Multielemental Composition Research Articles

Synthesis and electrochemical performance of novel high-entropy spinel oxide (FeCoMgCrLi)3O4

High-entropy oxides (HEOs) are attractive options for anode materials in lithium-ion batteries (LIBs) because of their impressive specific capacity and structural stability. The multi-element composition of HEOs endows them with diverse physicochemical properties. However, the role of different elements in the energy storage mechanism remains unclear, and the limited number of successfully synthesized high-entropy oxide systems currently hinders further development. Therefore, developing HEOs with different compositions and studying their electrochemical properties is of great significance. Using the glycine-nitrate solution combustion synthesis (SCS) method, we produced two new High Entropy Oxides (HEOs), namely (FeCoMgCr)3O4 and (FeCoMgCrLi)3O4, and assessed their electrochemical performance as LIBs anode materials. The studies indicate that the inclusion of lithium significantly enhances the lithium storing capabilities of the material system. Specifically, after undergoing two hundred cycles at a current density of 200 mA/g, (FeCoMgCrLi)3O4 exhibited a specific capacity of 658 mAh/g, which was considerably greater than the specific capacity of (FeCoMgCr)3O4, which was 306.9 mAh/g. This work enriches the spinel-type high-entropy oxide systems and proposes a new design strategy for HEOs as LIBs anode materials.

Unveiling the Behavior of an Endangered Facultative Cuprophyte Coincya Species in an Abandoned Copper Mine (Southeast Portugal).

Plant-soil interactions of endangered species with a high-priority conservation status are important to define in situ and ex situ conservation and restoration projects. The threatened endemic Coincya transtagana, thriving in the southwest of the Iberian Peninsula, can grow in metalliferous soils. The main goal of this study was to investigate the behavior of this species in soils rich in potentially toxic elements in the abandoned Aparis Cu mine. Soil samples were characterized for physicochemical properties and multielemental composition, as well as biological activity, through an analysis of enzymatic activities. Plant biomass was assessed, and multielemental analysis of the plants was also performed. The mine soils had slightly basic pH values and were non-saline and poor in mineral N-NH4, with medium-to-high organic matter concentration and medium cation-exchange capacity. In these soils, dehydrogenase had the highest activity, whereas protease had the lowest activity. The total concentrations of Cu (1.3-5.9 g/kg) and As (37.9-118 mg/kg) in soils were very high, and the available fraction of Cu in the soil also had high concentration values (49-491 mg/kg). Moreover, this study shows for the first time that C. transtagana had high uptake and translocation capacities from roots to shoots for Cu, Ni, and Cr. Although Cu in the plants' aerial parts (40-286 mg/kg) was considered excessive/toxic, no signs of plant toxicity disorders or P uptake reduction were detected. This preliminary study revealed that C. transtagana is Cu-tolerant, and it could be used for phytoremediation of soils contaminated with potentially toxic elements, while also contributing to its conservation.

Multi-Elemental Analysis and Geographical Discrimination of Greek "Gigantes Elefantes" Beans Utilizing Inductively Coupled Plasma Mass Spectrometry and Machine Learning Models.

Greek giant beans, also known as "Gigantes Elefantes" (elephant beans, Phaseolus vulgaris L.,) are a traditional and highly cherished culinary delight in Greek cuisine, contributing significantly to the economic prosperity of local producers. However, the issue of food fraud associated with these products poses substantial risks to both consumer safety and economic stability. In the present study, multi-elemental analysis combined with decision tree learning algorithms were investigated for their potential to determine the multi-elemental profile and discriminate the origin of beans collected from the two geographical areas. Ensuring the authenticity of agricultural products is increasingly crucial in the global food industry, particularly in the fight against food fraud, which poses significant risks to consumer safety and economic stability. To ascertain this, an extensive multi-elemental analysis (Ag, Al, As, B, Ba, Be, Ca, Cd, Co, Cr, Cs, Cu, Fe, Ga, Ge, K, Li, Mg, Mn, Mo, Na, Nb, Ni, P, Pb, Rb, Re, Se, Sr, Ta, Ti, Tl, U, V, W, Zn, and Zr) was performed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Bean samples originating from Kastoria and Prespes (products with Protected Geographical Indication (PGI) status) were studied, focusing on the determination of elemental profiles or fingerprints, which are directly related to the geographical origin of the growing area. In this study, we employed a decision tree algorithm to classify Greek "Gigantes Elefantes" beans based on their multi-elemental composition, achieving high performance metrics, including an accuracy of 92.86%, sensitivity of 87.50%, and specificity of 96.88%. These results demonstrate the model's effectiveness in accurately distinguishing beans from different geographical regions based on their elemental profiles. The trained model accomplished the discrimination of Greek "Gigantes Elefantes" beans from Kastoria and Prespes, with remarkable accuracy, based on their multi-elemental composition.

