Metal Content Research Articles

Treating waste with waste: New insight into phosphorus removal by graphitic carbon nitride modified water treatment sludge-based ceramsite

This study developed a novel ceramsite adsorbent, combining water treatment sludge (WTS) and graphite carbon nitride, which aimed at removing phosphate from wastewater to realize the sustainable development strategy of ‘treating waste with waste’. The optimal conditions for the preparation of N-modified WTS (NWTS)-based ceramsite were determined as follows: NWTS: bentonite: CaCO3=1:0.4:0.5, preheating at 450 °C for 15 min, and calcinating at 1100 °C for 15 min. The study examined the effects of pH, ceramsite dosage, initial phosphorus concentration, and temperature on phosphate removal, and it assessed the potential risk of heavy metal release from the ceramsite during application. The result indicated that phosphorus adsorption of the ceramsite reached 0.5 mg/g at pH=6, T=303 K, Pinitial=1 mg/L and dosage of 2 g/L, achieving 100% removal efficiency. The adsorption process of phosphate by ceramsite followed pseudo-second order kinetic and the Sips model, suggesting that the adsorption mechanism involved multilayer chemisorption. Ligand exchange reaction was the primary driver of adsorption, with hydrogen bonding further augmenting the adsorption efficiency. Additionally, the heavy metal content released by the ceramsite was significantly below the relevant standard limits, confirming its excellent feasibility and safety. These characteristics suggested that the ceramsite adsorbent had broad application potential in actual wastewater treatment process.

Impact of Systematic Modeling Uncertainties on Kilonova Property Estimation

The precise atomic structure and therefore the wavelength-dependent opacities of lanthanides are highly uncertain. This uncertainty introduces systematic errors in modeling transients like kilonovae and estimating key properties such as mass, characteristic velocity, and heavy metal content. Here, we quantify how atomic data from across the literature as well as choices of thermalization efficiency of r-process radioactive decay heating impact the light curve and spectra of kilonovae. Specifically, we analyze the spectra of a grid of models produced by the radiative transfer code Sedona that span the expected range of kilonova properties to identify regions with the highest systematic uncertainty. Our findings indicate that differences in atomic data have a substantial impact on estimates of lanthanide mass fraction, spanning approximately 1 order of magnitude for lanthanide-rich ejecta, and demonstrate the difficulty in precisely measuring the lanthanide fraction in lanthanide-poor ejecta. Mass estimates vary typically by 25%–40% for differing atomic data. Similarly, the choice of thermalization efficiency can affect mass estimates by 20%–50%. Observational properties such as color and decay rate are highly model dependent. Velocity estimation, when fitting solely based on the light curve, can have a typical error of ∼100%. Atomic data of light r-process elements can strongly affect blue emission. Even for well-observed events like GW170817, the total lanthanide production estimated using different atomic data sets can vary by a factor of ∼6.

Mining soil heavy metal inversion based on Levy Flight Cauchy Gaussian perturbation sparrow search algorithm support vector regression (LSSA-SVR)

Soil heavy metal pollution in mining areas poses severe challenges to the ecological environment. In recent years, machine learning has been widely used in heavy metal inversion by hyperspectral data. However, deterministic algorithms and probabilistic algorithms may confront local optimal solutions in practical applications. The local optimal solution is not the optimal value obtained within the entire defined interval, and as a result will affect the reliability of these approaches. This paper proposes a Levy Flight Cauchy Gaussian perturbation Sparrow Search algorithm Support Vector Regression (LSSA-SVR) soil heavy metal content prediction model. It introduces Levy Flight (LF) measurement and Cauchy Gaussian perturbation based on the Sparrow search algorithm. The LSSA-SVR model was shown to increase the breadth of solutions searched, avoiding the local optimal solution problem. When applied to mining soil heavy metal experiments, we found that the LSSA-SVR model gave a good fit for the elements Cu, Zn, As, and Pb. The correlation coefficients between the predicted results and the actual results of the four elements were all above 0.94. The heavy metal predicted results of LSSA-SVR have a small error margin in both the overall distribution and in individual differences. This study provides an efficient and accurate monitoring method for mining soil heavy metal inversion. It also provides strong support for environmental management and soil remediation.

