials under the tested conditions. Its waste-derived origin, rapid adsorption kinetics, and effective fluoride removal make it a promising material for the treatment of fluoride-rich phosphate mine waters. The comparative evaluation further indicates that integrating chemical pretreatment with adsorption may represent a promising strategy for the treatment and potential reuse of mining effluents, although the performance of such a combined treatment train should be validated experimentally. Full article

5052 aluminum alloy has been widely used in aerospace, shipbuilding, automotive, and electronic industries due to its low density, high specific strength, and excellent corrosion resistance. Understanding its laser-induced damage behavior under combined continuous-wave (CW) and nanosecond (ns) pulse laser irradiation is essential for optimizing combined laser processing. In this study, the damage behaviors induced by individual CW laser, individual ns pulse laser, and combined pulse laser were systematically investigated using high-speed imaging, infrared thermography, and three-dimensional surface characterization. The results show that the combined pulse laser significantly enhances both damage depth and material removal efficiency compared with single laser irradiation. Although the peak surface temperature remains nearly unchanged under different processing conditions, the crater morphology and penetration depth vary substantially. High-speed imaging reveals that plasma evolution and molten metal ejection dominate the material removal process. Variations in processing parameters significantly modify molten pool dynamics and plasma behavior. In particular, enhanced plasma shielding or excessive energy dissipation reduces the effective laser energy coupling, leading to decreased material removal efficiency. The synergistic interaction among molten pool evolution, plasma expansion, and molten metal ejection governs the final damage morphology. This study provides new insights into the dynamic interaction mechanisms between combined pulse laser and aluminum alloys, offering guidance for parameter optimization in high-precision laser micromachining. Full article

This study aims to investigate the feasibility of ethanol-digested calcium oxide (CaO-E) as a novel dechlorination sorbent for the efficient removal of hydrogen chloride (HCl) from coal-fired flue gas and further evaluate its influence on mercury speciation and transformation in flue gas, thereby addressing the low efficiency and limited multi-pollutant control capability of conventional dry dechlorination technologies. Based on a laboratory-scale injection reaction system, ethanol-digested calcium-based sorbents were injected into simulated coal-fired flue gas to systematically examine the effects of key factors, including Ca/Cl molar ratio, SO₂, and fly ash, on dechlorination efficiency. Density functional theory (DFT) calculations were further employed to elucidate the reaction mechanisms. Meanwhile, mercury-laden flue gas was introduced to investigate the removal characteristics of elemental mercury (Hg⁰) and oxidized mercury (Hg²⁺) by CaO-E. The experimental results demonstrated that ethanol-digested CaO exhibited significantly superior performance compared with untreated samples, and the formation of a porous calcium hydroxide structure was identified as the key factor responsible for its high dechlorination efficiency. When the Ca/Cl molar ratio reached 4.0, the dechlorination efficiency could be stably maintained above 80%. SO₂ showed a pronounced inhibitory effect on the dechlorination process, whereas fly ash exhibited a slight promoting effect. Mercury removal experiments revealed that CaO-E had limited removal capability toward Hg⁰ but effectively reduced the concentration of Hg²⁺. Specifically, when the Ca/Cl molar ratios were 3 and 5, the Hg²⁺ concentrations decreased to 1.4 and 0.6 μg/m³, respectively. This behavior can be attributed to the fact that Hg²⁺ mainly exists in chlorinated forms such as HgCl₂, which possess strong polarity and can be readily adsorbed by the alkaline active sites on the CaO-E surface. In addition, as the dechlorination process proceeded, chlorine-containing species in the flue gas were gradually consumed, suppressing the oxidation conversion of Hg⁰ to Hg²⁺ and thereby further reducing the Hg²⁺ concentration. Theoretical calculations indicated that both HCl and SO₂ could undergo chemisorption on calcium active sites, while HCl possessed a lower reaction energy barrier and therefore dominated the competitive adsorption process, exhibiting preferential reactivity. Overall, ethanol-digested calcium oxide not only demonstrates excellent HCl removal performance, but also shows the capability to regulate mercury speciation in flue gas to a certain extent, providing both theoretical insights and technical support for the synergistic control of multiple pollutants in coal-fired flue gas. Full article