Design of CO2-Resistant High-Entropy Perovskites Based on Ba0.5Sr0.5Co0.8Fe0.2O3-δ Materials.

High-entropy perovskite materials (HEPMs), characterized by their multi-element composition and highly disordered structure, can incorporate multiple rare earth elements at the A-site, producing perovskites with enhanced CO2 resistance, making them stay high performance and structurally stable in the CO2 atmosphere. However, this modification may result in reduced oxygen permeability. In this study, we investigated La0.2Pr0.2Nd0.2Ba0.2Sr0.2Co0.8Fe0.2O3-δ (L0.2M1.8) high-entropy perovskite materials, focusing on enhancing their oxygen permeability in both air and CO2 atmospheres through strategic design modifications at the B-sites and A/B-sites. We prepared Ni-substituted La0.2Pr0.2Nd0.2Ba0.2Sr0.2Co0.7Fe0.2Ni0.1O3-δ (L0.2M1.7N0.1) HEPMs by introducing Ni elements at the B-site, and further innovatively introduced A-site defects to prepare La0.2Pr0.2Nd0.2Ba0.2Sr0.2Co0.7Fe0.2Ni0.1O3-δ (L0.1M1.7N0.1) materials. In a pure CO2 atmosphere, the oxygen permeation flux of the L0.1M1.7N0.1 membrane can reach 0.29 mL·cm-2·min-1. Notably, the L0.1M1.7N0.1 membrane maintained a good perovskite structure after stability tests extending up to 120 h under 20% CO2/80% He atmosphere. These findings suggest that A-site-defect high-entropy perovskites hold great promise for applications in CO2 capture, storage, and utilization.

Elevated atmospheric CO2 alters the multi-element stoichiometry of pollen-bearing oak flowers, with possible negative effects on bees

Increasing atmospheric CO2 levels change the elemental composition in plants, altering their nutritional quality and affecting consumers and ecosystems. Ecological stoichiometry provides a framework for investigating how CO2-driven nutrient dilution in pollen affects bees by linking changes in pollen chemical element proportions to the nutritional needs of bees. We investigated the consequences of five years of Free Air CO2 Enrichment (FACE) in a mature oak-dominated temperate forest on the elemental composition of English oak (Quercus robur) pollen. We measured the concentrations and proportions of 12 elements (C, N, P, S, K, Na, Ca, Mg, Cu, Zn, Fe, and Mn) in Q. robur pollen-bearing flowers collected from the Birmingham Institute for Forest Research (BIFoR) FACE facility. An elevated CO2 (eCO2) level of 150 ppm above ambient significantly reduced the S, K, and Fe levels and altered the multi-element ratio, with different elements behaving differently. This shift in pollen multi-element composition may have subsequent cascading effects on higher trophic levels. To assess the impact on bees, we calculated the stoichiometric mismatch (a measure of the discrepancy between consumer needs and food quality) for two bee species, Osmia bicornis (red mason bee) and Apis mellifera (honey bee), that consume oak pollen in nature. We observed stoichiometric mismatches for P and S, in pollen under eCO2, which could negatively affect bees. We highlight the need for a comprehensive understanding of the changes in pollen multi-element stoichiometry under eCO2, which leads to nutrient limitations under climate change with consequences for bees.

Effects of multi-element composition regulation on the structure and electrochemistry of P2-type layered cathode materials

