Rapid laser reactive sintering of BaCe0.7Zr0.1Y0.1Yb0.1O3-δ electrolyte for protonic ceramic fuel cells
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Chemical risk assessment considers potentially susceptible populations including pregnant women and developing fetuses. Humans encounter thousands of chemicals in their environments, few of which have been fully characterized. Toxicokinetic (TK) information is needed to relate chemical exposure to potentially bioactive tissue concentrations. Observational data describing human gestational exposures are unavailable for most chemicals, but physiologically based TK (PBTK) models estimate such exposures. Development of chemical-specific PBTK models requires considerable time and resources. As an alternative, generic PBTK approaches describe a standardized physiology and characterize chemicals with a set of standard physical and TK descriptors – primarily plasma protein binding and hepatic clearance. Here we report and evaluate a generic PBTK model of a human mother and developing fetus. We used a published set of formulas describing the major anatomical and physiological changes that occur during pregnancy to augment the High-Throughput Toxicokinetics (httk) software package. We simulated the ratio of concentrations in maternal and fetal plasma and compared to literature in vivo measurements. We evaluated the model with literature in vivo time-course measurements of maternal plasma concentrations in pregnant and non-pregnant women. Finally, we prioritized chemicals measured in maternal serum based on predicted fetal brain concentrations. This new model can be used for TK simulations of 859 chemicals with existing human-specific in vitro TK data as well as any new chemicals for which such data become available. Furthermore, this gestational model may allow for in vitro to in vivo extrapolation of point of departure doses relevant to reproductive and developmental toxicity.
The present study documents an automated approach to performing elemental analysis on a large group uranium ore concentrate (UOC) samples. In this work, 17 UOC samples, 2 quality control samples, and 26 process blanks were purified sequentially through a single 500 μL Uranium and TEtra Valent Actinides (UTEVA®) column. For each sample, the trace elemental impurities were separated from its dissolved uranium matrix on the UTEVA column and collected for analysis by inductively coupled plasma – optical emission spectroscopy / triple quadrupole mass spectrometry (ICP-OES/TQMS). The UTEVA column was subsequently regenerated prior to separation of the following sample. The column was efficiently regenerated, for each UOC, even after processing ~50 mg of uranium, cumulatively. The validity of the method was established by determining the trace impurities of two quality control uranium reference samples (CRM 124–1 and CUP-2). The current trace element measurements from the 17 UOC samples were compared to previously reported values from an interlaboratory comparison exercise, when available. The methodology employed here produces trace elemental analysis with excellent correlation to the previously reported data for many of the elements / samples, particularly when viewed through the context of existing geochemical comparisons tools (e.g. chondrite normalized variation plots).
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Inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) is an emerging technique for measuring actinide isotopes when assessing pre- and post- detonation nuclear material. In this study, ICP-MS/MS was investigated for direct Np and Pu quantitation in unseparated, dissolved bulk soil matrices. To achieve this, purified nitric oxide (NO) was investigated for the reactivity of Th, Np, U, Pu, Am, and Cm. Purifying NO prior to the collision reaction cell (CRC) results in increased sensitivity and allows for higher gas flows to be utilized for the removal of interferences. Here, the interference from uranium hydrides was mitigated to less than 3.85 x 10 -11 . This method was demonstrated on standard reference materials which were measured for 237 Np and 238,239,240 Pu in dilute sample digestions. The 238 Pu measurement was validated by spiking into a standard reference material and was accurately measured with an excess of 85000 of 238 U.
