930
Anal. Chem. 1987, 59, 930-937
Determination of the Thickness of Flat Particles by Automated Electron Microprobe Analysis Bert J. Raeymaekers, Xiande Liu, Koen H. Janssens, Piet J. Van Espen, and Fred C. Adams*
Department of Chemistry, University of Antwerp (U.Z.A.),Uniuersiteitsplein 1, B-2610 Wilrijk, Belgium
A method Is described for the measurement of the thlckness of thin disk-shaped (laminar) mlcropartlcles by automated analytical electron microscopy. The thkkness Is determined from the backscattered electron Intensity and the X-ray Intensity data, relying on a fast, iteratively applled standardless ZAF correction procedure. The method Is illustrated through measurements of thin sliver bromide mlcrocrystallites and metallic mkropartlcies obtained by sparking.
In quantitative electron microprobe analysis of microscopical objects, the thickness of the particles is an important parameter for the successful application of the well-known ZAF correction procedure. Different methods for the determination of the thickness of films have been described. Originally, a methodology was based on the X-ray continuum intensity ( l ) but , since reliable backscattered electron (BSE) detectors such as the Everhardt-Thornley or the solid-state semiconductor detector became available, interest shifted toward backscattered electron intensity. The thickness of particles can also be accurately determined on the basis of measured X-ray intensities, but the acquisition of an X-ray spectrum takes significantly more time than the measurement of the backscattered electron intensity. Therefore, the latter method is very suitable to use in combination with automated electron probe analysis. The relation of BSE intensity as a function of specimen thickness can be described most accurately by Monte Carlo calculations ( 2 , 3 )or by the numerical solution of the electron transport equations ( 4 ) . Unfortunately, both these approaches require rather long computation times and are consequently not suitable for fast calculations necessary when large particle collections need to be measured. Only through the application of straightforward analytical expressions of the BSE intensity and the composition of the specimen, sufficiently fast thickness determinations are possible. Reuter developed an expression for thickness calculations of supported and unsupported thin films, assuming that the electron transmission through the film can be described by a simple exponential law (5). A more advanced theory, worked out by Niedrig (6)approximates closely to the results obtained by Monte Carlo simulations of the backscattering process for samples differing widely in composition. Quantitative electron probe microanalysis of single particles requires the accurate knowledge of three-dimensional size and shape of the particle (7). A microscopic image obviously contains only a two-dimensional geometry of the particle, and methods relying on tilting of the sample or the application of shadowing techniques should be used to provide the particle size in the z-direction. This, however, requires carefully performed manual operations for each single particle and prevents the routine use for large particle sets. During the last few years hardware became commercially available for computer-controlled electron probe microanalysis and software was developed for automated, virtually unattended particle analysis. These systems can only measure two-dimensional
size and shape information for irregularly shaped objects (8), though for objects not exceeding the electron penetration range, some information on the thickness can be obtained from the X-ray and electron intensities. Linders (9) utilized an automated scanning transmission electron microscope (STEM) to compare three methods for thickness determinations of evaporated spray droplets and thin biological specimen relying respectively on the X-ray continuum and the backscattered and the transmitted electrons. The method based on the BSE intensity appeared to be a suitable alternative to the old continuum method (IO), but the measurement of the transmitted electron intensity allowed the most accurate possibility for the determination of the mass thickness. In this paper we describe a method for the determination of composition and shape for collections of thin laminaryshaped particles (thickness less than one-third the average diameter), using a computer-controlled electron microprobe.
