Browsing by Subject "metals"

Now showing 1 - 5 of 5
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    Association of Urinary and Blood Concentrations of Heavy Metals with Measures of Bone Mineral Density Loss: a Data Mining Approach with the Results from the National Health and Nutrition Examination Survey
    (Springer, 2021) Ximenez, João Paulo B.; Zamarioli, Ariane; Kacena, Melissa A.; Barbosa, Rommel Melgaço; Barbosa, Fernando, Jr.; Orthopaedic Surgery, School of Medicine
    Osteoporosis and its consequence of fragility fracture represent a major public health problem. Human exposure to heavy metals has received considerable attention over the last decades. However, little is known about the influence of co-exposure to multiple heavy metals on bone density. The present study aimed to examine the association between exposure to metals and bone mineral density (BMD) loss. Blood and urine concentrations of 20 chemical elements were selected from 3 cycles (2005–2010) NHANES (National Health and Nutrition Examination Survey), in which we included white women over 50 years of age and previously selected for BMD testing (N = 1892). The bone loss group was defined as participants having T-score < − 1.0, and the normal group was defined as participants having T-score ≥ − 1.0. We developed classification models based on support vector machines capable of determining which factors could best predict BMD loss. The model which included the five-best features-selected from the random forest were age, body mass index, urinary concentration of arsenic (As), cadmium (Cd), and tungsten (W), which have achieved high scores for accuracy (92.18%), sensitivity (90.50%), and specificity (93.35%). These data demonstrate the importance of these factors and metals to the classification since they alone were capable of generating a classification model with a high prediction of accuracy without requiring the other variables. In summary, our findings provide insight into the important, yet overlooked impact that arsenic, cadmium, and tungsten have on overall bone health.
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    Design of Anisotropically Shaped Plasmonic Nanocrystals from Ultrasmall Sn-Decorated In2O3 Nanoclusters Used as Seed Materials
    (American Chemical Society, 2022-12-07) Davis, Gregory A., Jr.; Prusty, Gyanaranjan; Hati, Sumon; Lee, Jacob T.; Langlais, Sarah R.; Zhan , Xun; Sardar, Rajesh; Chemistry and Chemical Biology, School of Science
    Ultrasmall inorganic nanoclusters (<2.0 nm in diameter) bridge the gap between individual molecules and large nanocrystals (NCs) and provide the critical foundation to design and prepare new solid-state nanomaterials with previously unknown properties and functions. Herein, for the first time, we report the monodispersed colloidal synthesis and successful isolation of metastable, rhombohedral-phase, <2.0 nm indium oxide (In2O3) nanoclusters. Ultrasmall nanocluster formation is controlled by a kinetically driven growth process, as evaluated through the variation of metal-to-passivating ligand concentrations. Although <2.0 nm-diameter In2O3 nanoclusters are synthesized in the presence of tin (Sn) precursors, they do not display typical localized surface plasmon resonance (LSPR) properties, which are commonly observed in Sn-doped In2O3 (Sn:In2O3) NCs. Our Raman and X-ray photoelectron spectroscopy and high-resolution transmission electron microscopy (HRTEM) analyses support the existence of Sn-decorated In2O3 nanoclusters, where Sn complexes reside on the surface of the nanocluster as Z-type ligands, as opposed to the formation of Sn:In2O3 nanoclusters, which behave as wide band gap (∼5.5 eV) nanomaterials. The experimentally determined band gap is in good agreement with the theoretical effective mass calculations. The newly synthesized Sn-decorated, 1.7 nm-diameter In2O3 nanoclusters are further used as reactive monomers for the seeded growth synthesis of bcc-phase, plasmonic Sn:In2O3 NCs via ex situ injection of In precursors without the addition of any Sn precursors. The LSPR peak of Sn:In2O3 NCs, which appear to form nanoflower assemblies, is tunable in the 1800–4000 nm region and possibly even the deep-IR region. In addition to altering the size and assembly of the spherical Sn:In2O3 NCs by introducing different amounts of indium acetylacetonate, injection of indium chloride precursors in the reaction mixture results in the formation of rod-shaped NCs. Surprisingly, Sn-decorated, <1.5 nm-diameter In2O3 nanoclusters do not grow into large plasmonic Sn:In2O3 NCs. Taken together, the results presented here contribute to the fundamental understanding of the surface free energy of ultrasmall metal oxide nanoclusters and further advance the knowledge on the phase transformation and growth of plasmonic NCs.
