Search Results (979)

Aluminium alloys are extensively considered in aviation and automobiles owing to their lightweight properties and favourable specific strength-to-weight ratio. Generally, the poor surface properties of these alloys limit their application, particularly in sliding conditions. To enhance the surface qualities, particularly the material’s wear resilient features, a unique surface modification process using electro-discharge coating (EDC) has been employed. This work investigates the optimisation of coating variables produced by the EDC technique utilising green compact electrodes composed of 50 wt.% tungsten disulfide (WS₂) and 50 wt.% copper (Cu) powder. The substrate material utilised was AA7075 alloy. The Taguchi–TOPSIS approach was employed to determine optimal EDC process variables, with pulse-on time (T_on), current (I_p), and pulse-off time (T_off). Wear rate (WR), surface roughness (SR), and friction coefficient (CoF) were used to assess the coating features. A wear study was performed with a pin-on-disc device with an undeviating sliding speed (0.25 m/s) and a 25 N load. The results revealed that the supreme features derived from the linear plots were I_p (4 A), T_on (80 µs), and T_off (5 µs). The ANOVA found that I_p had the utmost significant impact, accounting for 44.09%; T_off, 28.01%; T_on, 20.33%; and minimum error, 8.58%. A validation trial with perfect parameters returned values of 0.000179 mm³/Nm (WR), 0.204 (CoF), and 2.818 µm (SR). These findings are significantly better than those of the other coatings. The discrepancy among the estimated and experimental relative closeness in optimal settings is 6.34%, demonstrating that the Taguchi–TOPSIS method is more appropriate for multi-criteria optimisation. Full article

Oral squamous cell carcinoma (OSCC) remains a major clinical challenge, highlighting the need for novel therapeutic strategies. Natural bioactive compounds such as curcumin (Cu) and cordycepin (Co) have shown anticancer potential; however, their effects on cancer cell morphology and behavior remain incompletely characterized. This study assessed the individual and combined effects of Cu and Co on oral squamous cell carcinoma cells (OECM-1) and normal human gingival epithelial cells (HGEpiC) over 24 and 48 h. Metabolic activity, membrane integrity, oxidative stress, apoptosis, and inflammatory responses were evaluated using MTT, LDH, ROS-H₂O₂, caspase 3/7, and NO assays. Label-free digital holographic microscopy enabled real-time monitoring of morphology, motility, and proliferation. Both compounds induced ROS-mediated cytotoxicity, but responses were notably more pronounced in OECM-1 than in HGEpiC cells. Real-time morphological profiling revealed distinct response patterns: Co primarily exerted cytostatic effects, whereas Cu induced cell shrinkage, impaired motility, and inhibited cell division. The combination treatment (CC) largely reflected Cu-driven morphological and functional changes, with Co coexisting without counteracting Cu’s effects. Taken together, these findings reveal compound-specific mechanisms of action for Cu and Co in OSCC therapy. Full article

Owing to the high stability and low cost of nanozymes, they have been extensively investigated and reported. In this work, highly active CeO₂ nanoflowers were first prepared and then different metal elements were doped into the CeO₂ nanoflower matrix via a novel synthesis method to fabricate M-CeO₂ (M = Cu, Fe, Co, Mn, La) nanomaterials. Mn-CeO₂ with the highest peroxidase-like activity was selected via systematic screening, the as-prepared Mn-CeO₂ nanocomposites exhibited enhanced enzyme-like activity due to the strong metal-support interaction. This article explored the effects of doping ratio, pH, temperature, reaction time, and material concentration on its activity. A simple sensitive and selective colorimetric method was established and successfully used to detect hydrogen peroxide and ascorbic acid sensitively. When the hydrogen peroxide (H₂O₂) concentration is within the 2.0–120.0 μM range, the UV-visible absorbance at 652 nm was associated linearly with the H₂O₂ concentration, R² = 0.9959, LOD = 1.7 μM (S/N = 3). The absorbance of the reaction system showed a good linear relationship with the ascorbic acid (AA) concentration (1.0–40.0 μM, R² = 0.992), LOD = 0.98 μM (S/N = 3). This study provides an effective way to construct efficient nanozymes and their potential applications in sensing and detection. Full article

