Classification of mineral particles by non-linear mapping of electron microprobe energy dispersive X-ray spectra

The Analyst ◽  
1994 ◽  
Vol 119 (5) ◽  
pp. 971 ◽  
Author(s):  
Boris Treiger ◽  
Igor Bondarenko ◽  
Piet Van Espen ◽  
Ren� Van Grieken ◽  
Fred Adams
Keyword(s):  
Electron Microprobe ◽  
Linear Mapping ◽  
Energy Dispersive ◽  
X Ray ◽  
Mineral Particles ◽  
Non Linear

Long-term variations in individual particle types in the aerosol of Phoenix, Arizona, as determined using automated electron microprobe analysis and multivariate statistical techniques

1993 ◽  
Vol 51 ◽  
pp. 742-743
Author(s):  
Karen A. Katrinak ◽  
James R. Anderson ◽  
Peter R. Buseck
Keyword(s):  
Electron Microprobe ◽  
Fine Fraction ◽  
Coarse Fraction ◽  
Motor Vehicles ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
X Ray ◽  
Mineral Particles ◽  
Anthropogenic Air Pollutants

Aerosol samples were collected in Phoenix, Arizona on eleven dates between July 1989 and April 1990. Elemental compositions were determined for approximately 1000 particles per sample using an electron microprobe with an energy-dispersive x-ray spectrometer. Fine-fraction samples (particle cut size of 1 to 2 μm) were analyzed for each date; coarse-fraction samples were also analyzed for four of the dates.The data were reduced using multivariate statistical methods. Cluster analysis was first used to define 35 particle types. 81% of all fine-fraction particles and 84% of the coarse-fraction particles were assigned to these types, which include mineral, metal-rich, sulfur-rich, and salt categories. "Zero-count" particles, consisting entirely of elements lighter than Na, constitute an additional category and dominate the fine fraction, reflecting the importance of anthropogenic air pollutants such as those emitted by motor vehicles. Si- and Ca-rich mineral particles dominate the coarse fraction and are also numerous in the fine fraction.

Application of Energy Dispersive X-ray Fluorescence, γ-ray Spectrometry and Multivariate Statistical Approach for the Soil Classification of Samples from Douala – Cameroon

2021 ◽  
pp. 109589
Author(s):  
Joel Cebastien SHOUOP GUEMBOU ◽  
Maurice MOYO. NDONTCHUENG ◽  
Jilbert Eric MEKONGTSO NGUELEM ◽  
Ousmanou MOTAPON ◽  
David STRIVAY
Keyword(s):  
Statistical Approach ◽  
Soil Classification ◽  
Energy Dispersive ◽  
Multivariate Statistical ◽  
X Ray ◽  
Multivariate Statistical Approach ◽  
Γ Ray

scholarly journals Multi-scale characterization of glaucophane from Chiavolino (Biella, Italy): implications for international regulations on elongate mineral particles

2021 ◽  
Vol 33 (1) ◽  
pp. 77-112
Author(s):  
Ruggero Vigliaturo ◽  
Sabrina M. Elkassas ◽  
Giancarlo Della Ventura ◽  
Günther J. Redhammer ◽  
Francisco Ruiz-Zepeda ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Environmental Scanning Electron Microscopy ◽  
Atomic Scale ◽  
Energy Dispersive ◽  
Mineral Particle ◽  
X Ray ◽  
Mineral Particles ◽  
Particle Population ◽  
Investigation Methods

Abstract. In this paper, we present the results of a multi-analytical characterization of a glaucophane sample collected in the Piedmont region of northwestern Italy. Investigation methods included optical microscopy, powder X-ray diffraction, Fourier-transform infrared spectroscopy, µ-Raman spectroscopy, Mössbauer spectroscopy, electron probe microanalysis, environmental scanning electron microscopy and energy-dispersive X-ray spectroscopy, and scanning/transmission electron microscopy combined with energy-dispersive X-ray spectroscopy and electron energy-loss spectroscopy. In addition to the crystal–chemical characterization of the sample from the mesoscale to the near-atomic scale, we have also conducted an extended study on the morphology and dimensions of the mineral particles. The main finding is that studying the same particle population at different magnifications yields different results for mineral habit, dimensions, and dimensional distributions. As glaucophane may occur as an elongate mineral particle (e.g., asbestiform glaucophane occurrences in California and Nevada), the observed discrepancies therefore need to be considered when assessing potential breathability of such particles, with implications for future regulations on elongate mineral particles. While the sample preparation and particle counting methods are not directly investigated in this work, our findings suggest that different magnifications should be used when characterizing an elongate mineral particle population, irrespective of whether or not it contains asbestiform material. These results further reveal the need for developing improved regulation for elongate mineral particles. We thus propose a simple methodology to merge the datasets collected at different magnifications to provide a more complete description and a better risk evaluation of the studied particle population.