Hyperspectral Inversion of Soil Cu Content in Agricultural Land Based on Continuous Wavelet Transform and Stacking Ensemble Learning

Heavy metal pollution in agricultural land poses significant threats to both the ecological environment and human health. Therefore, the rapid and accurate prediction of heavy metal content in agricultural soil is crucial for environmental protection and soil remediation. Acknowledging the limitations of traditional single linear or nonlinear machine learning models in terms of prediction accuracy, this study developed an ensemble learning model that integrates multiple linear or nonlinear learning models with a random forest (RF) model to improve both the prediction accuracy and reliability. In this study, we selected a typical copper (Cu) polluted area in the Pearl River Delta of Guangdong Province as the research site and collected Cu content data and indoor soil reflectance spectral data from 269 surface soil samples. First, the soil spectral data were preprocessed using Savitzky–Golay (SG) smoothing, multiplicative scattering correction (MSC), and continuous wavelet transform (CWT) to reduce noise interference. Next, principal components analysis (PCA) was employed to reduce the dimensionality of the preprocessed spectral data, eliminating redundant features and lowering the computational complexity. Finally, based on the dimensionality-reduced data and Cu content, we established a stacked ensemble learning model, where the base models included SVR, PLSR, BPNN, and XGBoost, with RF serving as the meta-model to estimate the soil heavy metal content. To evaluate the performance of the stacking model, we compared its prediction accuracy with that of individual models. The results indicate that, compared to the traditional machine learning models, the prediction accuracy of the stacking model was superior (R2 = 0.77; RMSE = 7.65 mg/kg; RPD = 2.29). This suggests that the integrated algorithm demonstrates a greater robustness and generalization capability. This study presents a method to improve soil heavy metal content estimation using hyperspectral technology, ensuring a robust model that supports policymakers in making informed decisions about land use, agriculture, and environmental protection.

Anomaly detection of heavy metal concentrations in water by Laser-Induced breakdown spectroscopy based on GAN-Transformer model

The diverse types of water quality anomalies and the challenges associated with obtaining abnormal water quality samples limited the development of laser-induced breakdown spectroscopy (LIBS) for water quality detection. This paper presents a GAN-Transformer anomaly detection model for the warning of heavy metal exceedance in water quality using LIBS. The experiment configured four categories of water matrix samples with 20 different concentrations of mixed chromium (Cr) and manganese (Mn) solutions. The GAN-Transformer anomaly detection model was employed to analyze these samples, and its performance was compared with five other anomaly detection models: LSTM-NDT, MAD-GAN, DAGMM, USAD, and Transformer. The results indicate that the GAN-Transformer anomaly detection model achieved the best identification results, with an accuracy of 97.68% and a recall of 97.57% on the test set. Compared to the Transformer model, the accuracy and recall were enhanced by 4.82% and 5.32%, respectively. The experiment also confirmed the model’s robustness in handling complex matrices by detecting heavy metal content in field-collected water samples from the Yangtze River. In conclusion, the GAN-Transformer model-based LIBS heavy metal anomaly detection represents a simple and reliable method for rapid on-site water quality detection.

Mechanistic understanding of the biochar-induced inhibition of growth and soil phosphorus solubilization by Bacillus megaterium

Due to the complex composition of biochar and the potential interactions between the components that jointly make up biochar, previous studies have always shown controversial results regarding impacts of biochar on soil phosphorus (P) solubilization. Using a nested experimental design, this study investigated the effects of different components of biochar, i.e. whole biochar (BC), dissolved biochar (DBC) and washed biochar (WBC) on the microbial-mediated P solubilizing process. The growth of Bacillus megaterium, acid/alkaline phosphatase activity, differential metabolites of bacteria and metabolic pathways were measured in treatments with biochar pyrolyzed at 200, 300, 400, 500 and 600 °C. Results showed that BC, DBC and WBC all negatively affected the growth and alkaline phosphatase activity of B. megaterium, and BC500/WBC500 and BC400/WBC400 had the greatest impacts. The negative effects of high-temperature biochar on cell proliferation were caused by persistent free radicals and included down-regulation of histidine metabolism by BC400 and interference in nucleotide metabolism by BC600. The impacts of low-temperature biochar on cell proliferation and alkaline phosphatase activity were highly related to the metal content. Using the independent action model, antagonistic effects were found between DBC and WBC on inhibiting B. megaterium growth, while these biochars had synergistic effects on inhibition of alkaline phosphatase activity. Overall, this study provides insights on how biochar adversely modulates microbial-mediated P solubilization.