Indium Tin Oxide (ITO) is one of the most widely used ohmic materials for fabricating ohmic layers in thin-film solar cells. ITO thin layers have reached almost the maximum theoretical conductivity and the lowest practical resistivity. Along with indium’s toxic environmental impact and the high cost of materials, these are the reasons why new materials for efficient, cheaper thin-film transparent ohmic layers are being examined. One of those materials is copper-doped zinc oxide (ZnO:Cu). In this paper, we present a new approach to copper-doped zinc oxide fabrication methods, based on the modern authorial Physical Vapor Co-Deposition technique, which involves optimizing Cu concentration to fine-tune crystal structure, optical band gap, and electrical properties, creating n-type TCOs essential for efficient charge transport in next-generation thin films perovskite solar cells. Full article

This study presents a quantitative investigation of substituent effects on the stability of 1:2 complexes formed between para-substituted 2-phenylbenzimidazole ligands and Cu(II) or Co(II) ions. The ligands, featuring hydroxyl (–OH), chloro (–Cl), and nitro (–NO₂) substituents, were synthesized via copper acetate-mediated oxidative cyclization. Stability constants (log K) were determined spectrophotometrically using both the Benesi–Hildebrand and Job methods, which yielded perfectly consistent results and confirmed ML₂ stoichiometry. For both metal series, the stability decreases in the order –OH > –Cl > –NO₂. Excellent linear correlations were obtained between log K and Hammett σ constants, yielding reaction constants of ρ = −0.79 for Cu(II) and ρ = −1.00 for Co(II). These negative ρ values confirm that electron-donating substituents enhance complex stability by increasing electron density on the donor nitrogen. Furthermore, the stability constants for Cu(II) complexes are approximately two orders of magnitude higher than those for Co(II), in agreement with the Irving–Williams series. This work establishes a clear, predictive structure–stability relationship and validates the combined methodological approach for quantifying metal–ligand interactions in tunable benzimidazole systems. Full article

Co-pyrolysis of sludge and plastics has gradually emerged as a crucial technical approach for waste reduction and resource recovery. This study develops high-precision, interpretable prediction models and quantifies the contributions of core risk factors to environmental risks. Based on the experimental datasets from 2015 to 2025, which include operational parameters and eight potential toxic elements (PTEs) with four chemical speciation fractions: acid-soluble/exchangeable (F1), reducible (F2), oxidizable (F3), and residual (F4), we constructed six machine learning models. Based on the experimental datasets from 2015 to 2025, which include operational parameters and eight potential toxic elements (PTEs) chemical speciation (F1–F4), we constructed six machine learning models. Feature importance analysis and Shapley Additive Explanation (SHAP) analysis were employed to identify core risk factors and interpret the model’s decision logic. Results indicate that XGBoost, Random Forest and CatBoost outperform other models, achieving test accuracies of 0.94, 0.92, and 0.90, with weighted F1-Scores of 0.94, 0.92, and 0.90, respectively. Feature importance highlights the most important features for the six different models, with Cd-F4, As-F1, and Cu-F4 contributing most significantly to the model predictions. SHAP analysis quantified the contributions of each feature to the model predictions, verified Cd-F4 as the primary risk discriminant, and further revealed that F1 and F4 of PTEs are key factors in distinguishing risk levels. This study proposes an interpretable machine learning framework, providing a theoretical basis for the optimization of the sludge and plastic co-pyrolysis process and the assessment of potential risks. Full article

In this study, a novel “Physics-Informed Hybrid Machine Learning” framework was developed to model and optimize the complex combustion and carbon-based emission characteristics of Cu₂O nano-additive doped diesel fuel. To reduce reliance on purely empirical correlations, the proposed framework integrates alterations in fuel physical properties into the prediction loop, thereby enhancing physical consistency and model generalizability. The methodology comprises data pre-processing, modeling via Gaussian Process Regression (GPR) with an Automatic Relevance Determination (ARD) kernel, and multi-objective optimization using NSGA-II. Experimental tests were conducted at a constant engine speed of 2000 rpm under varying load conditions. The developed hybrid model exhibited high predictive accuracy, particularly for performance metrics and gaseous emissions (e.g., R² > 0.95 for BSFC and CO). ARD-based feature importance analysis confirmed that nano-additive dosage plays a critical role in the fine-tuning of emissions. Crucially, the optimization algorithm identified a nano-additive dosage of ~29 ppm and an engine load of 15.5 Nm as the optimal operating point for the simultaneous improvement of performance and carbonaceous emissions. This finding, exploring the unmeasured design space, demonstrates the framework’s capability to discover optimal conditions beyond discrete experimental points. Full article