P2-type Mn-based oxides are promising cathode materials for sodium-ion batteries due to their low cost and high capacity virtue. However, the irreversible phase transition and unstable anion redox at high operating voltages (∼4.2 V) will cause structural distortions, leading to slow sodium-ion diffusion kinetics and severe capacity degradation. Herein, a multi-elemental composition regulation strategy is proposed to enhance the structural stability of P2-type cathode by optimizing the structure and modulating the irreversible oxygen redox during high-voltage cycling. A series of multi-element cathodes Na0.67(Fe1/4Co1/4Ni1/4Ti1/4)1-xMnxO2 (x = 0.4,0.5,0.6,0.7,0.8,0.9) are designed and the effects of component modulation on their structure and electrochemical behavior are systematically investigated. Especially, the optimized Na0.67Fe0.05Co0.05Ni0.05Ti0.05Mn0.8O2 cathode maintains P2 phase during the initial charging/discharging between 1.5 V and 4.5 V, inhibits irreversible oxygen redox, and exhibits small lattice expansion. Impressively, the above optimized cathode exhibits superior cycling stability with capacity retention of nearly 90 % and reversible capacity of 130.1 mAhg−1 after 100 cycles at 1C rate. Furthermore, the optimized cathode also displays an excellent rate capability (capacity of 108.2 mAh g−1 at 5 C rate) due to the enhanced Na+ diffusion kinetics. This work provides new insight into developing high-stable Mn-based oxide cathodes operating at high voltage for sodium-ion batteries.

Validation of a PGNAA sensor model for bulk material sorting

Global mineral demand is forecast to increase significantly to achieve the transition to renewable energy. Greater volumes of ore of lower grade will have to be mined to meet demand. Techniques to process large volumes of low-grade ore efficiently are being investigated to reduce the cost and impact of mining. One technique is to use sensor information to sort mined material, allowing waste to be discarded early in mineral processing. Prompt gamma neutron activation analysis (PGNAA) is a sensing technique that can provide information on the multi-elemental composition of a bulk sample which can be used for bulk material sorting. This paper presents the development of a Monte Carlo simulation model of a PGNAA sensor for bulk sorting using the Geant4 toolkit. The GEOSCAN sensor (Scantech Australia) was used as a case-study to demonstrate the application of the model. The sensor responses for a range of pure mineral samples (Fe2O3, SiO2, S, Na2CO3 and MnO2) were measured to validate the developed model. The sensitivity of the simulation results to the hadronic and electromagnetic physics models used was tested. It was determined that the PGNAA sensor model can reproduce measurements obtained from the GEOSCAN sensor. In particular, the model can provide a good reproduction of the overall spectral shape and the locations of distinct characteristic peaks. The differences between simulated and experimental results are within 30% on average. It was found that the Geant4 HP neutron model best reproduces the activation peaks observed in experimental measurements. Additionally, the PGNAA spectrum was found to be insensitive to the choice of electromagnetic model for the photon interactions. The validated sensor model provides a useful tool for investigating PGNAA sensor applications including a bulk sorting strategy for new materials, sensor calibration, improvements in signal analysis and optimised sensor design.

Evaluating Source Complexity in Blended Milk Cheese: Integrated Strontium Isotope and Multi-Elemental Approach to PDO Graviera Naxos.

Graviera Naxos, a renowned cheese with Protected Designation of Origin status, is crafted from a blend of cow, goat, and sheep milk. This study focused on assessing the Sr isotopic and multi-elemental composition of both the processed cheese and its ingredients, as well as the environmental context of Naxos Island, including samples of milk, water, soil, and feed. The objective was to delineate the geochemical signature of Graviera Naxos cheese and to explore the utility of Sr isotopes as indicators of geographic origin. The 87Sr/86Sr values for Graviera Naxos samples ranged from 0.70891 to 0.70952, indicating a relatively narrow range. However, the Sr isotopic signature of milk, heavily influenced by the feed, which originates from geologically distinct areas, does not always accurately reflect the local breeding environment. Multi-elemental analysis revealed variations in milk composition based on type and season; yet, no notable differences were found between raw and pasteurized milk. A mixing model evaluating the contributions of milk, sea salt, and rennet to the cheese's Sr isotopic signature suggested a significant average contribution of 73.1% from sea salt. This study highlights the complexities of linking dairy products with their geographical origins and emphasizes the need for sophisticated geochemical authentication methods.

