Experimental Data and Model Simulations of Beam Spread in the Environmental Scanning Electron Microscope

Transcription

1 SCANNING VOL. 23, (21) Received: November 11, 2 FAMS, Inc. Accepted: January 22, 21 Data and Simulations of Beam Spread in the Environmental Scanning Electron Microscope SCOTT A. WIGHT Surface and Microanalysis Science Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA Summary: This work describes the comparison of experimental measurements of electron beam spread in the environmental scanning electron microscope with model predictions. Beam spreading is the result of primary electrons being scattered out of the focused beam by interaction with gas molecules in the low-vacuum specimen chamber. The scattered electrons form a skirt of electrons around the central probe. The intensity of the skirt depends on gas pressure in the chamber, beam-gas path length, beam energy, and gas composition. A model has been independently developed that, under a given set of conditions, predicts the radial intensity distribution of the scattered electrons. measurements of the intensity of the beam skirt were made under controlled conditions for comparison with model predictions of beam skirting. The model predicts the trends observed in the experimentally determined scattering intensities; however, there does appear to be a systematic deviation from the experimental measurements. Key words: environmental scanning electron microscope, electron microscope, beam spread, electron scattering, skirt, Monte Carlo, model, simulation PACS: s, 14.6.Cd, Ew, x, d Introduction Conventional scanning electron microscopes (SEM) require a high vacuum [1-3 Pa (1-5 Torr)] sample chamber. This high-vacuum requirement places restrictions on the specimens that can be investigated in conventional SEMs. Specimens should be clean, dry, and free of volatile species that would out-gas in the high vacuum of the chamber and contaminate the specimen chamber and column. Insulating or only partially conductive specimens often need to be Address for reprints: Scott A. Wight National Institute of Standards and Technology 1 Bureau Dr STOP 8371 Gaithersburg, MD , USA scott.wight@nist.gov coated with a conductive layer of carbon or a metal to drain excess charge away and reduce surface charging. Environmental scanning electron microscopes (ESEM) and the other low-vacuum [ Pa (1 1 Torr)] scanning electron microscopes (LVSEM) do not have these restrictive specimen limitations. In fact, live cells, wet materials, oily filters, and liquids are frequently not an obstacle for these instruments. The environment inside the specimen chamber during operation consists of low-energy secondary electrons, gas molecules, and ions that have the added benefit of helping to drain the excess surface charge away. The need for conductive coatings is therefore reduced or eliminated for specimens investigated in the ESEM or LVSEM. Dynamic experiments such as hydration, dehydration, melting, solidification, dissolution, and chemical reactions are often directly observable in these microscopes. Electrons scattered out of the primary electron beam are a consequence of the high-volume density of gas molecules in the ESEM and LVSEM. In contrast, the high-vacuum SEM specimen chamber has very few gas molecules in it by design. Gas scattering of electrons is not an issue in the conventional SEM but must be considered in the ESEM and LVSEM. For the case of imaging with backscattered or secondary electrons, the skirt electrons contribute a nonspecific signal that acts to increase the noise and degrade the signal-to-noise ratio. Danilatos (1988) has demonstrated that as long as there remains even a small fraction of the total electron current in the focused probe, high spatial resolution images remain possible, provided a sufficient dwell time is used to compensate for the decreased signal-tonoise. Gas-scattered electrons create a problem for microanalysis when they generate x-rays from a nearby material that is different in composition from the material of interest under the primary beam. A chemical characterization problem arises when those x-rays reach the detector and are attributed to the material under the primary electron beam. Several researchers (Bache et al. 1997; Bolon 1991; Danilatos 1988; Doehne and Bower 1993; Gilpin and Sigee 1995; Griffin 1992; Griffin and Nockolds 1996; Griffin et al. 1993, 1994, 1995; Wight et al. 1997) have studied and reported on the experimental measurements of electron scattering in the gaseous environment of the ESEM. The early work was either done at much longer working distances, because of the design of the early