Inductively coupled plasma – time-of-flight – mass spectrometry (ICP-TOF-MS) was employed for the isotopic analysis of uranium particles of varying 235 U enrichment levels. Here, a single particle (SP)-based introduction scheme was employed such that individual particles, in a suspension, were analyzed. The uranium oxide microparticles were comprised of depleted uranium (DU, 235 U/ 238 U of 0.0017316(14)), natural uranium (NU, 235 U/ 238 U of 0.0072614(39)), and low enriched uranium (LEU, 235 U/ 238 U of 0.051025(15)). The percent relative difference of the SP-ICP-TOF-MS measured isotopic ratios compared to the expected values for the DU, NU, and LEU particle populations were 8.75, 0.12, and 1.23 %, respectively. After characterization, the DU and NU particles were doped within a complex sample matrix (Arizona Test Dust) containing Fe, Ti, Al, and Si particles, among others. Then, the suspension was analyzed via SP-ICP-TOF-MS and the detected particles were classified as DU or NU based on their measured 235 U/ 238 U ratio. In the same analysis, the matrix particles (i.e., Al, Fe, and Ti) were detected, demonstrating the simultaneous nuclide detection provided by the measurement platform. The presented SP-ICP-TOF-MS methodology for uranium particle characterization proved to be a high throughput method for detecting and isotopically discerning uranium particles with varying enrichment levels, in a complex matrix.
The heterogeneity in the composition of municipal solid wastes (MSW) poses significant challenges in the production of biofuel and bioproducts. This research aims to enhance the accuracy and efficiency of waste analysis and characterization by introducing a fast characterization approach for MSW-derived refuse-derived fuels (RDF) by combining Laser-Induced Breakdown Spectroscopy (LIBS) with advanced machine learning (ML) techniques. The approach combines data pre-processing of LIBS spectra of RDF, and the development of ML models trained on domain and theory-based spectral features for predicting process parameters. These models are adept at predicting key process parameters like High Heating Value (HHV), carbon content, and volatile matter. This approach can achieve an average RRMSE of 2.13% and R 2 of 0.98 or higher for all considered parameters on testing data. This work demonstrates significant potential for improving waste sorting, processing efficiency, and environmental compliance over traditional labor- and time-intensive laboratory waste analysis and characterization.
Fe-Mn composite oxide (FMO) is widely applied to the oxidation and removal of As(III) from water. However, As(III) can directly reduce manganese oxides, decreasing the oxidation capacity or reusability and thereby greatly limiting the applicability of FMO. Here, the oxidation capacity and reusability of FMO for As(III) were efficiently improved by light radiation, and the effect of typical coexisting ions (SO 4 2– and Ca 2+ ) on the removal of As(III) was also studied. O 2 •– produced from excited manganese oxide and ligand-to-metal charge transfer in iron oxide-As(III) complex enhanced As(III) oxidation and removal under light radiation. At an initial As(III) concentration of 1000 μg L –1 , the total As concentration was respectively decreased to 11.5, 1.5 and 4.4 μg L –1 under darkness, UV light and sunlight at 180 min, and could be reduced to below the guideline limitation of drinking water (10 μg L –1 ) within 40 and 60 min under UV light and sunlight, respectively. SO 4 2– exhibited negligible effect on As removal efficiency because FMO had obviously lower adsorption capacity and selectivity for SO 4 2– than for As(V). The adsorption of coexisting Ca 2+ on manganese oxide decreased the negative charge on the FMO surface, thereby improving As(III) adsorption and oxidation. FMO exhibited excellent reusability, and a total As removal efficiency of 99.1% was still maintained after five cycles of an adsorption-desorption process under UV light. Finally, this work elucidates the photochemical oxidation and removal mechanism of FMO for As(III), and proposes a low-cost and efficient method for the detoxification of As(III)-contaminated drinking water.
Reducing iron oxide to iron metal with fossil fuels produces circa 4% of annual anthropogenic CO 2 , ca. 2 Gt/a, as direct chemical emissions from the process. Using ammonia instead of coke—releasing only water and nitrogen as byproducts—could be a widely deployable method of decarbonizing industrial ironmaking, because ammonia carries hydrogen and can be transported easily worldwide. However, initial reports suggest that the reaction of ammonia with iron oxide is slow and inefficient, completed only in hours and using only a few percent of the ammonia supplied. Drawing on thermodynamic and kinetic analysis of the reaction, we explored high-temperature, high-flow reaction conditions designed to increase the reaction rate and the ammonia utilization. We report the reduction of iron oxide in 1 min while using 64% of the ammonia supplied. We show that these insights translate to the gram scale and the reduction of pelletized ore, a common form used industrially.
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