Contemporary Stage Lighting Art: The Multi-Element Composition of Post-Drama Stage Space

Contemporary Stage Lighting Art: The Multi-Element Composition of Post-Drama Stage Space

Effect of quenching-super intercritical quenching-tempering process on the evolution of microstructure and the yield ratio of Ni–Cr–Mo steel

In the present study, X-ray diffraction, electron probe microanalysis, and transmission electron microscopy, among other advanced characterization methods, were used to analyze the microstructure and mechanical properties of the 9Ni steel treated at different heat treatment conditions. The goal was to reveal the dual-optimal strengthening mechanism of “low yield ratio and ultra-cryogenic toughness” of the investigated steel. The experimental results indicated that the 9Ni steel, designed with a ''Ni–Cr–Mo'' multi-elemental composition, balanced its hardenability and corrosion resistance. After the Q-Q' (710 °C) -T process, the diffusion of Cr and Mo atoms in the steel accelerated, while the Fe displacement diffusion formed a more stable FeNi face-centered cubic structure with a lattice energy of −76.98 eV. At this stage, the microstructure of the investigated steel primarily consisted of tempered sorbite (with an average effective grain size of 13.1 μm), tempered martensite lath clusters, reversed austenite, and precipitated Cr23C6 and Mo2C particles. This composition resulted in a low yield ratio. The concentration of Ni near the lath clusters promoted the formation of the reversed austenite with a volume fraction of 10.2%, ensuring the cryogenic toughness of the investigated steel.

A catalyst family of high-entropy alloy atomic layers with square atomic arrangements comprising iron- and platinum-group metals.

We report a catalyst family of high-entropy alloy (HEA) atomic layers having three elements from iron-group metals (IGMs) and two elements from platinum-group metals (PGMs). Ten distinct quinary compositions of IGM-PGM-HEA with precisely controlled square atomic arrangements are used to explore their impact on hydrogen evolution reaction (HER) and hydrogen oxidation reaction (HOR). The PtRuFeCoNi atomic layers perform enhanced catalytic activity and durability toward HER and HOR when benchmarked against the other IGM-PGM-HEA and commercial Pt/C catalysts. Operando synchrotron x-ray absorption spectroscopy and density functional theory simulations confirm the cocktail effect arising from the multielement composition. This effect optimizes hydrogen-adsorption free energy and contributes to the remarkable catalytic activity observed in PtRuFeCoNi. In situ electron microscopy captures the phase transformation of metastable PtRuFeCoNi during the annealing process. They transform from random atomic mixing (25°C), to ordered L10 (300°C) and L12 (400°C) intermetallic, and finally phase-separated states (500°C).

Correlation Study of Multi-Element Composition and Oxidative Stability of Ziziphus Lotus Lam. Seed Oils Collected from Different Regions of Tunisia

Correlation Study of Multi-Element Composition and Oxidative Stability of Ziziphus Lotus Lam. Seed Oils Collected from Different Regions of Tunisia

Suitability of XRF for Routine Analysis of Multi-Elemental Composition: A Multi-Standard Verification.

This study investigated the suitability of X-ray fluorescence (XRF) analysis for routine multi-elemental composition analysis, checking its analytical capabilities by measuring a wide array of certified reference materials of soil and plant origin. A portable XRF analyzer was used to evaluate 32 soil and 12 plant standard materials, using both the Soil and Geochem mode, with sequential beams, allowing the detection of a wide range of elements. Recovery rates were calculated by comparing XRF measurements with certified values, and their correlations were verified through the Spearman coefficient. The results demonstrated the reliability of XRF measurements for soil samples, with a large number of elements showing a good or very good recovery and strong correlations with certified values. For plant samples, XRF largely overestimated the certified values, but the strong statistically significant correlations for almost all tested elements allowed us to correct this systematic bias, using the reported median value for dividing the value obtained via XRF. The Geochem mode emerged as more reliable for a larger number of elements. It was concluded that XRF may be a suitable alternative to ICP-MS in routine multi-elemental composition analysis.

Past progress in environmental nanoanalysis and a future trajectory for atomic mass-spectrometry methods

The development of engineered nanotechnology has necessitated a commensurate maturation of nanoanalysis capabilities. Building off a legacy established by electron microscopy and light-scattering, environmental nanoanalysis has now benefited from ongoing advancements in instrumentation and data analysis, which enable a deeper understanding of nanomaterial properties, behavior, and impacts. Where once environmental nanoparticles and colloids were grouped into broad ‘dissolved or particulate’ classes that are dependent on a filter size cut-off, now size distributions of submicron particles can be separated and characterized providing a more comprehensive examination of the nanoscale. Inductively coupled plasma-quadrupole mass spectrometry (ICP-QMS), directly coupled to field flow fractionation (FFF-ICP-QMS) or operated in single particle mode (spICP-MS) have spearheaded a revolution in nanoanalysis, enabling research into nanomaterial behavior in environmental and biological systems at expected release concentrations. However, the complexity of the nanoparticle population drives a need to characterize and quantify the multi-element composition of nanoparticles, which has begun to be realized through the application of time-of-flight MS (spICP-TOFMS). Despite its relative infancy, this technique has begun to make significant strides in more fully characterizing particulate systems and expanding our understanding of nanoparticle behavior. Though there is still more work to be done with regards to improving instrumentation and data processing, it is possible we are on the cusp of a new nanoanalysis revolution, capable of broadening our understanding of the size regime between dissolved and bulk particulate compartments of the environment.

