Recently, interest in aluminium ion batteries with aluminium anodes, graphite cathodes and ionic liquid electrolytes has increased; however, much remains to be done to increase the cathode capacity ...and to understand details of the anion-graphite intercalation mechanism. Here, an aluminium ion battery cell made using pristine natural graphite flakes achieves a specific capacity of ∼110 mAh g
with Coulombic efficiency ∼98%, at a current density of 99 mA g
(0.9 C) with clear discharge voltage plateaus (2.25-2.0 V and 1.9-1.5 V). The cell has a capacity of 60 mAh g
at 6 C, over 6,000 cycles with Coulombic efficiency ∼ 99%. Raman spectroscopy shows two different intercalation processes involving chloroaluminate anions at the two discharging plateaus, while C-Cl bonding on the surface, or edges of natural graphite, is found using X-ray absorption spectroscopy. Finally, theoretical calculations are employed to investigate the intercalation behaviour of choloraluminate anions in the graphite electrode.
Go for gold: As‐prepared insulin–Au nanoclusters (NCs) show intense red fluorescence, excellent biocompatibility, and preservation of natural insulin bioactivity in lowering the blood‐glucose level. ...Their versatility in applications is demonstrated by fluorescence imaging, X‐ray computed tomography, and insulin–inhibitor interactions (see picture; IDE=insulin‐degrading enzyme).
Abstract
Machine learning and artificial intelligence approaches have revolutionized multiple disciplines, including toxicology. This review summarizes representative recent applications of machine ...learning and artificial intelligence approaches in different areas of toxicology, including physiologically based pharmacokinetic (PBPK) modeling, quantitative structure-activity relationship modeling for toxicity prediction, adverse outcome pathway analysis, high-throughput screening, toxicogenomics, big data, and toxicological databases. By leveraging machine learning and artificial intelligence approaches, now it is possible to develop PBPK models for hundreds of chemicals efficiently, to create in silico models to predict toxicity for a large number of chemicals with similar accuracies compared with in vivo animal experiments, and to analyze a large amount of different types of data (toxicogenomics, high-content image data, etc.) to generate new insights into toxicity mechanisms rapidly, which was impossible by manual approaches in the past. To continue advancing the field of toxicological sciences, several challenges should be considered: (1) not all machine learning models are equally useful for a particular type of toxicology data, and thus it is important to test different methods to determine the optimal approach; (2) current toxicity prediction is mainly on bioactivity classification (yes/no), so additional studies are needed to predict the intensity of effect or dose-response relationship; (3) as more data become available, it is crucial to perform rigorous data quality check and develop infrastructure to store, share, analyze, evaluate, and manage big data; and (4) it is important to convert machine learning models to user-friendly interfaces to facilitate their applications by both computational and bench scientists.
A challenge in the risk assessment of perfluorooctane sulfonate (PFOS) is the large interspecies differences in its toxicokinetics that results in substantial uncertainty in the dosimetry and ...toxicity extrapolation from animals to humans. To address this challenge, the objective of this study was to develop an open-source physiologically based pharmacokinetic (PBPK) model accounting for species-specific toxicokinetic parameters of PFOS. Considering available knowledge about the toxicokinetic properties of PFOS, a PBPK model for PFOS in mice, rats, monkeys, and humans after intravenous and oral administrations was created. Available species-specific toxicokinetic data were used for model calibration and optimization, and independent datasets were used for model evaluation. Bayesian statistical analysis using Markov chain Monte Carlo (MCMC) simulation was performed to optimize the model and to characterize the uncertainty and interspecies variability of chemical-specific parameters. The model predictions well correlated with the majority of datasets for all four species, and the model was validated with independent data in rats, monkeys, and humans. The model was applied to predict human equivalent doses (HEDs) based on reported points of departure in selected critical toxicity studies in rats and monkeys following U.S. EPA's guidelines. The lower bounds of the model-derived HEDs were overall lower than the HEDs estimated by U.S. EPA (e.g., 0.2 vs. 1.3 μg/kg/day based on the rat plasma data). This integrated and comparative analysis provides an important step towards improving interspecies extrapolation and quantitative risk assessment of PFOS, and this open-source model provides a foundation for developing models for other perfluoroalkyl substances.
•An open-source PBPK model for PFOS in mice, rats, monkeys and humans was developed.•A Bayesian approach was used to characterize parameter uncertainty between species.•Human equivalent doses (HEDs) and reference doses (RfDs) were calculated.•Calculated RfDs were close to EFSA's guidance value, but lower than EPA's RfDs.