THEORY Analytical Expression for the Backscatter Coefficient. Various models for electron backscattering are reported in the literature. Niedrig (6) combined the equation for single Rutherford scattering, proposed by Everhardt ( I l ) ,with an isotropic diffusion term as used by Archard (12) and Thummel (13). This extended Everhardt theory is in good agreement with experimental data. According to this theory, the backscatter coefficient for a thin, unsupported film can be expressed as dx) = a
(I-
+ k - 1) (a + k ) ( a + k + 1)
a+k
(a
:)"'*I
+
k(u
-
a
x
+(Uk)(u + k +- k2 )- 1)[ 1 - ( 1 +k -1
*)(
-
1 - -$+k-'3
(1)
'a+k-2R where x is the thickness of the film,pm; R the electron range, pm; a the Everhardt coefficient; and k the diffusion term. For very thin films, the following linear approximation can be made: d x ) = (a + k ) ( x / R )
(2)
The Everhardt coefficient a is given by a = 0.024F/A
(3)
with 2 and A respectively the mean atomic number and the mean atomic mass of the film, calculated using atomic concentrations. The electron range R in micrometers is given by the relation
R = 0.033(A/Zp)E01.65
(4)
The diffusion term, k , can be calculated as follows. The backscatter contribution due to diffusion for an infinitely thick sample can be written as
0003-2700/87/0359-0930$01.50/00 1987 American Chemical Society
ANALYTICAL CHEMISTRY, VOL. 59, NO. 7, APRIL 1, 1987
i
(&)
(1
-In
pn-2
I
+ 1.44yd2)lI2- 1 + 0.36yd2 0.6yd
931
0"-1
2
where Yd is the reduced diffusion depth, given by Yd
qdmcan
= 40/72
(6)
also be expressed in terms of the diffusion coefficient
k:
since qd.. can be calculated for any given mean atomic number from eq 5 and 6, k(Z) can be obtained by solving eq 7. To avoid the repeated numerical solution of this equation, was expressed as a least-squares polynomial of the form
k(a
k(2) = -0.2137
+ 0.051082 - (7.499 X 10-4)Z2+ - (1.800 X 10-*)Z4 (8)
(5.807 X
The relative error of this approximation is smaller than 2% for 2 higher than 10. Equations 7 and 8 are valid for unsupported thin films only. In many practical situations, however, the films are supported with a flat substrate of known composition and infinite thickness. The influence of such substrates on the backscatter coefficient decreases with film thickness. Reuter (5) mathematically described this effect as a loss of transmission of the backscattered electrons from the substrate through the thin film. He used the following expression: q ( x ) = qse-upx
+ qF(l -
e-'px)
(9)
in which x is expressed in centimeters and where qs and qF are respectively the backscatter coefficients of the substrate and the film material. u is defined as u
= (4.5 x 105)~o-1.65
(10)
where Eo is expressed in kiloelectronvolts. In this work the second term of eq 9 was substituted by the thin-film term of Niedrig's eq 1 or eq 2 q(x)
=
qse-OPx
+ q(x/R)
(11)
thus utilizing both backscattering from the thin film and from the substrate. Monte Carlo Simulations. In the Monte Carlo electron trajectory simulation, the path of an individual electron is calculated in a stepwise manner through the solid as the electron is subject to elastic and inelastic scattering. The distance between scattering events, the scattering angles, and the amount of energy loss are calculated from realistic physical models. Random numbers are used to distribute the choices for these parameters over their respective ranges so as to accurately represent the relative probabilities for each process. Because of the large number of possible choices for the parameters, a large number of trajectories need to be calculated in order to obtain statistically valid results. The details of the Monte Carlo electron trajectory simulation methods can be found in the literature (14). Each electron trajectory is constructed from a number of subsequent scattering steps originating from the point where the electron beam hits the surface of the solid. The calculation of a trajectory is terminated when the electron has lost all its energy (absorbed electron) or has emerged from the solid (backscattered electron). The fundamental repetitive calculational element of the Monte Carlo simulation (corresponding to a single scattering
pn Flgure 1. Simulation of a single scattering event in a Monte Carlo electron trajectory calculation.