Water exchange frequency affects the fractions of sulfur and heavy metals in mariculture sediments

Water exchange is a key step in mariculture activities. However, the impact of water exchange frequency (WEF) on the environmental behavior of sulfur and heavy metals is not well understood. In this study, the migration and transformation of sulfur and heavy metals in mariculture sediments under different WEFs were investigated. The results indicated that high WEF would be unfavorable to overlying water quality, while increased acid volatile sulfur (AVS) in the sediments (11.13 μmol/g). High WEF accelerated the release of heavy metals from bottom sediments and their enrichment in the surface layer, leading to an increase in heavy metal content in the surface sediments, with Cd showing particularly significant changes (CV, ∼20%). Moreover, the WEF also had an obvious effect on the Cd fraction (CV>10%). The increase in acid-soluble Pb inhibited the conversion of AVS to chromium (II)-reducible sulfur (CRS) in the sediments, enhancing the sediment aging process. An appropriate frequency of water exchange (once every 5 days) could increase the abundance and diversity of bacteria and help to shape specific microorganisms. Changes in heavy metals in the surface sediments caused Firmicutes to become the most affected bacterial species by the WEF. The functional flora involved in the sulfur cycle were lesser affected by the WEF (CV, ∼5%), whereas those involved in the nitrogen cycle were more affected (CV >17%). The findings provide guidance for scientific mariculture.

Ecological Assessment of Heavy Metal Content in Ukrainian Soils

Ecological Assessment of Heavy Metal Content in Ukrainian Soils

Assessment of Heavy Metal (Zinc, Copper, Lead and Cadmium) Contamination in Common Edible Shellfish Species of the Hooghly River and Sunderbans, India

The content of four heavy metals (Zinc, Copper, Lead and Cadmium) in muscles of three shell fish species - prawns -Penaeus monodon and Penaeus indicus and crabs-Scylla serrata, the most prime shellfish food resources of human in the domestic and international market were studied at four stations in the estuarine belt near Bay-of-Bengal which receives wastes of various types from industries and various anthropogenic activities. The samples were digested by acid digestion. The metal contents were quantified using an AAS (Atomic absorption spectrophotometer). The distribution of trace metals accumulated in the muscle tissues of the above mentioned species was in the order- Zn > Cu> Pb> Cd. In the present study, levels of Zinc in the shell fishes ranged from 07.44±0.65 to 128.10 ±2.96 ; Cu ranged from 5 ±0.15 to 99.14 ±1.31; Pb varied from 1.67± 0.14 to 23.99 ± 0.79 and Cd ranged from 1.29± 0.35 to 7.09 ± 0.80.The concentration of the four metals exhibited spatial variation as station 1 >station 2 > station 3 > station 4, which could be a reflection of different bioavailability of metal concentrations in the water body at different stations. The results obtained showed that the metal concentrations in most of the cases were above the threshold value recommended by WHO. Metals such as Cu, Zn, Pb, Cd, can affect various aquatic organisms as well as human being either directly or indirectly as they can enter into the food chain and may be biomagnified at higher trophic levels which is one of the top concerns for human health. Essential heavy metals such as Zinc and Copper are relatively less harmful at low concentration while non-essential metals such as Cd and Pb are highly toxic even at low concentrations.