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    Molecular Dynamics Simulation of Electrical Resistivity in Sintering Process of Nanoparticle Silver Inks
    (Elsevier, 2016-12) Zhang, Yi; Wu, Linmin; Guo, Xingye; Jung, Yeon-Gil; Zhang, Jing; Department of Mechanical Engineering, School of Engineering and Technology
    A molecular dynamics (MD) model is developed to simulate low temperature sintering of silver nanoparticles and resultant resistivity. Due to the high surface to volume ratio, nanoparticle silver inks can sinter at low thermal curing temperatures, which are used in intense pulsed light (IPL) sintering process. In this study, the configurational change of nanoparticle silver during sintering is studied using the MD model. Then the resultant electric resistivity is calculated using the Reimann-Weber formula. The simulation results show that the resistivity decreases rapidly in the initial sintering stage, due to the fast neck formation and growth. Additionally, the predicted temperature-dependent resistivity evolutions are in good agreement with both experimental measurements and analytical sintering model, indicating that the resistivity decreases with increasing sintering temperature. The model provides a design tool for optimizing IPL process.
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    Phase field simulation of dendritic microstructure in additively manufactured titanium alloy
    (Elsevier, 2019-01) Zhang, Jing; Wu, Linmin; Zhang, Yi; Meng, Lingbin; Mechanical and Energy Engineering, School of Engineering and Technology
    Additive manufacturing (AM) processes for metals, such as selective laser sintering and electron beam melting, involve rapid solidification process. The microstructure of the fabricated material and its properties strongly depend on the solidification. Therefore, in order to control and optimize the AM process, it is important to understand the microstructure evolution. In this work, using Ti-6Al-4V as a model system, the phase field method is applied to simulate the microstructure evolution in additively manufactured metals. First, the fundamental governing equations are presented. Then the effects of various processing related parameters, including local temperature gradient, scan speed and cooling rate, on dendrites’ morphology and growth velocity are studied. The simulated results show that the dendritic arms grow along the direction of the heat flow. Higher temperature gradient, scan speed and cooling rate will result in small dendritic arm spacing and higher growth velocity. The simulated dendritic morphology and arm spacings are in good agreement with experimental data and theoretical predictions.
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    Towards In-baggage Suspicious Object Detection Using Commodity WiFi
    (IEEE, 2018) Wang, Chen; Liu, Jian; Chen, Yingying; Liu, Hongbo; Wang, Yan; Computer Information and Graphics Technology, School of Engineering and Technology
    The growing needs of public safety urgently require scalable and low-cost techniques on detecting dangerous objects (e.g., lethal weapons, homemade-bombs, explosive chemicals) hidden in baggage. Traditional baggage check involves either high manpower for manual examinations or expensive and specialized instruments, such as X-ray and CT. As such, many public places (i.e., museums and schools) that lack of strict security check are exposed to high risk. In this work, we propose to utilize the fine-grained channel state information (CSI) from off-the-shelf WiFi to detect suspicious objects that are suspected to be dangerous (i.e., defined as any metal and liquid object) without penetrating into the user's privacy through physically opening the baggage. Our suspicious object detection system significantly reduces the deployment cost and is easy to set up in public venues. Towards this end, our system is realized by two major components: it first detects the existence of suspicious objects and identifies the dangerous material type based on the reconstructed CSI complex value (including both amplitude and phase information); it then determines the risk level of the object by examining the object's dimension (i.e., liquid volume and metal object's shape) based on the reconstructed CSI complex of the signals reflected by the object. Extensive experiments are conducted with 15 metal and liquid objects and 6 types of bags in a 6-month period. The results show that our system can detect over 95% suspicious objects in different types of bags and successfully identify 90% dangerous material types. In addition, our system can achieve the average errors of 16ml and 0.5cm when estimating the volume of liquid and shape (i.e., width and height) of metal objects, respectively.