Discrimination of deposit types using magnetite geochemistry based on machine learning

The application of trace elements in magnetite for deposit genesis research is significant, highlighting its potential as a valuable mineral exploration tool. However, traditional low-dimensional analysis methods are not effective in revealing the genetic types of deposits using magnetite trace elements, as they fail to fully utilize the rich high-dimensional information provided by magnetite trace element analysis. To address this limitation, we implemented a supervised machine learning method, eXtreme Gradient Boosting (XGBoost), to correlate the multi-element composition of magnetite with deposit types. Our study encompassed 3,865 magnetite trace element datasets from six distinct deposit types (BIF, IOA, IOCG, magmatic, porphyry, and skarn deposits). It demonstrates the XGBoost classifier’s efficiency and accuracy in classifying high-dimensional magnetite trace element data based on deposit types, achieving an impressive overall accuracy of 96% with an F1 score of 95%. Interpretation of the model using the SHAPley Additive exPlanations (SHAP) tool shows that Ni, Ga, Sc, and V are the most indicative elements for classifying deposit types using magnetite trace element chemistry. Additionally, a visualization method based on XGBoost and t-SNE was proposed. Finally, Xgboost and SHAP were applied in Jinchuan magmatic sulfide Ni-Cu-PGE deposit. Based on optical characteristics and machine learning, Jinchuan magnetite can be classified into three types. Compared with type I magmatic magnetite and type III hydrothermal magnetite, type II magnetite’s paragenetic with sulfides, calcite and apatite and high Ni content may indicate that it’s origin of interaction between sulfide melts–volatile fluids. These results indicate that deep volatile fluid plays a key role for the formation of Jinchuan Cu-Ni sulfide deposit.

Elemental, phytochemical analysis and determination of antibacterial, antioxidant, and cytotoxic activities of leaves extracts of eleven Eucalyptus species

The genus Eucalyptus has attracted considerable attention from natural product specialists exploring new phytochemicals for therapeutic purposes due to their possible biological activities. This was stimulated by current findings that Eucalyptus species interrupt the propagation of the recently tormenting COVID-19 virus. Eleven Eucalyptus leaf extracts were subjected to in vitro antimicrobial studies against four bacterial strains: Staphylococcus aureus, Streptococcus pyogenes, Staphylococcus lugdunensis and Staphylococcus epidermis using the broth serial dilution assay. The potential of the extracts to inhibit free radicals 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) was investigated, indicating antioxidant properties. Furthermore, the cytotoxicity test was performed against the human embryonic kidney (HEK293-T) cell line using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Phytochemicals were identified and characterized using Fourier transform infrared spectroscopy (FTIR) and one-dimensional gas chromatography mass spectrometry (GC–MS). Moreover, the microwave plasma atomic emission spectroscopy (MP-AES) coupled with inductively coupled plasma optical emission spectroscopy (ICP-OES) was used to evaluate the multielemental composition of the extracts. The MP-AES and ICP-OES techniques in this work displayed accuracy and sensitivity for multielement determination by identifying P, B, Ca, Zn, Cu, Mg, Fe, Mn, Na, and K as major constituents in Eucalyptus extracts. The extracts generally had strong antioxidant and antibacterial properties, with E. viminalis (IC50 = 2.91 ± 0.22 µg/mL) demonstrating strong action against the ABTS radical. E. nitens and E. dunnii also showed highest activity against DPPH and ABTS, with IC50 values < 10 µg/mL. Additionally, with IC50 values greater than 20 µg/mL, the extracts demonstrated relative non-toxicity against HEK293-T cells. The existence of the bioactive chemicals found by FTIR and GC–MS may be the cause of the observed biological activity. Because Eucalyptus plant species have the highest antioxidant activity and the most inhibitory action against the majority of Streptococcus bacterial strains, they can be employed as a therapeutic treatment to treat infections caused by Streptococcus.