In this work, Fe, Co, Ni, Cu, and Mo powders were used as starting materials to prepare high-entropy alloy (HEA) thin films by a coating and vacuum sintering process. Using the HEA thin film as the substrate, selenium was subsequently deposited by chemical vapor deposition (CVD) to obtain high-entropy alloy selenide thin films (HEASe). The phase structure, surface chemical states, morphology, and elemental distribution of the porous films were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS). The electrocatalytic hydrogen evolution performance of the electrodes was evaluated using a three-electrode configuration in 0.5 M H₂SO₄, 1 M KOH, 1 M KOH + 0.5 M NaCl, and 1 M KOH + 0.5 M Na₂S solutions. The results indicate that the HEA selenide thin-film electrodes exhibit favorable electrocatalytic behavior in all four electrolytes. Among them, HEASe-450 shows the best overall performance. In 0.5 M H₂SO₄, it requires an overpotential of only 57.6 mV to reach a current density of 10 mA cm⁻², with a Tafel slope of 146.96 mV dec⁻¹. In 1 M KOH, the overpotential at 10 mA cm⁻² is 50.1 mV, and the corresponding Tafel slope is 142 mV dec⁻¹. In 1 M KOH + 0.5 M NaCl, the overpotential is 52.7 mV with a Tafel slope of 122.72 mV dec⁻¹. In 1 M KOH + 0.5 M Na₂S, an overpotential of 85 mV is required, and the Tafel slope increases to 236 mV dec⁻¹. Full article

Catalysis has entered everyday life through a range of technological processes that rely on different catalytic systems. The increasing demand for such systems requires rationalization of the use of their expensive components, such as noble-metal catalysts. As such, a catalyst with low noble-metal concentration, in which each one of the noble atoms is active, would reach the lowest price possible. Nevertheless, no clear reactivity descriptors have been outlined for this type of low-coordinated supported atom. Using DFT calculations, we consider three diverse systems as models of single-atom catalysts. We investigate monomers and bimetallic dimers of Ru, Rh, Pd, Ir, and Pt on MgO(001), Cu adatom on thin Mo(001)-supported films (NaF, MgO, and ScN), and single Pt adatoms on oxidized graphene surfaces. The reactivity of these metal atoms was probed by CO. In each case, we see the interaction through the donation–backdonation mechanism. In some cases, CO adsorption energies can be linked to the position of the d-band center and the adatom’s charge. A higher-lying d-band center and less-charged, supported single atoms bind CO more weakly. Also, in some cases, metal atoms that are less strongly bound to the substrate bind CO more strongly. The results suggest that the identification of common activity descriptor(s) for single metal atoms on foreign supports is a difficult task with no unique solution. However, it is also suggested that the stability of adatoms and strong anchoring to the support are prerequisites for the application of descriptor-based search to novel single-atom catalysts. Full article

Murunskite (K₂FeCu₃S₄) is a layered sulfosalt chalcogenide that occupies a unique position between the cuprate and iron pnictide families: it shares electronic characteristics with the former and adopts the crystal structure of the latter. Despite a completely random distribution of magnetic Fe within a nonmagnetic Cu matrix, murunskite exhibits a well-defined quarter-zone antiferromagnetic transition at 97 K and complete orbital order below 30 K. These findings reveal the unexpected emergence of long-range order in a high-entropy-like environment. This inherent robustness to site disorder in a layered structure makes murunskite a paradigmatic system for further studies. Here, we investigate doping strategies in murunskite to assess how its electronic and magnetic properties can be tuned. Using melt-growth techniques, we achieve substitutions at the magnetic metal site (Fe), spacer cation (K), and sulfur ligand (S), which significantly influence transport and magnetic properties. In addition, we use ionic-liquid gating on the parent compound and observe a gate-dependent suppression of resistivity, confirming the potential for electrostatic control over transport. Our results demonstrate the chemical and electronic plasticity of murunskite, offering a valuable platform for co-engineering disorder, magnetism, and transport, and opening avenues to explore quantum phenomena in correlated and high-entropy materials. Full article