Antibiotic wastewater pollution is a serious environmental problem. This study prepared three types of P-doped biochar (P-CB, P-WB, and P-BB) from corn straw (CB), wheat straw (WB), and bamboo (BB) using phosphoric acid activation at 800 °C. Characterization by SEM, XRD, FTIR, and N₂ adsorption confirmed that high-temperature H₃PO₄ activation drastically reduced the specific surface area but transformed the original microporous framework into a mesopore-dominated structure (average pore diameter 12–15 nm). Adsorption experiments showed that all P-doped biochars enhanced norfloxacin (NOR) removal, with P-CB performing best: 87.14% removal within 30 min at C₀ = 50 mg·L⁻¹ and a maximum adsorption capacity of 305.5 mg·g⁻¹ at higher concentration. Kinetics followed a pseudo-second-order model (R² > 0.9982), and isotherms fitted the Freundlich model (R² = 0.9764–0.9855). Thermodynamics indicated a spontaneous and exothermic process, suggesting that the macroscopic driving force is dominated by physisorption. Mechanism analysis revealed that the synergistic effect of mesopore-dominated diffusion, graphitic π-π sites (from enhanced aromatization at 800 °C), and P-anchored chemisorption overrides the loss of specific surface area, enabling rapid and high-capacity adsorption. Optimal adsorption occurred at pH 5–9, while coexisting anions had a mild inhibitory effect. These findings demonstrate that high-temperature P-doping offers a strategy to rebalance pore architecture and surface functionality rather than simply maximizing specific surface area for efficient antibiotic removal from wastewater. Full article

To address cathode passivation, performance deterioration, and toxic stress during the removal of hexavalent chromium [Cr(VI)] in biocathode microbial fuel cells (MFCs), this study constructed nanomaterial-hybridized biocathodes to improve electricity generation and Cr(VI) removal in MFCs. Reduced graphene oxide (rGO), nano-iron sulfide (nano-FeS), and rGO/nano-FeS were separately hybridized with biocathodes to systematically investigate the effects of different hybridized biocathodes on the performance of MFCs for Cr(VI)-containing wastewater treatment. The results showed that the FeS group exhibited the best Cr(VI) removal capability, with a maximum removal kinetic constant of 0.184 h⁻¹, which was 3.60 times that of the Control group, and showed the smallest performance decline after three consecutive cycles. Mechanistic analysis indicated that nano-FeS promoted the transformation of Cr(VI) into Cr(III) and Cr(0) through its strong adsorption and reducing capacities; it also enhanced biofilm cell activity and the protein/polysaccharide ratio in extracellular polymeric substances; furthermore, it shaped a multi-taxon-dominated microbial community capable of Cr(VI) tolerance and reduction and enhanced the associated metabolic functions, thereby improving resistance to Cr(VI) stress and effectively alleviating cathode passivation. In contrast, rGO tended to enhance biocathode conductivity and electricity generation in MFCs, with the rGO + FeS group achieving the highest power density output of 51.54 ± 3.62 mW/m², which was 1.22 times that of the Control group, as well as the smallest decline in power density after three consecutive cycles. Overall, nanomaterial hybridization reshaped interfacial electron transfer and microbial stress resistance in biocathodes, enabling efficient Cr(VI) removal and stable electricity generation, and providing a new strategy to construct long-term stable bioelectrochemical systems for heavy metal-containing wastewater treatment. Full article

Fuzzy multi-criteria decision-making is important for technology assessment when expert judgments contain uncertainty, hesitation, and inconsistent evidence. This study develops a T-Spherical Fuzzy-Valued Neutrosophic Set (T-SFVNS)-based MEREC-EDAS framework for evaluating low-carbon cooling and energy-management technologies for data centers. Expert linguistic assessments are represented by T-Spherical Fuzzy-Valued Neutrosophic Numbers and aggregated before a score function is used at the explicit scalarization boundary. Standard MEREC then derives objective criterion weights from criterion-removal effects, and standard EDAS ranks alternatives by their positive and negative distances from the average score profile. The application evaluates nine technologies against ten criteria using assessments from thirty domain specialists. The corrected MEREC calculation assigns the greatest weights to carbon reduction potential (0.127), electricity demand reduction (0.125), maintenance complexity (0.124), operational cost efficiency (0.123), and cooling efficiency (0.123). The final ranking is Direct-to-Chip Liquid Cooling, Liquid Immersion Cooling, AI-Enabled Energy Management, Water-Side Free Cooling, Free-Air Cooling, Rear-Door Heat Exchanger Cooling, Hot/Cold Aisle Containment, Renewable-Powered Cooling, and Thermal Storage-Assisted Cooling. Weight perturbation, q-parameter, leave-one-expert-out, alternative-deletion, dominated-alternative, and multi-method comparisons show that the leading tier is robust, although the exact order of the two liquid-cooling technologies is sensitive in some scenarios. The findings provide a transparent and reproducible decision-support basis while explicitly acknowledging the information compression and rank-reversal limitations of score-based MCDM. Full article

