APPLICATION OF MICRO X-RAY FLUORESCENCE SPECTROMETRY FOR LOCALIZED AREA ANALYSIS OF BIOLOGICAL AND ENVIRONMENTAL MATERIALS

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1 Copyright(c)JCPDS-International Centre for Diffraction Data 2000,Advances in X-ray Analysis,Vol APPLICATION OF MICRO X-RAY FLUORESCENCE SPECTROMETRY FOR LOCALIZED AREA ANALYSIS OF BIOLOGICAL AND ENVIRONMENTAL MATERIALS John R. Sieber, Marek Lankosz* and Magdalena Boruchowska* National Institute of Standards and Technology, Gaithersburg, Maryland, USA *Faculty of Physics and Nuclear Techniques, Univ. of Mining and Metallurgy, Krakow, Poland ABSTRACT A feasibility study was conducted to evaluate the National Institute of Standards and Technology micro X-ray fluorescence spectrometer as a tool for testing material homogeneity at the microscale level as described by the Ingamells sampling constant. The research included testing Standard Reference Materials (SRM@s) at sampling levels in the range of micrograms and verification of a fundamental parameter method for quantitative analysis of biological and environmental materials. Such information would make SRMs more useful for comparison to real world samples that are often available in limited quantity. Sources of uncertainty considered in this work were spectrometer stability, specimen handling, and spectrum deconvolution. Repeatability values range from less than 1 % to as high as 30 % because mass fractions range from mg/kg to percent levels. Concentrations of analyte elements were calculated using a fundamental parameter approach. Scattered tube lines were used for matrix correction and to estimate the mass thickness of the sample. This procedure was previously developed for geological samples and glass. Therefore, it was necessary to evaluate its performance for organic samples. Reasonably good agreement between calculated concentrations and certified values was obtained for most elements. INTRODUCTION In the development of new analytical methods, there is a trend toward the use of smaller quantities of specimens. This trend is due to considerations of cost and portability of equipment, scarcity of sample, restricted collection times, and the need for speed of analysis. More researchers are using specimen quantities of less than 100 mg. Therefore, it is becoming more difficult to ensure that a subsample is completely representative of the material as a whole. Ingamells and Switzer [ 1 ] addressed the issue of subsampling error for elemental analysis of geological materials. For an analyzed component of a material, they defined a sampling constant, I&, in terms of the weight (mass) of the analytical subsample and the relative standard deviation, R (%), of repeated determinations of the component. They made the point that KS represents the amount of sample necessary to ensure a relative subsampling error of 1% (68% confidence level), and in fact I& is equal to the subsample mass if R = 1%. Recently, researchers have applied the concept of sampling constant for both elemental analysis and determinations of trace organic compounds in a variety of environmental materials. Zeisler [2] used instrumental neutron activation to study the inhomogeneity of certain elements in a number of NIST SRMs. Schantz [2] demonstrated the use of chromatographic techniques to

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3 Copyright(c)JCPDS-International Centre for Diffraction Data 2000,Advances in X-ray Analysis,Vol study errors from subsampling for determinations of organic chemicals in environmental samples. Of interest to users of X-ray fluorescence (XRF), Mattiuzzi and Markowicz [3] showed that a pass/fail homogeneity test using principles applied to within- and between-sample testing of bulk materials is feasible using a microbeam XRF spectrometer to obtain effective subsample masses below Working independently, we attempted to use the NIST Micro X-ray Fluorescence (MXRF) spectrometer to characterize a variety of biological and environmental materials for homogeneity at the microscale. Our efforts took the form of a feasibility study to enumerate the requirements for presenting samples to the spectrometer and for processing the measurements to obtain sampling constants for as many elements as possible. Due to the home-built nature of the equipment, we found it necessary to carefully characterize both the hardware and the software. The second objective of this work was to evaluate the performance of a computer program, by Lankosz and Pella [4], designed for quantitative analysis of geological materials. The program uses the coherently and incoherently scattered, tube target lines to calculate the average atomic number and mass thickness of the sample. It has been shown to be effective for samples of infinite or intermediate thickness with average atomic numbers ranging from 7 to 16. The goal was to evaluate the program for organic materials having high concentrations of H, C, N, and 0. SAMPLE QUANTITY The first task was to estimate the quantity of material analyzed by the spectrometer. The NIST MXRF spectrometer uses pinholes in MO metal to collimate the X-ray beam. The X-ray beam is produced within the tube with a spot size of about 0.25 mm and broadens as it passes through the pinhole and onto the sample. A part of the sample is measured only if the irradiated region and the region viewed by the detector coincide. The detector has an entrance collimator opening of 5.6 mm diameter. Because the incidence and takeoff angles are both approximately 45 degrees, the measured region is elliptical in shape. Two methods were used to determine the size of the measured region of a sample. First, the dimensions of the spectrometer were measured and trigonometry was used to calculate the lengths of the major and minor axes of the ellipse. Second, the area was measured by rastering a single Zn particle across the region. As illustrated in Fig. 1, a plot of the Zn count rate versus location, the ellipse is about 3.2 mm x 2.4 mm which are the same dimensions calculated by trigonometry for a 2 mm collimator. In the figure, the maximum Zn count rate is off center due to misalignment of the X-ray tube and detector. To complete the estimate of measured sample quantity, it is necessary to estimate the density of the material and the depth horn which X-rays emanate. All samples were prepared as pressed briquettes (no additives) with intermediate thickness for at least the more energetic analyte lines. As a fast approximation, sample density can be calculated using the mass and dimensions of the briquette. Information depths for the X-rays can be estimated using mass absorption coefficients and X-ray theory. Finally, the measured mass of material is estimated as the product of the density, the measured area, and the thickness of the briquette.