event) is illustrated in Figure 1. In taking the electron from point PN to point PN+l, the step length S, a scattering angle 4, and an azimuthal angle $ need to be calculated. The step length S and the scattering angle 4 are calculated on the basis of elastic scattering only since inelastic scattering is only responsible for slight angular deviations. The total relativistic Rutherford scattering cross section is used to model elastic scattering: E moc2 2 uE = (5.21 X lo-")( 4T (12) a(a + 1) E 2moc2
(
$y
+ +
)
where UE is the total scattering cross section (in cm2),E is the electron energy (in keV), and a is a screening factor given by Bishop (151,
The following expression for the scattering angle 4 can be obtained from eq 12: cos 4 = 1 -
2aR
1+a-R
where R represents a uniformly distributed random number (0 5 R 5 1). The step length S is taken from a logarithmic distribution around the mean free path h
S = -A In (IRI)
(15)
while X can be obtained from the total scattering cross section using
in which N Ais the Avogadro number and p the density of the solid. Since the azimuthal angle $ is uniformly distributed between Oo and 360°,it can be calculated according to
+ = 2xR
(17)
The energy loss along the trajectory is calculated by taking the segment length S multiplied by the rate of energy loss with distance traveled dEldS, given by the Bethe relation
AE = S ( d E / d S ) with
(18)
932
ANALYTICAL CHEMISTRY, VOL. 59, NO. 7, APRIL 1, 1987
where the mean ionization potential J can be calculated by using the Berger-Seltzer equation (161,
J = 9.672
+ 58.52-0.19 (eV)
/'
nt
I
(20)
The backscatter coefficient q of a solid can be calculated by simply dividing the number of backscattered electron n, by the total number of calculated trajectories TIT: 7 = n,/nT
(21)
Other physical properties, such as, e.g., the transmission coefficient VT (in case of thin films) or the radial distribution (dn,/dw) of the backscattered (and transmitted) electrons can also be obtained. The program, which is currently implemented on a VAX 11/780, under the VMS operating system, can simulate different experimental setups: (a) electron scattering in bulk samples; (b) scattering in unsupported thin films; (c) scattering in supported thin films (e.g., a gold layer on a carbon substrate). Due to its molecular structure, the program can easily be modified to simulate scattering in other geometric arrangements, e.g., in spherical particles. For a simulation, involving the calculation of 100oOelectron trajectories in a bulk sample, about 20 min of CPU time are required. EXPERIMENTAL SECTION Instrumentation. The measurements were performed on a JEOL JXCA 733 electron probe microanalyser equipped with different electron detectors and an energy dispersive X-ray detection. An annular solid-state (surface barrier) detector is installed under the objective lens. Electron and X-ray detectors as well as the sample stage and the electron beam control are integrated in a TN 2000 periphery, allowing completely automated operation of the instrument with an LSI 11/23 computer. A software package for automated particle measurements was developed in the laboratory (17)and contains routines for energy dispersive and wavelength dispersive X-ray spectrum acquisition, automated particle characterization, and image processing. Results are stored on a dual double density diskette and on magnetic tape, but data can also be transferred to a VAX 11/780 minicomputer for further off-line data processing, e.g., for the application of multivariate statistics with the data processing package (DPP) (18) or for plotting of the results. Measurement of the Electron Backscatter Coefficient. The electron backscatter coefficient, q, for an infinitely large, flat sample is defined as the number of electrons leaving the surface in the backward direction divided by the number of electrons impinging on the surface. Measurement of the backscatter current over this full 277 geometry requires the use of a Faraday cage in which the entire sample is mounted (19),a measurement condition which is not readily available on most instruments. Further, it is not suitable for automated measurements as described in this article, because of the slow response time of the Faraday cage and the small currents involved. As an alternative, one could use the electron current absorbed by the specimen to measure the backscatter coefficient. Experience, however, has taught that this approach does not produce a reliable estimate of the backscatter coefficient in the case of carbon-coated, nonconducting samples. In the experiments described, the backscattered electrons were measured with the aid of a solid-state annular detector mounted approximately 11 mm above the sample surface and the solid angle of detection is ca. 1.5sterradials. Due to this experimental setup, the measurements of the backscattered electron current are not absolute and a suitable calibration procedure had to be established. Furthermore, errors might be introduced because of the anisotropy in the backscattering of electrons from thin films. Calibration of the Backscattered Electron Detector. In our experimental setup, the signal from the annular backscatter electron detector is amplified by a JEOL 733 BSE current amplifier and digitized with a resolution of 8 bits by the TRACOR TN-2000 computer system. The reading of this BSE current (in the range 0-255) depends on the contrast and the brightness