Drug discovery is still an expensive and time-consuming process where finding the right drug associations is important for therapeutic development. In this paper, a new system is proposed for drug design called PharmaGraphFormer (PGF). It consists of five stages: (i) Data acquisition and preprocessing (DAP), (ii) Feature extraction and feature fusion (FEF), (iii) Molecular representation (MR), (iv) Multi-task prediction, and (v) Explainable artificial intelligence (XAI). This study employs a hybrid graph neural network (GNN)-transformer architecture that combines structural and sequence-based representations. Through DAP, several processes are executed, including the imputation or removal of missing values, outlier rejection, and class balancing. Next, through FEF1, features are extracted to represent the input data efficiently. Initially, compound-protein features are generated to document the interactions and relationships between chemical compounds and their corresponding target proteins. Secondly, drug characterizations are computed to encapsulate the physical, chemical, and structural attributes of each drug. After that, MR is performed using a graph-based molecule representation. Then, a novel model integrating GNNs and graph transformers, termed GNN-T, is proposed. Initially, GNNs represent the most promising deep learning models adept at processing non-Euclidean data. The Graph Transformer layer enhances atom representations by consolidating the representations of adjacent atoms through an attention mechanism. Finally, XAI is applied to explain the internal mechanisms of AI systems, rendering them comprehensible and interpretable. Across five independent runs, the proposed model achieved an accuracy of $0.963\pm 0.002$, a precision of $0.971\pm 0.002$, a recall of $0.958\pm 0.003$, an F1-score of $0.964\pm 0.002$, and a ROC-AUC of $0.993\pm 0.001$. These results demonstrate an outstanding performance when compared with all other models and emphasize that the proposed model is reliable in solving the problems of prioritizing compounds in line with the latest developments in AI-powered virtual screening and drug–target interaction modeling. Full article

Anthropogenic pollution of aquatic ecosystems presents a significant global challenge, underscoring the urgent need for resilient, biologically mediated remediation strategies. In this context, microalgae have emerged as a compelling solution, owing to their inherent adaptability to diverse environments and their capacity for efficient contaminant mitigation through bioremediation. These organisms possess the potential to sequester and remove a broad spectrum of pollutants from wastewater streams, including excess nutrients, organic substrates, heavy metals, and various emerging contaminants. Specifically, their metabolic versatility allows these microorganisms to tolerate and degrade complex substances such as recalcitrant micropollutants and hydrocarbons even under fluctuating environmental conditions. This review evaluates extremophilic microalgae as specialized biological agents capable of functioning under harsh anthropogenic stressors that may constrain the performance of microalgal strains commonly investigated for wastewater treatment. Their distinctive stress tolerance may provide advantages for treating wastewater characterized by extreme physicochemical conditions. By examining the unique metabolic pathways of these extremophiles, this analysis addresses critical gaps in the current bioremediation literature regarding the practical scalability and economic viability of integrating such specialized biomass into large-scale treatment infrastructure. Full article

The present work presents a new synthetic jet piezoelectric pump designed to address the airflow delivery needs arising from the increasing power density of high-performance microelectronics. Traditional miniaturized cooling techniques suffer from low efficiency, bulky size, and high cost, while microfluidic cooling has emerged as a vital chip thermal management method with outstanding miniature heat removal capacity. We systematically designed the vibration mode and pump structure, adopting the sixth-order resonant frequency as the operating frequency. A dual resonant layer with stiffness-guided fixed boundaries was employed to enhance vibration efficiency and energy conversion, together with an optimized flow channel layout and parametric design. Experiments conducted under 35 V square-wave excitation demonstrate that the 20 mm × 20 mm × 2.5 mm pump delivers a flow rate of 1.6 L/min and a back pressure of 2.7 kPa. This work provides a feasible technical route for large-scale airflow delivery applications of synthetic jet piezoelectric pumps, with potential for thermal management in microelectronic devices, while balancing excellent performance and low manufacturing cost. Full article