scholarly journals Elemental content profiles in propolis from several cities of Turkey

2017 ◽  
Vol 7 (8) ◽  
pp. 661 ◽  
Author(s):  
Canan Aksoy ◽  
Meltem Maras Atabay ◽  
Engin Tirasoglu ◽  
Ezgi Taylan Koparan ◽  
Aysel Kekillioglu
Keyword(s):  
Folk Medicine ◽  
Calcium Content ◽  
Energy Dispersive ◽  
Elemental Content ◽  
Good Resolution ◽  
Element Analysis ◽  
X Ray ◽  
Geological Origin ◽  
Macro Element

Background: Macro-element content profiles in propolis that have been previously used in traditional folk medicine have provided enough information to develop a classification of the geological origin of propolis. Within this study, we aim to contribute our research to existing literatüre, particularly through our use of EDXRF spectroscopy, which has not been used to study propolis before. The results of the study led us to conclude that the residues of heavy metals were a limited concentration in Turkish propolis samples.Objective: The purpose of this study was to investigate the macro-element profiles in Turkish propolis from 18 different cities of Turkey.  Methods: The macro-element of 22 raw propolis samples were investigated using Energy-Dispersive X-ray fluorescence spectrometry.Results: Turkish Propolis was discovered to be rich with minerals of potassium, sodium which could be more beneficial in human nutrition. Potassium content was at a relatively higher level than other elements in these samples, while calcium content was at  alower level in those samples from various regions of Turkey.Conclusion: The elements of propolis that we studied were distinctive enough to make the discrimination of propolis from different locations in Turkey possible. The quantification by energy-dispersive X-ray fluorescence spectrometry procedures provided good resolution of multi-element analysis in propolis samples.Keywords: Propolis; element analysis; energy-dispersive X-ray fluorescence spectrometre 

The discrimination and classification of small fragments of window and non-window glasses using energy-dispersive x-ray fluorescence spectrometry

1980 ◽  
Vol 9 (3) ◽  
pp. 119-122 ◽  
Author(s):  
R. J. Dudley ◽  
C. R. Howden ◽  
T. J. Taylor ◽  
K. W. Smalldon
Keyword(s):  
Energy Dispersive ◽  
Fluorescence Spectrometry ◽  
X Ray

scholarly journals Use of energy-dispersive X-ray fluorescence combined with chemometric modelling to classify honey according to botanical variety and geographical origin

2019 ◽  
Vol 412 (2) ◽  
pp. 463-472 ◽  
Author(s):  
Yiannis Fiamegos ◽  
Catalina Dumitrascu ◽  
Michele Ghidotti ◽  
Maria Beatriz de la Calle Guntiñas
Keyword(s):  
Geographical Origin ◽  
External Validation ◽  
Principal Component ◽  
Energy Dispersive ◽  
Sample Treatment ◽  
Classification Models ◽  
Botanical Variety ◽  
X Ray ◽  
Food Commodities

AbstractHoney is one of the food commodities most frequently affected by fraud. Although addition of extraneous sugars is the most common type of fraud, analytical methods are also needed to detect origin masking and misdescription of botanical variety. In this work, multivariate analysis of the content of certain macro- and trace elements, determined by energy-dispersive X-ray fluorescence (ED-XRF) without any type of sample treatment, were used to classify honeys according to botanical variety and geographical origin. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to create classification models for nine different botanical varieties—orange, robinia, lavender, rosemary, thyme, lime, chestnut, eucalyptus and manuka—and seven different geographical origins—Italy, Romania, Spain, Portugal, France, Hungary and New Zealand. Although characterised by 100% sensitivity, PCA models lacked specificity. The PLS-DA models constructed for specific combinations of botanical variety-country (BV-C) allowed the successful classification of honey samples, which was verified by external validation samples.

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