I
n l
Figure 2. Calibration curves converting backscattered electron intensities into q values, for three different electron beam energies. setting of the amplifier and on the efficiency of the solid-state detector. In order to relate the BSE current, ZBs, to the backscatter coefficient, q, the system was calibrated by using polished thick targets of the following metals: Mg, Al, Si, Ti, Cr, Fe, Ni, Cu, Zr, Mo, Cd, W, and Au. Figure 2 shows the relation between the experimentally observed BSE signal and the backscatter coefficient, the latter taken from the literature (20),for a fixed setting of the contrast and the brightness of the amplifier, an incident primary current, lo,of 1nA, and a primary electron energy of 15, 20, and 30 keV. The experimental points in this figure can be described by a linear relation of the form tlexp
= ao + ~ J B S
(22)
where the intercept, uo, for a given calibration curve depends on the contrast setting and the slope, al,depends on the brightness setting and on the primary (actually backscattered) electron energy. In practice, rather than establishing a. and a, for each experimental run, it was found more convenient to adjust the brightness and contrast setting of the amplifier so that the BSE signals of Mg and Fe were equal to the values of the calibration curve established once under standard conditions for a primary electron beam of 20 kV and 1 nA. RESULTS Comparison of Theory and Experiment. The validity of the Niedrig equation (eq 1) and of its linearized form (eq 2) for thin unsupported samples was tested by comparison with Monte Carlo (MC) simulation of the industrially important case of AgBr. Simulations of 30 000 electron trajectories were performed for AgBr thin films at different initial electron energies. The backscatter coefficients obtained by the simulations at different thicknesses are compared with the values calculated by eq 1 in Figure 3 for an incident electron energy of 10, 15, 20, and 25 keV. The best agreement is obtained for an electron energy of 20 kV. For higher energies the results of the simulation are systematically lower than the calculated values. In the low thickness region the data obtained with both approaches differ somewhat. The MC tend to follow an S-shaped curve with an inflection point whereas the Niedrig curve shows a monotoneously decreasing first derivative over the full thickness range. This effect can also be seen in the experimental results published by Niedrig (6, 19). A comparison was further made between the results of simulation of backscattering in a supported thin film and the theoretical model of Niedrig-Reuter (eq 11). Up to 30 000 electron trajectories were simulated in carbon-supported foils of Al, Cu, and Au for electrons with an initial energy of 20 kV. Figure 4 compares the results of the
ANALYTICAL CHEMISTRY, VOL. 59, NO. 7, APRIL 1, 1987
determined backscatter coefficient for PET-supported AgBr-films are compared with the results of Monte Carlo calculations for carbon-supported AgBr films at 20 keV. Considering the long calculation times of the MC program, only the values for 20 kV were simulated. Experimental results and MC values show a fair agreement in the thickness range below 300 nm. Since the electron penetration range R, as calculated from eq 4, for AgBr at 20 kV is 1.6 Fm, the experimental points can be approximated by the linear equation within 10% error. We can conclude that the linearly approximated NiedrigReuter model for supported thin films can be used to calculate the film thickness in the range 0 Ix IR/3. Automated Thickness Determination. Analysis Procedure. From the discussion above we can assume that the combined Niedrig-Reuter approach can be used for thickness measurements of thin films and by extension also for the determination of the thickness of thin laminary-shaped particles supported by a flat low 2 substrate. Provided the composition of the particles is known and the particle is sufficiently thin to apply the Niedrig linear approximation
10 keV a
0
20 keV
01
02
933
03 x ( p m )
Figure 3. Monte Carlo results for the BSE coefficients of thln unsupported films with a plot of the Niedrig model according to eq 1.