This study presents an electrothermal coating approach for synthesizing cell-imprinted polymers (CIPs) on metallic microwires through localized resistive heating-induced polymerization. Imprinted polymers (IPs) are robust, cost-effective synthetic affinity materials widely used in sensing applications. However, conventional fabrication methods, including bulk and suspension polymerization, often lack spatial control, producing non-specific polymerization, heterogeneous coatings, and reduced sensor reproducibility. Electrochemical polymerization provides improved spatial control but requires specialized instrumentation and restricts monomer selection. Here, applying direct current (DC) to metallic microwires immersed in a prepolymer solution generated localized Joule heating, enabling controlled in situ polymerization and uniform coatings while minimizing undesired bulk polymerization. By optimizing the applied current and polymerization time, CIP coatings with tunable thicknesses were fabricated on gold-coated microwires. Under optimized conditions, ~6 µm thick coatings were imprinted using Salmonella templates. Scanning electron microscopy revealed bacteria-shaped cavities consistent with template removal and the formation of imprinted cavities. Rebinding experiments demonstrated enhanced bacterial capture, with CIP-coated microwires achieving ~70% capture efficiency, compared to 22% for bare microwires and 33% for non-imprinted polymer (NIP) controls. These results support the effectiveness of the proposed method for localized polymerization and demonstrate the enhanced capture of the template species by CIP-coated microwires relative to bare microwires and NIP-coated controls. Full article

Woody biomass is often promoted as a low-carbon energy source in global decarbonization efforts. However, LCA (life cycle assessment) evaluations of woody biomass-to-energy systems show very different environmental performance. Variations in technology and methodology across investigations can cause these inconsistencies. This review paper analyzes methodologies of LCAs of woody biomass conversion routes such as combustion, combined heat and power, gasification, pyrolysis, torrefaction-assisted systems, and new bioenergy with carbon capture configurations. A systematic literature review was conducted using Scopus, SpringerLink, and ScienceDirect, identifying 4272 records, of which 98 studies were retained for detailed analysis following the application of defined inclusion and exclusion criteria. Functional unit selection, from biomass mass per unit to power or heat per unit, is highly variable, affecting comparability. Forest carbon stock fluctuations, infrastructure, and end-of-life treatment are inconsistently included in cradle-to-grave system boundaries. Static GWP100 methods are often used in biogenic carbon removal without considering temporal carbon dynamics. The importance of pretreatment steps like drying, pelletizing, and torrefaction cannot be overstated, even though they have a direct impact on the quality of the fuel, the efficiency of transportation, and the effectiveness of the conversion process downstream. The large range of stated emission levels for comparable technologies is further influenced by logistics assumptions, plant scale, and allocation mechanisms in cogeneration systems. The review synthesizes these methodological differences and proposes a harmonization methodology to increase woody biomass LCA transparency and comparability. By identifying important sources of outcome variability, this study helps policymakers, project developers, and industry stakeholders evaluate biomass energy investments and bring clarity to environmental decisions. Full article

In the present research, the application of a photocatalytic reactor operated under simulated solar-light-assisted air gap membrane distillation (AGMD) is proposed to remove ketoprofen from seawater. TiO₂ at a concentration of 1 g/L, containing sulfur, was applied as a photocatalyst. The AGMD process was carried out under a feed temperature of 60–80 °C and a membrane area of 131 cm² during long-term operation. Simulated solar light was applied as an irradiance source. At the first stage of the process, the feed was concentrated for 73 h, and after that, the solution of seawater spiked with ketoprofen was photocatalytically treated for 96 h. Based on the experiments, it was found that 51% of ketoprofen was removed after the solar-driven photocatalysis process. Pure distillate without salts (conductivity below 2 µS/cm) and ketoprofen were obtained after 73 h. The performance of the membrane exhibited ca. two times higher permeate flux at an operation temperature of 80 °C in comparison with 60 °C, i.e., 24.7 L/h·m² and 47.3 L/h·m², respectively. Despite the presence of small deposits on the membrane surface, no membrane wetting was observed. The concentration of ketoprofen in the concentrates during the AGMD process and solar-driven photocatalysis can remove this pharmaceutical even from matrices enriched with salts (high AGMD concentrate), with good efficiency. Full article