Determination of trace analytes in nuclear grade Calcium Metal Samples by Axially Viewed Inductively Coupled Plasma – Atomic Emission Spectrometric technique

An Inductively Coupled Plasma – Atomic Emission Spectrometric (ICP-AES) method has been developed for the direct determination of 19 analytes namely, Al, B, Be, Cd, Co, Cr, Cu, Fe, Li, Mg, Mo, Mn, Ni, Pb, Pd, Si, Ta, V and W at trace concentration levels in calcium matrix. In nuclear industry, quality control and assurance of nuclear fuels and associated materials for trace metallic impurity contents form an integral part of the system for the smooth functioning of the reactor for the stipulated time span. In this context, it was required to determine trace analytes in nuclear grade Calcium which is used as a reducing agent for the production of U, Th, Pu, etc. in nuclear industry. Using axial ICP-AES, initially calibration curve for Ca with 396.847nm analytical line was obtained. Systematic studies were carried out to identify various analytical wavelengths of the analyte elements which are almost free from Ca, being the main matrix and calibration curves were obtained. For all analytes and Ca, detection limits and sensitivity values were calculated. To validate the method, three synthetic samples with analyte contents in the range of 0.1 - 5 g/mL and Ca at 1 mg/mL were analyzed, the % recovery being in the range of 80-120% with precision better than 5% RSD. The method was found to be useful for the direct determination of the elements of interest in calcium matrix and was applied for the analysis of two nuclear grade real life calcium metal samples.

Heavy Metal Content in the Soil of Baiji Refinery and Surrounding Area, Controlling its Distribution Factors

This study was conducted to analyze the presence of heavy metals within the soil inside and around Baiji Oil Refinery and their factors that control the spatial distribution of metals in soils existed as (organic matter (OM), iron-manganese, pH, clay minerals). In this study, geochemical analysis of Baiji Oil Refinery soil and nearby areas was conducted by Atomic Absorption Spectrophotometer (AAS). Twenty two samples were analysed in which the results showed heavy metal as (Cd, Pb, Cr, Ni, Fe, Mn, Zn and Cu) concentrations that most of these metals were found to be higher than their global limits in the soil, except (Fe, Mn and Zn) found to be within those limits. Controlling factors were conducted for six samples, three of highest concentrations and three of lowest one. The results reveal that the mean concentration of OM in the highest concentrations was 1.64% while the lowest concentrations was 1.59%, the mean concentration of Fe-Mn was in the highest concentrations 23380-359 ppm and in the lowest samples was 11304-114 ppm, respectively. The mean concentration for the pH in the highest concentrations was 8.5 and for the samples within the lowest concentrations was 7.9. However, the mean clay for the samples within the highest concentration were 1.04%, whereas the samples within the lowest concentration were 1.48%. The results showed that the controlling factors did not affect the soil heavy metal distribution of Baiji Oil Refinery and their nearby areas. Therefore, such results indicate the role of industrial processes (oil industries) in increasing the concentration of heavy metals in the soils in addition to the elements inherited from the parent rocks.

Magmatic and rock-leaching contributions to the metal load in hydrothermal fluids at þeistareykir, Iceland

Magmatic-hydrothermal systems are key environments to study the transfer of elements from the deep Earth to the surface and the mobilization and re-distribution of elements within the crust. These systems have been recognized as potential active analogue sites for ore deposition. The source of fluids and their metal load is split between the relative contributions from degassing of underlying magma and interactions between the hydrothermal fluid and the host rock. Here, we combine analyses of noble gases and volatile metals in fluids and rocks from the þeistareykir geothermal field (NE Iceland) to provide constraints on the relative contribution of these two sources. Helium isotope data suggest 80–85% originated from magma degassing. The 3He/4He ratio, corrected for atmospheric contamination (Rc/Ra) correlates with volatile metal abundances in surface fluids and indicates that Bi and Hg are predominantly derived from magma degassing. It is also shown that the deep geothermal reservoir fluid is dominated by magmatic input, except for Mn, Fe, Co, Cu, Ti and V, using the elemental signature of magmatic degassing and water-rock interaction. The spatial variations in Rc/Ra and surface fluid volatile metal contents among the wells suggest an impact of the local and regional structures on the fluid's pathway from depth to surface.

Fabrication, Microstructural Evolution, and Mechanical Properties of SiC/(Hf0.25Ta0.25Zr0.25Nb0.25)C/C Nanocomposites.