a+k veXp= rl,e-upx + X
R
I
I
the thickness x can be determined by solving this equation iteratively. The initial estimate x o is obtained from xo =
vexp
-R a+k
while successive approximations of the thickness are obtained by using
01
0
1
05
1
x(pm)
Figure 4. Backscattered electron coefficient for thin carbon-supported foils of AI, Cu, and Au (dots) calculated by MC simulations, compared with the Niedrig-Reuter eq 11.
MC calculations with those obtained by using the model with eq 11. In the thin-film range there is a fair agreement between both methods for A1 and Cu but for Au the slopes differ significantly. For large thicknesses the plateau values of 7 obtained with the Niedrig model differ significantly from those obtained by the MC simulation. The calculated values approach the bulk 7 values as published by Bishop (20): Al, 0.164; Cu, 0.325; Au, 0.507. The discrepancy of 10-20% between the results of the MC simulation and the values from the literature was attributed to the simplicity of the model which does not account for deflection of the electrons due to inelastic scattering. To compare the theoretical calculations with experimental results, AgBr films were prepared by evaporation under vacuum on 100-km-thickpoly(ethy1ene terephthalate) (PET) substrates. AgBr films with thicknesses of 35,50,70,100,150, 200, and 300 nm were prepared. The thickness of the AgBr film was monitored with a piezoelectric quartz crystal device. The sample preparation was done at Agfa-Gevaert, Belgium. Figure 5 compares the experimental BSE coefficients with the plot obtained from the Niedrig-Reuter eq 11and its linear approximation for the AgBr films at four different electron energies. Taking into account the scatter in the experimental results, it appears that theory and experiment agree to within 10% for electron energies above 15 kV. The experimentally
The first estimate x,-, is not corrected for the backscattering of the support material v8and thus provides an overestimated thickness. A stable thickness value is usually obtained after four iterations. A variable composition of the individual particles excludes a priori knowledge of the concentration of the elements present. Since the parameters a , k , R, u, and p, used in the above equation, are strongly dependent on the sample composition, quantitative analysis should be performed on each particle together with the thickness determination. This quantitative analysis procedure is based on a standardless ZAF method published by Wernisch (21), as modified for thin particles. The method allows the inclusion of the concentration of unmeasured (low 2)elements and the calculation of the concentration by oxide stoichiometry. Details of the method will be published elsewhere. In the iterative procedure, initial values for 2,A , and p are calculated from the observed K a or La X-ray intensities, I j , according to
t lj
With these values a thickness estimate of the particle is made, as described above. By use of this thickness, the particle ZAF correction procedure is applied to calculate the concentrations
934
ANALYTICAL CHEMISTRY, VOL. 59, NO. 7, APRIL 1, 1987
I
1
/ '
I
,/'
I
/
1 CI
02
33
x
WJm)
7 32
315
31
J
Figure 5. Niedrig-Reuter
3'
02
03
x (,rm)
model and its linear approximation for PET-supported AgBr films, with experimental results at different electron energies.