Retrieval-augmented fine-tuning (RAFT) can improve small language models (sLMs) on retrieval-grounded question answering, but the synthetic training data produced by commercial large language models (LLMs) vary in quality. This paper contributes a quality-aware selection protocol—rather than a new RAFT or QLoRA method—that scores LLM-generated alternatives along four embedding-based dimensions (question relevance, answer faithfulness, QA coherence, and semantic similarity) and selects one alternative per task before parameter-efficient fine-tuning. Under pre-specified paired-bootstrap contrasts with Holm correction, the parameter-free faithfulness-based selector only-AF significantly exceeds random selection on Gemma-2-9B-IT (ΔF1 = +0.106, 95% CI [+0.043, +0.174], Holm-corrected p = 0.019), and its pre-specified weighted companion af-70 (w_AF = 0.70) shows the same confirmed pattern (Holm-corrected p = 0.002). Both effects persist under a Korean character-level F1 that removes particles and punctuation (Holm-corrected p = 0.004 and p = 0.042), indicating robustness to the choice of lexical metric. Relative to training on the full 150-row augmented pool, the quality-selected 50-row sets are statistically indistinguishable while using one third of the training data, which we interpret as data efficiency rather than superiority. Across six instruction-tuned models (2B–27B), a significant selector-by-model interaction indicates that the optimal quality axis is model-dependent, and the two smallest models show no benefit from selection. The study’s confirmatory contrasts use a small controlled Korean corpus under a transductive design; two pre-registered validation experiments probe external validity. On an independent five-fold larger corpus with a passage-level train/test split, fine-tuning transfers strongly and the selected one-third subsets show no significant difference from the full pool, while the advantage over random selection is directionally positive but small and not significant; under controlled corruption of 35% of the pool, the metrics detect the damaged rows, and for the score-sum selector the selection-versus-random benefit is significantly larger than on the clean pool (difference-in-differences p = 0.0014; directionally consistent but not significant for the faithfulness selectors). Within this scope, quality-aware selection is a promising, data-efficient safeguard for synthetic RAFT data—performing comparably to full-pool training at one third of the cost, with growing value as pool quality degrades—and larger-scale external validation remains future work. Full article

Germanium is a critical rare-dispersed metal with irreplaceable applications in infrared optics, fiber-optic communications, and semiconductor industries, making its efficient recovery from secondary resources of great strategic importance. This study investigates the selective recovery of germanium from complex zinc smelting leachates using a novel hydroxamic acid extractant, BGYW, in synergistic combination with P204. The feed solution contained approximately 360 mg/L Ge, 10,790 mg/L Fe²⁺, and 98,530 mg/L Zn, representing a highly complex matrix. Continuous counter-current extraction was performed in a 30-stage miniature mixer-settler. Under optimized conditions of 10% BGYW + 5% P204 in white oil, an O/A ratio of 1:1, and 8 mol/L NH₄F as strippant, the single-stage germanium extraction efficiency reached 99.4%. Over 16 consecutive cycles, the extraction system maintained stable performance with average germanium extraction above 99%. A 3-stage scrubbing section using 50 g/L H₂SO₄ effectively removed co-extracted Zn, Cu, and Al impurities. Iron co-extraction, a major challenge, was successfully mitigated through a 2–3 stage iron scrubbing step using a chloride-containing scrubbing solution, which reduced the iron concentration in the strip liquor from approximately 600 mg/L to below 4 mg/L, and decreased the Fe/Ge mass ratio from 0.197 to below 0.01. The overall germanium recovery across the entire 30-stage continuous process reached 98.82%, and the dissolution loss of BGYW in the aqueous phase was reduced by over 85% compared to the conventional YW100 extractant. Third-phase formation caused by residual organic flocculants from the leaching step was eliminated through enhanced pre-treatment, while ferric fluoride precipitation in the stripping section was resolved by incorporating the iron scrubbing stage. This study demonstrates that the BGYW-P204 extraction system with the integrated iron scrubbing step offers an efficient, stable, and industrially viable approach for germanium recovery from zinc smelting leachates, providing a practical solution to the long-standing challenge of germanium–iron separation and contributing to the sustainable supply of this critical metal. Full article

Androgenetic alopecia (AGA) is a prevalent clinical disorder, and the key pathogenic factor is dihydrotestosterone (DHT) present in the pilosebaceous unit. Current clinical therapeutic options are often associated with notable adverse effects, highlighting the urgent need for safer and more effective interventions. Herein, a novel amphiphilic covalent organic framework (amCOF) is designed and synthesized. By simultaneously incorporating hydrophilic functional groups and lipophilic alkyl chains into the covalent organic skeleton, the material exhibits excellent amphiphilicity, high specific surface area, and well-ordered porous structures. Owing to its amphiphilic nature, amCOF disperses uniformly in aqueous physiological media and adapts favorably to the lipophilic microenvironment within hair follicles. Furthermore, the ordered porous architecture endows amCOF with rapid DHT adsorption kinetics, high adsorption capacity, and high removal efficiency. Functional assays demonstrate that amCOF effectively reverses the inhibitory effects of DHT on the proliferation and migration of human dermal papilla cells. In animal models, topical application of amCOF significantly reduces local DHT concentrations, promotes hair regrowth, and shows favorable biosafety profiles. Collectively, this work provides a new strategy for treating androgenetic alopecia by scavenging pathogenic lipophilic molecules from sebum using amphiphilic porous materials and also establishes a solid foundation for expanding the biomedical applications of COFs. Full article