A dense monolithic SiC/(Hf0.25Ta0.25Zr0.25Nb0.25)C/C high-entropy ceramic nanocomposite was prepared using a polymer-derived ceramic (PDC) method combined with spark plasma sintering (SPS). The microstructural evolution and mechanical properties of the obtained nanocomposites were characterized by X-ray diffractometer (XRD), transmission electron microscope (TEM), scanning-electron microscope (SEM), and nanoindentation. The results indicate that the phase composition of SiC/(Hf0.25Ta0.25Zr0.25Nb0.25)C/C can be adjusted by modifying the metal content of the single-source precursor (SSP) through molecular design. The resulting precursor exhibits an exceptionally high ceramic yield, with mass retention of over 90% at 1100 °C, which guarantees the densification of the final SiC/(Hf0.25Ta0.25Zr0.25Nb0.25)C/C composites. The PDC route facilitates the in situ formation of a high-entropy phase within the ceramic matrix under low temperature pyrolysis conditions. Combined with SPS, a dense monolithic SiC/(Hf0.25Ta0.25Zr0.25Nb0.25)C/C nanocomposite was obtained, exhibiting an open porosity of 0.41 vol%, nano-hardness of 27.47 ± 0.46 GPa, elastic modulus of 324.00 ± 13.60 GPa, and fracture toughness of 3.59 ± 0.24 MPa·m0.5, demonstrating excellent mechanical properties.

Contamination and health risk assessment of potentially toxic elements in rice (Oryza sativa) and soil from Ashanti Region.

Anthropogenic activities release potentially toxic elements into the environment, which contaminate the food chain. The main objective of this research was to analyze the concentrations of As, Cd, Cr, Hg, and Pb in rice grains and soils, establish their correlation and transfer factors between soil and rice grains as well as evaluate their human health risk from consumption of rice cultivated in the Asante Akim area. The levels of As, Cd, Cr, Hg, and Pb in soil and rice samples were assayed using an Agilent 7700 Series inductively coupled plasma-mass spectrophotometer. The mean heavy metal content in soil was 7.5, 0.52, 0.47, 1.30, and 8.69mg/kg for As, Cd, Cr, Hg, and Pb, respectively. Mean levels of the potentially toxic elements in rice were 0.082, 0.27, 0.48, 0.028, and 0.14mg/kg for As, Cd, Cr, Hg, and Pb, respectively. Soil pollution indices showed that the soils were unpolluted with the potentially toxic elements studied. The concentrations of the potentially toxic elements in rice were below the maximum allowable concentration (MAC) recommended by the Codex Alimentary Commission except Cd which was marginally higher than the MAC. Dietary exposure to the elements to consumers was assessed by comparing the estimated daily intake (EDI) to the provisional tolerable daily intake (PTDI). The estimated daily intake values for As, Cd, Cr, Hg, and Pb were 1.45 × 10-4, 4.8 × 10-4, 8.5 × 10-4, 4.95 × 10-5, and 2.4 × 10-4, respectively. The HQ for all the potentially toxic elements was less than the permissible value of 1, suggesting that the consumption of rice from the study area constitutes no potential non-carcinogenic health risk to the population. This study is unique because the risk is evaluated from rice that is directly consumed, and this gives a clearer picture of the risk to humans. Regular monitoring studies should be conducted to ascertain the levels of heavy metals in rice cultivated in the area since heavy metals can accumulate and the concentrations could increase to toxic levels with time.

Fluid inclusion LA-ICP-MS constraint on hydrothermal evolution of proximal cassiterite-bearing quartz veins in the giant Gejiu orefield: Implications for controls on metallogenic potential of granite-related skarn system