•A probabilistic human health risk assessment framework for PFOS was established.•A Bayesian dose-response model was created to analyze in vitro, in vivo toxicity, and human data.•A PBPK model was ...used to calculate human equivalent doses and reference doses (RfDs).•Calculated RfD was in the range of values from regulatory agencies from US, EU, and Germany.
Environmental exposure to perfluorooctane sulfonate (PFOS) is associated with various adverse outcomes in humans. However, risk assessment for PFOS with the traditional risk estimation method is faced with multiple challenges because there are high variabilities and uncertainties in its toxicokinetics and toxicity between species and among different types of studies.
This study aimed to develop a robust probabilistic risk assessment framework accounting for interspecies and inter-experiment variabilities and uncertainties to derive the human equivalent dose (HED) and reference dose for PFOS.
A Bayesian dose-response model was developed to analyze selected 34 critical studies, including human epidemiological, animal in vivo, and ToxCast in vitro toxicity datasets. The dose-response results were incorporated into a multi-species physiologically based pharmacokinetic (PBPK) model to reduce the toxicokinetic/toxicodynamic variabilities. In addition, a population-based probabilistic risk assessment of PFOS was performed for Asian, Australian, European, and North American populations, respectively, based on reported environmental exposure levels.
The 5th percentile of HEDs derived from selected studies was estimated to be 21.5 (95% CI: 10.6–36.3) ng/kg/day. After exposure to environmental levels of PFOS, around 50% of the population in all studied populations would likely have >20% of increase in serum cholesterol, but the effects on other endpoints were estimated to be minimal (<10% changes). There was a small population (~10% of the population) that was highly sensitive to endocrine disruption and cellular response by environmental PFOS exposure.
Our results provide insights into a complete risk characterization of PFOS and may help regulatory agencies in the reevaluation of PFOS risk. Our new probabilistic approach can conduct dose-response analysis of different types of toxicity studies simultaneously and this method could be used to improve risk assessment for other perfluoroalkyl substances (PFAS).
Hydrogen evolution reaction (HER) from water through electrocatalysis using cost-effective materials to replace precious Pt catalysts holds great promise for clean energy technologies. In this work ...we developed a highly active and stable catalyst containing Co doped earth abundant iron pyrite FeS2 nanosheets hybridized with carbon nanotubes (Fe1–x Co x S2/CNT hybrid catalysts) for HER in acidic solutions. The pyrite phase of Fe1–x Co x S2/CNT was characterized by powder X-ray diffraction and absorption spectroscopy. Electrochemical measurements showed a low overpotential of ∼0.12 V at 20 mA/cm2, small Tafel slope of ∼46 mV/decade, and long-term durability over 40 h of HER operation using bulk quantities of Fe0.9Co0.1S2/CNT hybrid catalysts at high loadings (∼7 mg/cm2). Density functional theory calculation revealed that the origin of high catalytic activity stemmed from a large reduction of the kinetic energy barrier of H atom adsorption on FeS2 surface upon Co doping in the iron pyrite structure. It is also found that the high HER catalytic activity of Fe0.9Co0.1S2 hinges on the hybridization with CNTs to impart strong heteroatomic interactions between CNT and Fe0.9Co0.1S2. This work produces the most active HER catalyst based on iron pyrite, suggesting a scalable, low cost, and highly efficient catalyst for hydrogen generation.
There is a great concern on potential adverse effects of exposure to perfluorooctane sulfonate (PFOS) in sensitive subpopulations, such as pregnant women, fetuses, and neonates, due to its reported ...transplacental and lactational transfer and reproductive and developmental toxicities in animals and humans.
This study aimed to develop a gestational and lactational physiologically based pharmacokinetic (PBPK) model in rats and humans for PFOS to aid risk assessment in sensitive human subpopulations.
Based upon existing PBPK models for PFOS, the present model addressed a data gap of including a physiologically based description of basolateral and apical membrane transporter-mediated renal reabsorption and excretion in kidneys during gestation and lactation. The model was calibrated with published rat toxicokinetic and human biomonitoring data and was independently evaluated with separate data. Monte Carlo simulation was used to address the interindividual variability.
Model simulations were generally within 2-fold of observed PFOS concentrations in maternal/fetal/neonatal plasma and liver in rats and humans. Estimated fifth percentile human equivalent doses (HEDs) based on selected critical toxicity studies in rats following U.S. Environmental Protection Agency (EPA) guidelines ranged from 0.08 to
. These values are lower than the HEDs estimated in U.S. EPA guidance (
) using an empirical toxicokinetic model in adults.