of the elements. From this concentration, the mean atomic number, the mean atomic mass, and the mean density are calculated as in eq 26 to 28, by substituting I j with the concentration and recalculating the thickness. This cycle is repeated until the difference in two thickness determinations is less than 1% . For binary compounds only two or three iterations are needed, but for more complex samples, especially when the thickness influences the ZAF correction factors profoundly, up to 10 iterations may be required. Experimental Verification for Particles. Thin AgBr particles were dispersed on a smooth PET foil and coated with 40 nm of carbon. A second coating, a few nanometers of Pd, was shadowed on the sample under an angle of 18.5". First, an automated analysis was run, followed by a thickness determination according to the iterative procedure using the linear Niedrig-Reuter equation. Afterward, the thickness was calculated by dividing the shadow length by a factor of 3. Since AgBr microcrystals have very straight edges, a sharp shadow line was obtained on the P E T foil and only the resolution of the secondary electron image causes an experimental error of 20 nm. The results are shown in Figure 6. The regression line approximates the 1:l slope and the scatter is limited to a level below 25 nm. A limiting factor, however, is the particle diameter. Indeed, during measurement of the BSE intensity, severe scattering of electrons near the boundary of the particles occurs, which leads, e.g., for a line scan, to profiles with smooth edges instead of a discontinuous step function. The magnitude of this effect depends on the composition of the particles and
C
01
02
Xm(wl;
Figure 6. Comparison between the thickness of laminar AgBr particles as determined by the method described in this paper (xNR)and by a shadowing method (xSH).
on the nature of the substrate material. Roughly, we estimated from available data that the aspect ratio of the particles (mean diameter divided by thickness) should be higher than 3 to decrease this effect to within the experimental errors. Automated Measurements. Automated EPMA operation for particle analysis has been described by Lee et al. (22),Kelly et al. (231, and Raeymaekers et al. (8). Our own software package (17),which was developed on the Tracor T N 2000
ANALYTICAL CHEMISTRY. VOL. 59. NO. 7, APRIL 1. 1987
7. secondaw eleclmn inage (SEI) of a few A@$ miooaystah.
system, was found to produce faster and more reliable results in comparison with the original particle recognition and characterization (PRC)software (Tracor Northern).
I
-
935
In this work the backscattered electron image is used to localize the particles. The backscatter signal is calibrated as described above, and a threshold is carefully set to allow the software to discriminate between the particles and the substrate. The computer-controlled analysis of the particles is divided into three steps: 1. The electron beam scans over the sample, using a raster of loo0 by 750, and locations with a backscatter signal above the preset threshold are stored in memory. When the contour of such an object is found to be closed, the object is considered completely recognized. From the stored coordinates of the contour, the area, the perimeter, the equivalent diameter, and the shape factor are calculated. During the localization the mean backscattered electron signal, averaged over all pixels belonging to the object, is registered. 2. In the second step an energy-dispersive X-ray spectrum of the object is acquired. During a preset acquisition time, the electron beam is positioned on the two-dimensional gravity center of the object or the electron beam is rastered over the object surface by using a raster or a star scan. The obtained
AgBr-Emulsion 1
n
I
I
AgT
Emulsion 2
L
DIAMETER Ipml
THICKNESS Ipml
$1
THICKNESSlpn
L 4 3.00
*
. ..... .
THICKNESS Iml
Flgure 8. Resuns of the characterization of two different AgBr emuisbns.
.
....
936
ANALYTICAL CHEMISTRY, VOL. 59. NO. 7. APRIL 1. 1987
spectnvn is deconvoluted with a fast derivative algorithm (H), Table I. Evolution of Particle Thickness and Composition and position and area of the X-ray lines are obtained. for Some Individual Particles (A125Zn75 Sample) 3. The information gathered in steps 1 and 2 is written to particle the background memory for later off-line processing. Step no./iterstion concn AI, concn Zn, 1 is repeated to localize more particles in the image field. If no. atom 90 atom ?IO thickness, nm one field is exhausted, a new field is automatically selected by moving the sample stage in the x- and y-directions. 0.564 0.1996 0.436 111 0.560 0.2294 0.439 T h e system needs about 0.5 s to measure the average 112 0.2307 0.560 0.440 113 backscatter signal and to calculate the size and shape infor0.4428 0.562 0.438 211 mation for one particle. Taking into account the time spent 0.5258 0.553 0.447 212 in searching for the particle in a field and in changing from 0.552 0.5330 0.448 213 one field to another, loo0 particles can be analyzed in less than 0.301 0.2543 0.699 311 1 h if on the average there are 60 particles in a field. If an 0.298 0.3033 0.702 312 0.3055 0.298 0.702 X-ray spectrum must be acquired, as is the case when the 313 composition of the material is unknown and varies from particle to particle, the total analysis time increases considerably. With a spectrum acquisition time of 20 s per particle, approximately 5 h are required to analyze loo0 particles. Before insertion in the electron microprobe, the samples are coated with a carbon layer of about 30 nm. to prevent any charge buildup.