4 Copyright(c)JCPDS-International Centre for Diffraction Data 2000,Advances in X-ray Analysis,Vol mm Collimator P *. V GN. L.... w.. ' Y..Irn.... N. mm 11.m....I I X Location Figure 1. X-ray illuminated area from a 2 mm pinhole collimator in the NIST MXRF spectrometer. Zn count rate (color-coded, cps) is plotted versus measurement. location. X and Y dimensions are in pm- SPECTROMETER PERFORMANCE Now that we have an approximation of the measured mass of material, it is necessary to study the precision with which measurements can be obtained. Critical sources of variability include the X-ray source, detection subsystem, sample motion subsystem, and spectrum processing software. Experiments were performed to evaluate each of these components. To test the stability of the X-ray tube and detector, twenty-four (24) measurements were made of the Mn KLii,iii peak from pure Mn metal normally used to test the detector resolution. Since only one peak was measured and the sample was not moved, the relative standard deviation is a direct measure of the stability of X-ray source and detector. The relative standard deviation (rsd) was % and was only slightly higher than the counting statistical error (cse) of %. To test the sample movement stage and spectrum processing software, measurements were made of an oil sample as an example of a completely homogeneous material. The oil was prepared to contain 400 mgikg each of Ca, Ba, and Zn plus 40 mg/kg of Hg. A small aliquot was placed in a sample cup of 37 mm diameter with 4 pm thick support film to create a thin, uniform layer of oil which was measured near the center of the cup. Table 1 contains the results of nine measurements of the four elements plus the scattered radiation from the MO tube. Good precision was observed for the MO tube lines, Zn, and Hg in that the rsd values are between 0.9 % and 1.4 %. However, even allowing for poorer counting statistics, the precision for Ca and Ba is considerably worse than for the other elements. Since Ca K-series lines and Ba L-series lines

5 Copyright(c)JCPDS-International Centre for Diffraction Data 2000,Advances in X-ray Analysis,Vol are in a narrow energy region, they overlap slightly in an energy dispersive spectrum. However, it is reasonable to expect the software to correctly handle this situation. Table 1. Oil sample count rate data from nine measurement locations in a 3 x 3 array. Element Ca Ba zn m MO MO Line LiiiMiv KL LiiiMiv la(l) KL(C) Average (cps) StdDev (cps) n rsd % cse % A material with more complex composition was analyzed to further investigate the performance of the software. Specially grown algae from the International Atomic Energy Agency (IAEA) was chosen due to the nature of its physical and chemical compositions. These algae [5], IAEA-393, were grown in water containing heavy metals at high concentrations so that the algae incorporated high concentrations of Cr, Fe, Zn, As, Cd, Hg, and Pb. Table 2 contains a summary of count rate data obtained from nine locations in a 3 x 3 array in the center of a 13 mm diameter briquette. Spectra were collected for 1000 seconds live time and the quantity measured at each location was estimated to be 2 mg. The data for Ca and Cd are highlighted to show a problem with the spectrum deconvolution. IAEA-393 contains approximately 2500 mg/kg Ca and 50 mg/kg Cd. The Cd L- series lines are weak compared to the K-series lines of K and Ca that all overlap in an energy dispersive spectrum. The problem with the data is that five times out of nine, no Cd peaks were found by the software. This apparently caused the Ca KLii,iii count rate to change from 41 counts per second (cps) (Cd peaks not found) to 48 cps (Cd peaks found). One reason for the problem is insufficient acquisition time for the spectra. When acquisition time is increased to 2000 seconds live time, the Cd L-series peaks are always found, but the precision problem is reduced, not eliminated. Table 2. Count rate data for nine measurements of IAEA-393 Jet-Milled Algae Average StdDev rsd % cse % K Ca Cd Cr Mn Fe Ni cu Zn AS Hg Pb MO CPS CPS