The results support the importance of renal reabsorption/excretion during pregnancy and lactation in PFOS dosimetry and suggest that the derivation of health-based toxicity values based on developmental toxicity studies should consider gestational/lactational dosimetry estimated from a life stage-appropriate PBPK model. This study provides a quantitative tool to aid risk reevaluation of PFOS, especially in sensitive human subpopulations, and it provides a basis for extrapolating to other per- and polyfluoroalkyl substances (PFAS). All model codes and detailed tutorials are provided in the Supplemental Materials to allow readers to reproduce our results and to use this model. https://doi.org/10.1289/EHP7671.
Celotno besedilo
Dostopno za:
CEKLJ, DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
Organic–inorganic hybrid two-dimensional (2D) perovskites have recently attracted great attention in optical and optoelectronic applications due to their inherent natural quantum-well structure. We ...report the growth of high-quality millimeter-sized single crystals belonging to homologous two-dimensional (2D) hybrid organic–inorganic Ruddelsden–Popper perovskites (RPPs) of (BA)2(MA) n −1Pb n I3 n +1 (n = 1, 2, and 3) by a slow evaporation at a constant-temperature (SECT) solution-growth strategy. The as-grown 2D hybrid perovskite single crystals exhibit excellent crystallinity, phase purity, and spectral uniformity. Low-threshold lasing behaviors with different emission wavelengths at room temperature have been observed from the homologous 2D hybrid RPP single crystals. Our result demonstrates that solution-growth homologous organic–inorganic hybrid 2D perovskite single crystals open up a new window as a promising candidate for optical gain media.
Toxicogenomics and physiologically based pharmacokinetic (PBPK) models are useful approaches in chemical risk assessment, but the methodology to incorporate toxicogenomic data into a PBPK model to ...inform risk assessment remains to be developed. This study aimed to develop a probabilistic human health risk assessment approach by integrating toxicogenomic dose–response data and PBPK modeling using perfluorooctane sulfonate (PFOS) as a case study. Based on the available human in vitro and mouse in vivo toxicogenomic data, we identified the differentially expressed genes (DEGs) at each exposure paradigm/duration. Kyoto Encyclopedia of Genes and Genomes and disease ontology enrichment analyses were conducted on the DEGs to identify significantly enriched pathways and diseases. The dose–response data of DEGs were analyzed using the Bayesian benchmark dose (BMD) method. Using a previously published PBPK model, the gene BMDs were converted to human equivalent doses (HEDs), which were summarized to pathway and disease HEDs and then extrapolated to reference doses (RfDs) by considering an uncertainty factor of 30 for mouse in vivo data and 10 for human in vitro data. The results suggested that the median RfDs at different exposure paradigms were similar to the 2016 U.S. Environmental Protection Agency’s recommended RfD, while the RfDs for the most sensitive pathways and diseases were closer to the recent European Food Safety Authority’s guidance values. In conclusion, genomic dose–response data and PBPK modeling can be integrated to become a useful alternative approach in risk assessment of environmental chemicals. This approach considers multiple endpoints, provides toxicity mechanistic insights, and does not rely on apical toxicity endpoints.
This work proposes a novel approach to modulate the nucleation and growth of perovskite crystals in planar perovskite (CH3NH3PbI3-xClx) solar cells by intermixing precursor-capped inorganic ...nanoparticles of PbS. A small amount of dispersed PbS nanoparticles which were covered with perovskite precursor molecules of methylammonium iodide (CH3NH3I, MAI) through the ligand-exchange treatment functioned as effective seed-like nucleation sites to promote the formation of perovskite lattice structures. Through this intermixing-seeded growth technique, substantial morphological improvements, such as increased crystal domains, enhanced coverage, and uniformity, were realized in the perovskite thin films, and the corresponding solar cell devices exhibited a promising power conversion efficiency of 17.4%, showing an enhancement of approximately 25% compared to that of the controlled pristine solar cell device. The substantially enhanced crystal orientation, particularly along the direction perpendicular to the substrate, was evident from the synchrotron-based grazing incidence wide-angle X-ray scattering data. This observation was consistent with the enhanced carrier diffusion lengths and excellent reproducibility of high fill factors of the planar heterojunction perovskite devices fabricated through the proposed technique.
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