APPLICATIONS The following two examples give a clear new of the potential of the developed method. The first example is on a material with a fixed composition. In the second, both composition and thickness vary from particle to particle. L a m i n a r Particles w i t h C o n s t a n t Composition. A typical example of this particle type is obtained for microcrystalline AgBr. The particles are flat laminar with triangular or hexagonal shape. Figure 7 shows a typical electron micrograph. T h e thickness distribution of such AgBr grains is a n important factor for the sensitivity of photographic emulsions and also for the economic use of silver in photographic film. Samples of these microcrystals were dispersed onto 100-rrm-thick PET foils on which the laminae appeared to be perfectly horizontally positioned and were measured with an electron beam energy of 20 kV at a current of less than 0.5 nA. During the measurement, it was ensured that the electron beam did not remain unnecessarily long on the particles and that the primary electron beam current was as low as possible in order to limit damage to the particles. The results of a three-dimensional characterization of two collections of AgBr particles are given in Figure 8 as an example. For both emulsions, the size distribution of the equivalent diameter and the thickness are shown together with a plot of thickness vs. area. The latter give a clear representation of the three-dimensional appearance of each of the individual particles. L a m i n a r P a r t i c l e s with a Variable Composition. In this case both composition and thickness are unknown parameters. T h e initial thickness is calculated for Z, A , and p, estimated on the basis of the X-ray intensities instead of the concentrations. Next, a standardless ZAF correction procedure calculates a first set of concentrations and the procedure is applied iteratively as described earlier in this text. For binary compounds only two or three cycles are needed, but for more complex samples the thickness influences the ZAF correction factors more profoundly, and the process requires more iterations. T h e results of a study of microscopic particles produced in the vacuum sparking process of an AI-Zn alloy (25% AI) in a spark source mass spectrometer are used to illustrate the methodology. Flat disk-shaped particles with different compositions were released during a sparking process in vacuum within the sample chamber of a JEOL JMS-01-BM2 spark source mass spectrometer. The sparks were generated by a 1-MHz rf signal
2
I b
'si
c 'M 53
c
2 oatme i p i
Figure 9. (a)Secondary ekchon image of an AlZn particle (60' tin). (b) The Same particle in the backscattered electron Image. (c) A linsscan p o r n OVBT me mrtide (whne line in ibr of me backscattered
electron intensty.
of 45 kV with a breakdown voltage of 32 kV. The particles were collected on a graphite substrate at IO-mm distance from the electrodes. Graphite was selected as sample substrate because this material did not produce interfering characteristic X-rays under electron bombardment. Table I illustrates the convergent nature of the calculations on this binary alloy. The result of the measurement of a large collection of particles is a multivariate set of concentrations of the detected elements (here AI and Zn) and the thickness and the diameter (or the area) of each of the particles. In this example, these appear as more or less circular disks (Figure 9). The thickness cannot be calculated reliably from the BSE intensity but must take into account the variable sample composition. Figure 10 shows a plot of thickness M. diameter and the aluminium concentration as a function of the particle volume. Detailed measurements on single particles agreed
ANALYTICAL CHEMISTRY, VOL. 59, NO. 7, APRIL 1, 1987
velopment of the electron microprobe automation software. We also are indebted to Agfa-Gevaert N.V.-Belgium for the manufacturing of all AgBr test samples. This work was supported by the National Ministry of Science Policy, Belgium, through Concerted Research Action 80-851 10, and by the Belgium National Science Foundation through financial support to K.J. and P.V.E. Registry No. AgBr, 7785-23-1; Al,,Zn,,, 12721-42-5.
z
2 0.600 2 c Y z
Y
937
0.1100
u 0
-
LITERATURE CITED
4
t
0.200
0.