In permanently submerged coastal wetlands, interactions between biogeochemical processes and microbial communities strongly influence greenhouse gas (GHG) fluxes. To improve our understanding of how redox-driven processes shape GHG dynamics in these ecosystems, we investigated the relationships among iron (Fe) pools, microbial dynamics, and the potential GHG production in subaqueous soils from an interdunal wetland in San Vitale Park (Italy), permanently submerged and affected by seasonal oscillations of the saline water table. Two subaqueous soil columns (WAS-2 and WAS-4), collected from similar settings, were analyzed. Surface layers of WAS-4 showed higher salinity and carbonate content, whereas WAS-2 was characterized by overall higher Fe concentrations. Distinct vertical distributions of organic matter and sulfur (S) were shown along depth. Laboratory incubations revealed that nitrous oxide (N₂O) production was up to ten times higher in WAS-2 than in WAS-4, with peaks in the top 13–14 cm, consistent with more active nitrification-denitrification in surface layers. Methane (CH₄) and carbon dioxide (CO₂) fluxes decreased with depth, reflecting reduced availability of labile carbon. Methanomicrobiales dominated CH₄-producing layers, indicating hydrogenotrophic methanogenesis, while amoA-carrying Nitrosomonadales and Thaumarchaeota, occurred in shallow, organic-rich layers where ammonia supported nitrification and denitrification. Denitrifiers mainly belonged to α- and β-Proteobacteria, consistent with their direct contribution to N₂O peaks. Spearman’s correlations showed N₂O positively correlated to sulfur and labile carbon (C), supporting denitrification under moderately reducing conditions. CH₄ and CO₂ positively correlated with organic C (Corg), total nitrogen (TN), and reactive Fe forms, reflecting redox-mediated microbial respiration and methanogenesis. Trace elements (B, Cr, Cu, Ni) acted as micronutrients or inhibitors depending on concentration. Canonical correspondence analysis indicated depth-structured links among gas fluxes, soil chemistry (Corg, TN, S/C, CaCO₃, P), and microbial distributions: surface layers, rich in labile C and nutrients, supported active bacteria and archaea involved in decomposition, nitrification, and denitrification, whereas deeper layers hosted oligotrophic archaea adapted to inorganic substrates. Overall, Fe pools appeared to be associated with soil processes relevant to GHG dynamics, although the extent of their regulatory role remains uncertain due to potential alterations of redox-sensitive Fe fractions during sample handling. These results contribute to broader efforts to predict GHG emissions in submerged wetland soils by linking redox stratification, inorganic chemistry, and microbial functional groups. Full article

The electrochemical reduction of CO₂ offers a sustainable approach to transforming carbon dioxide into value-added products when powered by renewable energy. However, current electrocatalysts lack efficiency and selectivity, hindering commercial application. Combining tin’s high formate selectivity with copper’s ability to reduce CO₂ via COOH* pathway offers a promising strategy. This synergy mitigates copper’s low selectivity, providing a cost-effective catalyst with enhanced performance over pure Sn-based systems. This work investigates CuSn bimetallic electrocatalysts synthesised by scalable electrodeposition onto gas diffusion layers to boost formate production. Catalytic performance and cell potential were evaluated at current densities ranging from 50 to 200 mA cm⁻² and varying Sn compositions. Catalysts with Sn content below 4% predominantly formed CO and H₂, but smaller particles and improved metal dispersion increased formate production. A catalyst containing 12% Sn achieved a maximum faradaic efficiency (FE) of 52% at 50 mA cm⁻² with an iR-corrected potential of −0.56 V vs. SHE. At 200 mA cm⁻², it exhibited a 30% FE for formate, along with 31% FE for CO and 9.3% FE for H₂, while other gases contributed to less than 4% FE, indicating potential as syngas feedstock. Higher Sn content, combined with smaller, well-distributed particles, effectively suppressed H₂, CO, and other by-products, highlighting a strong dependence of FE on Sn content and bimetallic distribution, demonstrating compositional tuning importance via electrodeposition. Full article

In this study, a novel material was obtained by functionalizing shredded maize stalk (MS) with Alizarine Red S (ArS), a complexing agent that contains −OH and −C=O groups in its structure (MS-ArS). The obtained MS-ArS was employed in adsorption studies for Mn²⁺, Pb²⁺, Cu²⁺, Cr³⁺, Zn²⁺, and Fe³⁺ (Mⁿ⁺) removal from mixed aqueous matrices. Initially, complex formation between (Mⁿ⁺) and ArS in buffer solution at pH 4 and 10 was investigated using the UV-Vis spectrometric method. Continuous, the functionalization process of MS with ArS was tested at several pH values (2, 4, 6, 8, and 10) using a batch technique. It was observed that the best functionalization of MS with ArS was obtained at pH = 2. Subsequently, Mⁿ⁺ adsorption onto the MS-ArS mass was tested separately at pH 4 and 10. The study achieved that Mⁿ⁺ adsorption proved to be pH dependent. The results confirmed that at pH = 10, Mⁿ⁺ adsorption was increased, compared with pH = 4. MS-ArS has affinity for Mⁿ⁺ in the following order Fe³⁺ > Cu²⁺ > Zn²⁺ > Mn²⁺ > Pb²⁺ > Cr³⁺. Experimental data revealed remarkable desorption rates when 0.5 M HCl was used. After five adsorption/desorption cycles of Mⁿ⁺, the removal capability of MS-ArS was preserved. Overall, the potential of MS-ArS for effective Mⁿ⁺ removal/reuse makes it a sustainable polymer for wastewater treatment applications. Full article