Sn and Cu are proposed to have their mineralization potential predetermined by their contents in initial fluids of granite-related magmatic-hydrothermal systems. However, it remains ambiguous whether the giant Sn-mineralized skarn system is applicable, and whether the Sn-Cu association in some deposits is predominantly determined by their initial metal contents. The Gejiu orefield is one of the most essential Sn-polymetallic districts worldwide, with proven resources of 3.27 million tons of tin, 3.25 million tons of copper, 4.29 million tons of lead and zinc, and >20 other metals with economic significance. Sn-polymetallic mineralization at Gejiu constitutes a composite skarn ore system that includes proximal skarn and related cassiterite-sulfide, greisen, and tourmaline-vein types. The Laochang Sn-polymetallic deposit hosts several largest skarn and cassiterite-sulfide orebodies in the eastern part of Gejiu. Recent exploitation at Laochang discovered Sn-mineralized quartz veins hosted in the concealed granite, providing a valuable opportunity to characterize the proximal magmatic-hydrothermal process of the mineralizing granitic system. Here, fluid inclusion analysis is carried out on these veins to discuss the fluid evolution, cassiterite precipitation mechanism and whether metal content in early proximal magmatic fluids determines the metal association and endowment in the deposit.Based on the paragenesis of ore and gangue minerals, three hydrothermal stages are distinguished, including quartz-tourmaline stage (Stage I), cassiterite-arsenopyrite-quartz stage (Stage II) and late sulfide stage (Stage III). Fluid evolution controlling vein formation is constrained by microthermometry and LA-ICP-MS analysis of four fluid inclusions generations successively entrapped in quartz and cassiterite. The fluids involved during vein formation show an interplay between single-sourced magmatic fluids and meteoric water. The intermediate-density single phase fluid recorded at stage I quartz is derived from initial fluids directly exsolving from granitic magma. At stage II, fluid immiscibility occurred and the separated brines were entrapped in quartz and early-formed cassiterite. Along with cassiterite precipitation, brines were mixed with low-salinity and cooler meteoric water, leading to entrapment of low-salinity aqueous fluid in outer growth zones of cassiterite at stage II. The constructed fluid evolution history suggests that fluid immiscibility may have facilitated the nucleation of cassiterite crystals at the onset of deposition while mixing of magmatic fluid with meteoric water likely dominate later cassiterite mineralization.Compared with the fluid dataset of barren and mineralized granitic systems worldwide, pre-ore fluids of the studied quartz veins are enriched in Sn, confirming that high Sn content in the initial magmatic fluid can serve as indicator to distinguish mineralized system. In contrast, although Cu mineralization is economically important in the Laochang deposit, predicted Cu contents in pre-ore proximal magmatic fluids are as low as those obtained from Cu-barren system. This implies introduction of Cu into the hydrothermal system from other sources.

Environmental monitoring of heavy metal content in the hydrographic network of a large city river

ABSTRACT Samples of edaphotopes were taken from a depth of 0–15 cm for analyses in this study. It was found that the water in the areas of the Hnidavske swamp and Teremnivski ponds was the most polluted. The level of Zn (0.01 mg/dm3) exceeded the maximum permissible concentration (MPC) at site 5 (Lypnyany village, outside the city of Lutsk, the content was 0.015 mg/dm3) and Hnidavske marsh (0.019 mg/dm3). At all study sites, Cr (0.001 mg/dm3) ranging from 0.002 to 0.005 mg/dm3, Co (0.005 mg/dm3) from 0.008 to 0.01 mg/dm3, and Ni (0.01 mg/dm3) from 0.02 to 0.036 mg/dm3 were also found to exceed the MPC. However, Cd levels (0.005 mg/dm3) did not exceed the MPC and was within the normal range at all study sites (0.0016–0.003 mg/dm3).

Metals in Wildfire Suppressants.

Frequent and severe wildfires have led to increased application of fire suppression products (long-term fire retardants, water enhancers, and Class A foams) in the American West. While fire suppressing products used on wildfires must be approved by the U.S. Forest Service, portions of their formulations are trade secrets. Increased metals content in soils and surface waters at the wildland-urban interface has been observed after wildfires but has primarily been attributed to ash deposition or anthropogenic impact from nearby urban areas. In this study, metal concentrations in several fire suppression products (some approved by the U.S. Forest Service, and some marketed for consumer use) were quantified to evaluate whether these products could contribute to increased metal concentrations observed in the environment postfire. Long-term fire retardants contained concentrations of toxic metals (V, Cr, Mn, Cu, As, Cd, Sb, Ba, Tl, and Pb) 4-2,880 times greater than drinking water regulatory limits, and potentially greater than some aquatic toxicity thresholds when released into the environment. Water enhancers and Class A foams contained some metals, but at lower concentrations than fire retardants. Based on these concentrations and retardant application records, we estimate fire retardant application in the U.S. contributed approximately 380,000 kg of toxic metals to the environment between 2009 and 2021.