6 Copyright(c)JCPDS-International Centre for Diffraction Data 2000,Advances in X-ray Analysis,Vol QUANTITATIVE ANALYSIS In 1995, Lankosz and Pella [2] published work describing a computer program for quantitative analysis of polished geological samples by microbeam X-ray This fundamental parameters program was novel in that it uses a calculated tube spectrum to allow the use of polychromatic radiation in combination with coherent and incoherent scatter for estimation of the mass thickness of the sample and its average atomic number. The method was intended for the analysis of samples that contain relatively high concentrations of low-z elements, but not more than a few percent of high-z elements, e.g. Pb, Sr, etc. Their publication showed the method was capable of accuracy to better than 10 % when the average atomic number was about 8. For glasses having high Li and B contents or when Mg, Al, or Si were included in the unanalyzed fraction, the accuracy was somewhat poorer. The samples analyzed for our work included SRM 1566a Oyster Tissue, SRM 1570a Spinach Leaves, SRM 1577b Bovine Liver, and SRM 1648 Urban Particulate Matter. The first three materials are mostly organic with high concentrations of H, C, N, and 0. The elements Na, Mg, P, and S were included in the unanalyzed fraction due to spectrometer insensitivity or the overlap of MO L-series lines from the X-ray tube. Table 3 contains the quantitative results in comparison to the certified contents of the four materials. Each found value is the average of nine determinations processed individually for count rates and quantitative analysis. The tabulated percent difference values (%diff) show that the results are accurate to within 5 to 10 percent for most elements. In many cases, the concentrations were below 50 mg/kg and the accuracy was somewhat poorer at 10 % to 15 % difference. A noticeable problem exists for Ca determinations in SRMs 1566a and 1577b. The cause has not been determined. Table 3. Quantitative results for Standard Reference Materials compared to certified values. SRM Al Cl K Ca Cr Mn Fe Cu Zn As Br Rb Sr mgikg % % % wdk mgkz wdkg &kg mgh wzkz w&i 1566a found cert %diff a found cert (13) 55.6 %diff found cert (9.7) 13.7 %diff Pb WY@ 1648 found cert (0.45) (860) (500) 6550 %diff

7 Copyright(c)JCPDS-International Centre for Diffraction Data 2000,Advances in X-ray Analysis,Vol As mentioned above, the computer program calculates an estimate of the area mass density of the specimen. As a result, there are nine individual estimates available for the density of each briquette that can be compared to one another and to the density calculated from the mass and dimensions of the whole briquette. Table 4 contains this information for two materials, SRM 1566a, and SRM The estimated density values from XRF data for the briquette of SRM 1566a exhibit significantly more variation than those from SRM This is likely due to differences in the nature and preparation of the material prior to certification by NIST. This variability necessitates first the complete quantitative analysis of each measured region before the comparison of data to investigate material homogeneity. In that way, density variations and their effect on measured count rate are taken into account. The disadvantages are that uncertainties associated with the fundamental parameters and the calibration of average atomic number will be folded into the overall uncertainty. Table 4. Measured area density values for briquettes of SRM 1566a and SRM SRM 1566a, 3 x 3 array of locations SRM 1648,3 x 3 array of locations Average: f (Is, n=9) Average: Z!I (Is, n=9) Whole briquette: mg/cm Whole briquette: mg/cm (calculated from mass and dimensions) (calculated from mass and dimensions) CONCLUSION The feasibility study performed to determine if the NIST MXRF spectrometer can be used for microscale homogeneity studies revealed a few things about the spectrometer and the materials. The spectrometer is capable of precise measurements, but problems with the spectrum manipulation software prevented realization of the potential of the hardware and accumulation of meaningful information on material homogeneity. The computer program developed by Lankosz and Pella for geological samples works reasonably well when applied to organic matrix materials. However, the method of presenting samples as small briquettes, while convenient, suffers from density variations across the disk, especially for organic materials, that prevent direct analysis of homogeneity using measured count rates.

8 Copyright(c)JCPDS-International Centre for Diffraction Data 2000,Advances in X-ray Analysis,Vol REFERENCES [l] Ingamels, C.O.; Switzer, P., Talanta, 1973,20(6), [2] Zeisler, R.L.; Schantz, M.M., Analytical Chemistry Division Technical Activities, National Institute of Standards and Technology, 1997, [3] Mattiuzzi, M. and Markowicz, A., 47th Annual Denver X-Ray Conference, paper F-41, [4] M. Lankosz; P.A. Pella, X-Ray Spectrometry, 1995,24(6), [5] Zeisler, R.; Dekner, R.; Zeiller, E.; Doucha, J.; Mader, P.; Kucera, J., Fresenius J. Anal. Chem., 1998,360,