With the deepening of deep mineral exploration, traditional methods face bottlenecks in identifying concealed orebodies, making the establishment of a mineralogical exploration indicator system for collision-type porphyry deposits imperative. This study investigates chlorite from the Cimabanshuo Porphyry Copper Deposit in the Zhunuo Ore Concentration Area of the Western Gangdese via systematic petrographic and in situ geochemical analyses, to elucidate the spatial evolution of its trace element compositions and assess the validity and applicability of different trace elements for hydrothermal center indication. Based on micropetrographic observations, chlorite is classified into three types: biotite-altered (Chl-1), amphibole-altered (Chl-2) and vein-type (Chl-3), with Chl-1 and Chl-2 significantly affected by primary mineral compositions. Trace element results show that spatial variations in Ti, Li, Ni, Co, Mn, and Sr contents and Li/Mn and Ti/Sr ratios in chlorite can clearly indicate the mineralization center—Ti, Li, Ni and Co are systematically enriched in the proximal ore zone by temperature and fluid compositional effects, while Mn and Sr are enriched in the distal ore zone due to elemental redistribution during fluid migration. Fitting analysis of chlorite elemental ratios against the distance from sampling points to the mineralization center indicates the Li/Mn ratio decreases with increasing distance (R² = 0.4665), consistent with elemental distribution and showing a certain correlation; in contrast, the Ti/Sr ratio has a fitting coefficient of determination of only 0.0581, which cannot serve as an effective analysis indicator for this study because the deposit’s plate collision metallogenic setting causes elemental migration to be disturbed by local geological factors. In addition, chlorite in the zones 0–500 m from the Cu I, Cu II, and Cu III orebodies and 1–1.5 km to the north is characterized by significant enrichment of Ti, Li, Ni, and Co, depletion of Mn and Sr and high Li/Mn ratios. Accordingly, a concealed hydrothermal center is inferred in the northern part of the Cimabanshuo Deposit beyond the proven orebodies. Comprehensive studies confirm that the spatial variation characteristics of trace elements in chlorite from the Cimabanshuo Porphyry Copper Deposit have high applicability for indicating hydrothermal mineralization centers. Full article

In this study, FeCoNiMoCu high-entropy alloy thin films were sulfided at different temperatures ranged from 250 °C to 450 °C by chemical vapor deposition, and the resultant sulfided Fe-Co-Ni-Mo-Cu-S alloys were characterized by means of XRD, SEM, XPS and EDS. HER performance tests were carried out in four electrolyte systems, namely 0.5 M H₂SO₄, 1 M KOH, 1 M KOH + 0.5 M NaCl and 1 M KOH + 1 M Na₂S. The results indicated that the as-prepared electrodes exhibited low HER overpotentials in all four electrolytes, with the optimal catalytic performance consistently achieved at a sulfidation temperature of 350 °C. Among the tested systems, the electrode delivered the best HER activity in 0.5 M H₂SO₄, showing an overpotential of merely 53 mV and a Tafel slope of 86.72 mV dec⁻¹ at a current density of 10 mA·cm⁻². In 1.0 M KOH, the overpotential required to reach the same current density was 98 mV with a Tafel slope of 72.43 mV dec⁻¹. For the mixed electrolyte of 1 M KOH and 0.5 M NaCl, the overpotential at 10 mA·cm⁻² was 142 mV accompanied by a Tafel slope of 49.51 mV dec⁻¹. In contrast, the 1 M KOH + 1 M Na₂S electrolyte yielded an overpotential of 77 mV and a Tafel slope of 84.01 mV dec⁻¹ at the identical current density. HER tests revealed that the sulfidation temperature exerts a significant influence on the formation and distribution of active phases of multi-metal sulfides (e.g., FeS_x, CoS_x, NiS_x, MoS₂) on the electrode surface. The electrodes prepared at an appropriate sulfidation temperature exhibit a larger specific surface area and enhanced hydrogen evolution reaction performance for water electrolysis. These findings may provide useful references for other researchers in the design and fabrication of high-entropy alloy-based HER catalysts. Full article