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Characterization Techniques for Bio-Nanocomposites
Published in Shrikaant Kulkarni, Neha Kanwar Rawat, A. K. Haghi, Green Chemistry and Green Engineering, 2020
X-ray fluorescence spectrometry (XRF) is a non-destructive method of elemental analysis. When an X-ray beam is incident upon a target element, orbital electrons are dislodged. The vacancies or holes generated in the inner shells are filled by outer shell electrons. Energy releases during the process in the form of secondary X-rays known as fluorescence (FLU). The energy of the emitted X-ray radiation is fallout of the distribution of electrons in the excited atom. A unique electron distribution of every element help produce the quantitative analysis of Ba, Ca, Zn, P, and S in additives and lubricating oils, lead, and sulfur in gasoline, sulfur in crudes and fuel oils, and halogens in polymers. The high analytical precision of wavelength dispersive X-ray fluorescence spectrometry (WDXRF) has made it possible to develop methods for the precious metal assay of catalyst used in reforming process as against the precision of classical wet chemical methods. Metals like Pt, Ir, Re, or Ru can be been determined from numerous catalysts.
Feedstock Preparation by Gasification
Published in James G. Speight, Handbook of Petrochemical Processes, 2019
The chemical composition of the coal is defined in terms of its proximate and ultimate (elemental) analyses (Speight, 2013a). The parameters of proximate analysis are moisture, volatile matter, ash, and fixed carbon. Elemental analysis (ultimate analysis) encompasses the quantitative determination of carbon, hydrogen, nitrogen, sulfur, and oxygen within the coal. Additionally, specific physical and mechanical properties of coal and particular carbonization properties are also determined.
Electrical, Physical, and Chemical Characterization
Published in Robert Doering, Yoshio Nishi, Handbook of Semiconductor Manufacturing Technology, 2017
Dieter K. Schroder, Bruno W. Schueler, Thomas Shaffner, Greg S. Strossman
The detection limits for XPS are on average in the part per thousand range under typical analysis conditions. Therefore, the technique is not generally suitable for trace elemental analysis. The sensitivities for some, usually, heavier elements may be nearly an order of magnitude better than the average, while the very lightest elements (Be, Li) have sensitivities closer to 1 atomic percent.
Reactive nitrogen and total organic carbon calibration techniques for the Aerodyne aerosol mass spectrometer
Published in Aerosol Science and Technology, 2023
Derek J. Price, Alison M. Piasecki, Rishabh U. Shah, Katherine L. Hayden, James B. Burkholder, James M. Roberts, Ann M. Middlebrook
Possible reasons for the factor of two difference between the two methods are less clear for 4-NC. Since this experiment was size selected (Figure S13a), we do not believe that lens transmission is causing the discrepancy. There is another size-selected experiment (not shown) where NAMS is also roughly a factor of two lower than Nr. Because most of the nitrogen was found in the CHN+ and C6H5NO4+ ions, we suspect that there might be issues with using the elemental analysis package, specifically related to the position of the carbon atom relative to nitrogen, and other parameters that go into the calculation of Norg in Equation (8). The N:C ratios from the Improved-Ambient elemental analysis of the AMS organic part of the mass spectra are inherently biased low because some of the nitrogen fragments into N+, which cannot be easily distinguished from nitrogen due to air (Aiken, DeCarlo, and Jimenez 2007; Aiken et al. 2008; Canagaratna et al. 2015). Aiken et al. (2008) report a small average bias (< 5%) and an uncertainty of 22% in the C:N ratio (or N/C as was reported), which is smaller than the factor of two observed here. The elemental analysis data processing also relies on the ability to detect isolated ions containing both carbon and nitrogen, which could be problematic for high m/z in the mass spectra. This could further lead to undercounting the amount of Norg with the HToF spectra.
Predicting coal elemental components from proximate analysis: Explicit versus implicit nonlinear models
Published in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2021
In the designing and operating energy conversion systems using coal as a fuel, coal elemental composition is one of the most key features. It is directly associated with the heating value and takes an essential role in the mass and energy computation. In addition to this, predicting the flow rate of flue gas and determining air quality in coal combustion are required to know elemental composition (Nhuchhen 2016; Yi et al. 2017). Generally, proximate and elemental analysis components are used to characterize the coals (Akkaya 2013, 2009). Proximate analysis is used to determine the ratio of ash (A), volatile matter (VM), fixed carbon (FC) and moisture (M). The elemental analysis is chosen to measure the amounts of major elements, specifically, carbon (C), oxygen (O), hydrogen (H), nitrogen (N) and sulfur (S). Sophisticated expensive equipment, long time and expertise are needed for the experimental determination of ultimate analysis data (Parikh, Channiwala, and Ghosal 2007). However, a common apparatus can be used easily and quickly for obtaining proximate analysis data (Yi et al. 2017). In this context, accurate predicting coal elemental component contents by using proximate analysis data can provide valuable benefits to the researchers and engineers in that area.
Mechanical and microstructural properties of recycled reactive powder concrete containing waste glass powder and fly ash at standard curing
Published in Cogent Engineering, 2018
Belachew Asteray Demiss, Walter Odhiambo Oyawa, Stanley Muse Shitote
Moreover, X-ray fluorescence (XRF) spectrometry analysis was conducted in Kenya Ministry of Mining to characterize the chemical composition of finely dispersed local waste samples. XRF spectrometry is an elemental analysis technique based on the principle that individual atoms, when excited by an external energy source, emit X-ray photons of a characteristic energy or wavelength. By counting the number of photons of each energy emitted from a sample, the elements present may be identified and quantitated (http://archaeometry.missouri.edu/xrf_overview.html). Accordingly, mineral analysis for the proposed raw waste materials was conducted for Silica (SiO2), Alumina (Al2O3), Iron Oxide (Fe2O3), Calcium Oxide (CaO), Magnesium Oxide (Mgo), Sodium Oxide (Na2O), Potassium Oxide (K2O), Titanium Dioxide (TiO2), Manganese Oxide (MnO) and loss of ignition.