Vanadium nitride induced method to construct cobalt sulfides homologous heterojunction toward ultrafast and high-capacity sodium-ion storage

In recent years, heterojunction has attracted widespread attention as an anode for sodium-ion batteries since they can effectively optimize the materials’ rate performance and cycling stability. However, the advantage is choked by multi-element composition and stepwise synthesis process. Herein, cobalt sulfide (Co9S8/CoS) homologous heterojunction deposited at vanadium nitride/carbon nanofibers is synthesized as an excellent anode for high-performance sodium-ion batteries in one step by employing the “3d-orbital electron complementary effect” combined with high-temperature heat-treatment technology. The Co9S8/CoS homologous heterojunction successfully overcomes the inherent drawback of Co9S8 and possesses an ultrafast charging/discharging process, outstanding reversible specific capacity, and remarkable rate capability. A systematic study reveals that vanadium nitride is a key trigger for forming Co9S8/CoS heterojunction. When used as anode materials for sodium-ion batteries, it reaches a high specific capacity of 353.0 mAh/g at a current density of 10 A/g (615.8 mAh/g at a current density of 0.05 A/g) due to the presence of heterointerface. Theoretical calculations show that the construction of the heterostructure enhances the sodium-ion storage capacity and storage kinetics compared with pristine Co9S8. This discovery opens an interesting strategy for constructing homogeneous heterojunctions and broadens the horizons for designing energy storage and conversion materials.

Laser-thermal reduction synthesis of high-entropy alloys towards high-performance pH universal hydrogen evolution reaction

Owing to their multi-elemental compositions and unique high-entropy mixing states, high-entropy alloy (HEA) nanoparticles (NPs) displaying tunable activities and enhanced stabilities thus have become a rapidly growing area of research in recent years. However, the integration of multiple elements into HEA NPs at the nanoscale remains a formidable challenge, especially when it comes to the precise control of particle size, elemental composition and content. Herein, a simple and universal high-energy laser assisted reduction approach is presented, which achieves the preparation of HEA NPs with a wide range of multi-component, controllable particle sizes and constitution on different substrates within seconds. Laser on carbon nanofibers induced momentary high-temperature annealing (>2000 ​K and ramping/cooling rates > 105 ​K ​s−1) to successfully decorate HEA NPs up to twenty elements with excellent compatibility for large-scale synthesis (20.0 ​× ​20.0 ​cm2 of carbon cloth). The IrPdPtRhRu exhibit robust electrocatalytic hydrogen evolution reaction (HER) activities and low overpotentials of 16, 28, and 12 ​mV at a current density of 10 ​mA ​cm−2 in alkaline (1.0 ​M KOH), alkaline simulated seawater (1.0 ​M KOH ​+ ​0.5 ​M NaCl), and acidic (0.5 ​M ​H2SO4) electrolytes, respectively, and excellent stability (7 days and >2000 cycles) at the alkaline HER.

Multi-elemental composition of botanical preparations and probabilistic evaluation of toxic metals and metalloids intake upon dietary exposure

The aim of this study was to evaluate the inorganic elemental composition (49 elements) of 29 botanical preparations obtained from fruits, leaves, peels, seeds, roots, fungi, and spirulina by using inductively coupled-mass spectrometry and a mercury analyzer. Simultaneously, the risk associated with the chronic dietary exposure to 12 toxic metals and metalloids among the European population was evaluated by using a probabilistic approach based on Monte Carlo simulations. The analysis revealed worrying intake levels of Al, As, and Ni, primarily stemming from the consumption of spirulina-, peel-, and leaf-based botanicals by younger age groups. The intake of As from all analyzed botanicals posed a significant risk for infants, yielding margins of exposure (MOEs) below 1, while those deriving from peel-based botanicals raised concerns across all age groups (MOEs = 0.04–2.3). The consumption of peel-based botanicals contributed substantially (13–130%) also to the tolerable daily intake of Ni for infants, toddlers, and children, while that of spirulina-based botanicals raised concerns related to Al intake also among adults, contributing to 11–176% of the tolerable weekly intake of this element. The findings achieved underscore the importance of implementing a monitoring framework to address chemical contamination of botanicals, thus ensuring their safety for regular consumers.

A new approach for sample preparation to determine the multi-element composition of cobalt-rich crust samples by wavelength dispersive X-ray fluorescence spectrometry

A new approach for sample preparation to determine the multi-element composition of cobalt-rich crust samples by wavelength dispersive X-ray fluorescence spectrometry