Exploring the performance of ammonia microfluidic fuel cell using PdNiCo aerogel

In this manuscript, PdNiCo and NiCo aerogel catalysts are prepared by an ultrafast sol-gel method combining microwave heating and freeze-drying. These new aerogels are synthesized to explore the transition metal content compared to a Pd aerogel in order to minimize the dependence on noble metals and improve their electrocatalytic properties in the presence of ammonia. The textural properties of the aerogels were characterized by the N2 adsorption/desorption isotherms. The crystal structures were measured by X-ray diffraction and X-ray photoelectron spectroscopy was used to analyze the electronic structures of the elements. The electrocatalytic activity of the aerogels towards the ammonia oxidation reaction was tested by cyclic voltammetry in a 1 M KOH + 1 M NH4OH solution. The combination of these properties in the PdNiCo and NiCo aerogels enhances the electrocatalytic activity of ammonium electro-oxidation compared to that of the Pd aerogel alone, and the multimetallic aerogels are more stable when used in a microfluidic device such as an ammonia fuel cell.

Scalable synthesis of Robust, high-loading nitrogen-infused intermetallic FePt@Pt (core@shell) catalyst for proton exchange membrane fuel cells

In this study, we propose PtFeIMN@Pt/C, featuring a Pt shell on a nitrogen-infused PtFe intermetallic core structure, and attempt large-scale synthesis of catalysts with high metal content (>50 wt%). Using the ultrasound-assisted polyol synthesis method, we synthesize core@shell structured PtFe@Pt/C catalysts with approximately 60 wt% metal content at a 10 g scale in a single step. Post-treatments, including annealing, acid treatment, and nitriding in high-pressure NH3 gas, follow to synthesize the target catalysts. Optimizing the annealing temperature reveals a trade-off relationship affecting catalyst activity and durability. The PtFeIMN@Pt/C_600 °C, synthesized under optimized conditions, exhibits superior electrochemical performance and durability compared to commercial Pt/C catalysts. The accelerated stability test (AST) further shows significantly enhanced durability when nitrogen is included in the core. In the single cell tests, PtFeIMN@Pt/C_600 °C demonstrates approximately four times higher mass activity than commercial Pt/C catalysts and a 29.9 mV voltage drop at 0.8 A cm−2 after AST, meeting the U.S. Department of Energy's targets.

Content of Selected Harmful Metals (Zn, Pb, Cd) and Polycyclic Aromatic Hydrocarbons (PAHs) in Honeys from Apiaries Located in Urbanized Areas.

The chemical composition of honey, and therefore its quality and properties, is influenced by many factors, including its botanical origin and the harvesting conditions-the location of the apiary, access to melliferous plants, the proximity of industrial infrastructure and communication routes, etc. This quality may be reduced by undesirable, toxic compounds that penetrate honey from a contaminated environment, such as heavy metals and residues from other environmental pollutants. Therefore, the aim of our research was to assess the quality of honeys from urbanized areas-in particular, to assess contamination with heavy metals and persistent organic pollutants (PAHs). In total, 35 samples from six different apiaries located in urbanized areas were examined. The content of heavy metals (Cd, Pb, Zn) was determined by atomic absorption spectrophotometry (AAS), and the content of total PAHs as the sum of the concentrations of the compounds benzo(a)anthracene, chrysene, benzo(b)fluoranthene and benzo(a)pyrene was determined by high-performance liquid chromatography with fluorescence detection (HPLC-FLD). The average zinc content ranged from about 2 to 4.5 mg/kg, the average lead content ranged from 3.5 µg/kg to 388 µg/kg and the average cadmium content ranged from 0.5 to 14 µg/kg. It was found that all honeys contained certain amounts of harmful metals, and only lead exceeded the permissible limits. None of the samples tested contained sum content of PAHs exceeding 10 µg/kg of honey. Contrary to our expectations, the results obtained indicate that honeys from urbanized areas do not contain these harmful substances. In general, the presence of harmful metals does not, however, reduce honey's quality or its health value.