Current Issue : July-September Volume : 2023 Issue Number : 3 Articles : 5 Articles
Particle size and morphology analysis is a problem common to a wide range of applications, including additive manufacturing, geological and agricultural materials’ characterisation, food manufacturing and pharmaceuticals. Here, we review the use of microfocus X-ray computed tomography (X-ray CT) for particle analysis. We give an overview of different sample preparation methods, image processing protocols, the morphology parameters that can be determined, and types of materials that are suitable for analysis of particle sizes using X-ray CT. The main conclusion is that size and shape parameters can be determined for particles larger than approximately 2 to 3 μm, given adequate resolution of the X-ray CT setup. Particles composed of high atomic number materials (Z > 40) require careful sample preparation to ensure X-ray transmission. Problems occur when particles with a broad range of sizes are closely packed together, or when particles are fused (sintered or cemented). The use of X-ray CT for particle size analysis promises to become increasingly widespread, offering measurements of size, shape, and porosity of large numbers of particles within one X-ray CT scan....
Extreme ultraviolet spectra of Na-like and Mg-like Os and Ir were recorded at the National Institute of Standards and Technology using a grazing incidence spectrometer. We report a method in EBIT spectral analysis that reduces signals from contaminant lines of known or unknown origin. We utilize similar ion charge distributions of heavy highly charged ions that create similar potentials for lighter contaminating background elements. First-order approximations to ion distributions are presented to demonstrate differences between impurity elements with and without heavy ions present....
We present five new dinuclear triple helicate compounds of types [Mn2L3](ClO4)4, [Co2L3](BF4)4, [Ni2L3](BF4)4, [Cu2L3](BF4)4, and [Zn2L3](BF4)4, where L is a previously reported semi-rigid ligand incorporating two α-diimine primary donor groups and two secondary 4-pyridyl donor groups. All complexes have been characterized in both solution and the solid state. Single crystal X-ray diffraction studies were used to probe the variation in the respective helical structures as the coordinated metal ion was altered, including the effect on the orientations of the secondary binding domains. The influence of the metal ion size, the spin state in the case of Fe(II), and the presence of Jahn-Teller distortions on the overall helical structure has been investigated. These results form a basis for the design and construction of new large metallosupramolecular architectures which manifest properties associated with the constituent helical metalloligand units....
A multi-principal element alloy (MPEA) is a type of metallic alloy that is composed of multiple metallic elements, with each element making up a significant portion of the alloy. In this study, the initial atomic percentage of elements in an (AlFeNiTiVZr)1-xCrx MPEA alloy as a function of the position on the surface was investigated using machine learning algorithms. Given the absence of a linear relationship between the atomic percentage of elements and their location on the surface, it is not possible to discern any clear association from the dataset. To overcome this non-linear relationship, the prediction of the atomic percentage of elements was accomplished using both decision tree (DT) and random forest (RF) regression models. The models were compared, and the results were found to be consistent with the experimental findings (a coefficient of determination R2 of 0.98 is obtained with the DT algorithm and 0.99 with the RF one). This research demonstrates the potential of machine learning algorithms in the analysis of wavelength-dispersive X-ray spectroscopy (WDS) datasets....
In the event of uranium release into the environment due to an accident, confirming the presence of uranium contamination is difficult because uranium is a naturally occurring element. In this study, we developed a method based on X-ray fluorescence (XRF) for the facile screening of uranium in brackish water samples in the event of an accident in a coastal area. Graphene oxide nanosheets were added to uncontaminated brackish water sampled from different sites to adsorb the uranium present in the samples, if any. The graphene oxide nanosheets were then collected using a membrane filter and analyzed using XRF. The results revealed that the signal intensity of the U Lα peak was proportional to the salinity. Hence, uranium contamination could be confirmed when the intensity of the U Lα peak was significantly greater than that derived from the background uranium content, as estimated from the salinity value. Thus, in the event of an accident, the salinity of the collected brackish water should be measured, and XRF analysis should be performed using our developed method. This method is useful for screening brackish water for uranium contamination....
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