Tissue-equivalent materials are used for simplifying quality control and quality assurance procedures, both in diagnostic and therapeutic radiology. Important information to formulate a tissue-equivalent material is elemental composition of its base materials. However, this information is not easily obtained. Therefore we propose a stoichiometric analysis method to investigate the elemental composition of the base materials that can potentially be used for manufacturing tissue-equivalent materials. In this technique, we combined the stoichiometric calibration and the basic data method to obtain the elemental composition of materials from measured computer tomography (CT) numbers. The elemental composition, with the maximum number of the elements of the material in question up to the available number of different tube voltages at the CT scanner, was analysed using the proposed approach. We tested eight different cylinders in this study. The estimated elemental compositions of unspecified materials in the cylinders were evaluated by comparing the calculated and the simulated CT numbers to the measured ones; the results showed good correlation with maximum absolute differences of 1.9 and 3.7 HU, respectively. The accuracy of the stoichiometric analysis method to estimate the elemental composition was influenced by the accuracy of the measured CT numbers. The method proposed allows for determining the elemental composition of the base materials which can then be applied further to formulate tissue-equivalent materials.
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http://dx.doi.org/10.1088/0031-9155/56/10/005 | DOI Listing |
ACS EST Air
January 2025
Environmental Engineering Program, University of Colorado Boulder, 1111 Engineering Drive, Boulder, Colorado 80309-0428, United States.
Quantifying changes in the properties of smoke aerosols under varying conditions is important for understanding the health and environmental impacts of exposure to smoke. Smoke composition, aerosol liquid water content, effective density (ρ), and other properties can change significantly as smoke travels through areas under different ambient conditions and over time. During this study, we measured changes in smoke composition and physical properties due to oxidative aging and exposure to humidity.
View Article and Find Full Text PDFLoading with non-metal cocatalysts to regulate interfacial charge transfer and separation has become a prominent focus in current research. In this study, g-CN/CNT composites loaded with non-metallic cocatalysts were prepared through pyrolysis using urea and CNTs. Various characterization techniques, including transmission electron microscopy (TEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), ultraviolet-visible diffuse reflectance spectroscopy (UV-vis DRS), photoelectrochemical (PEC) analysis, fluorescence lifetime spectroscopy (TRPL), electron paramagnetic resonance spectroscopy (ESR), and photoluminescence (PL) spectroscopy, were employed to analyze the sample's microstructure, phase composition, elemental chemical states, and photoelectronic properties.
View Article and Find Full Text PDFJ Hazard Mater
January 2025
State Key Lab of Geohazard prevention & Geoenvironment protection, College of Materials and Chemistry & Chemical Engineering, Chengdu University of Technology, Chengdu 610059, China. Electronic address:
Sulfur nanoparticles (SNPs) and their composites are promising for heavy metal adsorption, yet current SNPs often lack surface S, leading to low affinity toward heavy metal and ease of aggregation. Here, we report a simple light-driven method for facile prepare SNPs with surfaces enriched with S and in-situ load them onto graphene oxide (GO) to fabricate GO-S composites. Under illumination, the O generated by photosensitizer phloxine B was able to oxidize S into elemental SNPs.
View Article and Find Full Text PDFPhys Med Biol
January 2025
Graduate School of Medicine, Osaka University, 2-2 Yamada-oka, Suita, Osaka, 565-0871, JAPAN.
Accurate dose predictions are crucial to maximizing the benefits of carbon-ion therapy. Carbon beams incident on the human body cause nuclear interactions with tissues, resulting in changes in the constituent nuclides and leading to dose errors that are conventionally corrected using conventional single-energy computed tomography (SECT). Dual-energy computed tomography (DECT) has frequently been used for stopping power estimation in particle therapy and is well suited for correcting nuclear reactions because of its detailed body-tissue elemental information.
View Article and Find Full Text PDFiScience
January 2025
School of Mathematics and Statistics, Zhengzhou University, Zhengzhou 450001, China.
This study introduces a hybrid network model for phase classification, integrating quantum networks and complex-valued neural networks. This architecture uses elemental composition as its only input, eliminating complex feature engineering. Parameterized quantum networks handle sparse elemental data and convert data from real to complex domains, increasing information dimensionality.
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