20.0
0.
60.0
‘40.0
80. 0
VOLUME lPm3 I
(1) Marshall, D.; Hall, T. J . Phys. D 1988, 7 , 19. (2) Soum, G.; Arnell, F.; Balladore, J.; Jouffrey, B.; Verdier, P. Ukamicroscopy 1979, 4 , 451-466. (3) Newbury, D.; Myklebust, R. Ultramicroscopy 1979, 3, 391-395. (4) Fathers, D.; Rez, P. Scanning Electron Microsc. 1979, 55-66. (5) Reuter, W. Proc. X-ray Eiectron Opt. Microanal., 6th 1972, 121-130. (6) Niedrig, H. Scanning Electron Microsc. 1981, 29-45. (7) Markowlcz, A.; Raeymaekers. B.; Van Grieken, R.; Adams, F. I n (8)
(9) (10) 8
* *
0.u00-
E.,,.
#*.
(11) (12) (13)
R
(14)
.
0.200I
2.00
u.00
6.00
8.00
VOLUME l p r n 3 1
Flgure 10. Results of the characterization of the ACZn mlcroparticles.
within 10% with the results of this procedure, although the entire set of data on 500 particles was obtained in less than 6 h of electron probe operation time including an X-ray spectrum acquisition time per particle of 20 s. Data transfer and processing was achieved in less than 1 h.
ACKNOWLEDGMENT We are grateful to A. Markowicz for valuable advice on the ZAF correction calculations and to H. Nullens for the de-
(15) (16) (17) (18) (19) (20) (21) (22) (23)
Physical and Chemical Characterization of Single Pariicles ; Spurny, K.. Ed.; Ellis Horwood: Chichester, U.K., 1986; pp 173-195. Raeymaekers, B.; Van Espen, P.; Adams, F. Mikrochim. Acta 1984, 2, 437-454. Linders. P.; Hagemann, P. Ultramicroscopy 1983, 1 7 , 13-20. Linders, P.; Stols, A.; van de Vorstenbosch, R.; Stadhouders, A. Scanning Electron Microsc. 1982, 1603-1615. Everhardt, T. J . Appl. Phys. 1980, 37, 1483-1490. Archard, G. J . Appl. Phys. 1981, 32, 1505-1509. Thummel, H. Durchgang von Elektronen und Betastrahlen durch Materieschichten; Acadernie Verlag: Berlin, 1974. Heinrich, K. F. J.; Newbury, D. E.; Yakowitz, H. NBS Spec. Pubi. (U. S.) 1976, No. 460, 42. Bishop, H. E. NBS Spec. Pubi. (U. S . ) 1978, No. 460, 5. Berger, M. J.; Seltzer, S.M. National Academy of Science, Publ. 1133, Washington, DC, 1964, Chapter 10. Nullens, H. Unpubllshed software, developed at UIA Chemistry Department, Antwerp University, 1986. Van Espen. P. Anal. Chim. Acta 1984, 765, 31-49. Niedrig, H. Scanning Electron Microsc. 1978, 17-33. Bishop, H. I n Optique des Rayons X et Microanalyse; Castaign, R., Descamps, P., Philibert, J., Eds.; Herman: Paris, 1966. Wernisch, J. X-ray Spectrom. 1985, 1 4 , 109-119. Lee, R.; Kelly, J. Scanning Nectron Microsc. 1980, 302-310. Kelly, J.; Lee, R.; Lentz, S. Scanning Nectron Microsc. 1980,
311-322. (24) Den Harder, A., De Galan, L. Anal. Chem. 1974, 4 6 , 1464-1473.
RECEIVED for review July 15, 1986. Accepted November 24, 1986.