2 S. A. Wight: ESEM model vs. experimental beam spread 321 ESEM, or the working distance was not reported. The subsequent development of the long working distance detector (LWDD) has reduced the scattering by reducing the electron path through the gas, which is achieved by extending the final pressure-limiting aperture into the chamber to provide the longer working distance necessary to accommodate an energy-dispersive spectrometer (EDS). An accurate model of the primary electron beam scatter in ESEM or LVSEM would enable researchers to predict the magnitude of the scattered electron skirt. This knowledge is important to the understanding of the analytical spatial resolution of EDS in an ESEM or LVSEM. Ideally, the model would predict the optimum conditions to reduce scattering for a given analytical system. Alternatively, it could be used to develop a correction to the analytical data that reduces the effect of the scattered electrongenerated x-rays from the spectra. Joy (1996) has developed a model that predicts the electron scattering in the chamber before the primary electron beam interacts with the specimen; thus, it is useful for modeling scattering under ESEM and LVSEM conditions. data on the extent of the skirt as a function of ESEM parameters are needed to test the validity of these models. This study makes use of x-ray measurements on test structures to make a comparison with the Joy model. Collecting experimental scattering data in the ESEM for comparison with model simulations requires careful attention to all the instrument details. The scattering model is simplified and therefore has a limited set of variables to consider, whereas the ESEM has many more adjustments that can be made. It is therefore necessary to complete an entire series of measurements sequentially to reduce the chance of instrumental changes affecting the results. This work employs an Electroscan ESEM 22 with LWDD, with a sample to final aperture distance or beamgas path length (BGPL) of 2 mm, and a chisel-nose-lookdown (Kevex Quantum, ThermoNoran, Middleton, Wisc., USA) EDS detector. 1 Instrument starting parameters can be found in Table I. When the variable being measured is one of the starting parameters such as accelerating voltage all the other parameters are held constant. The accelerating voltage is then returned to 2 kv to measure the effect of varying a different parameter, such as chamber pressure. This study is limited to primary effects for the purpose of comparing simulated and experimental data. Instrument parameters such as filament heat, focus, stigmation, and 1 Certain commercial software, equipment, instruments, or materials are identified in this report to specify adequately the experimental procedure. Such identification does not imply recommendation or endorsement by the National Institute of Standards and Technology, nor does it imply that the materials or equipment identified are necessarily the best available for the purpose. image shift are not recorded here as they are instrument specific. All parameters are held constant for the series of measurements once the column is adjusted for best resolution at the beginning of the exercise. A 1 cm square block of high purity copper was chosen as the test structure. It was cleaned and mounted in a 2.5 cm round nonconductive epoxy mount. The mount was final polished with 1/4 µm diamond grit and was not coated. The polished copper mount was loaded in the ESEM with a straight edge parallel to the detector. A path to ground was made with carbon tape from copper to the stage. Two different types of experimental data were measured for comparison with the results of the model predictions. The first experiment was designed to measure the skirt intensity as a function of distance. K-alpha x-ray intensities were determined as a function of distance from the copper edge. X-ray spectra were collected as the sample was moved under the stationary electron beam starting on the copper and moving toward the edge of the copper and off onto the epoxy. When the copper block is no longer under the primary electron beam, any detected copper x- ray intensity must be produced by scattered electrons. The beam striking the epoxy is nearly completely absorbed because the backscattering coefficient of the constituents, principally carbon, is very low. These data must be corrected for the change in the area of the skirt that falls on the copper as the primary beam moves away. The second experiment was a series of measurements designed to demonstrate trends in scattering intensity caused by changing instrument variables. Spectra were collected with the electron beam centered on the epoxy 2 µm off the edge of the copper as instrument parameters were individually changed. The number of scattered electrons was assumed proportional to the intensity of copper x-rays. Working distance, accelerating voltage, and chamber gas were varied individually to assess the impact of each of these on the scattering of electrons out of the beam. Electron scattering in a gas before reaching the specimen is a much different situation to model than the traditional Monte Carlo models for electron specimen interactions (Heinrich 1976). Traditional models predict secondary TABLE I Starting instrument parameters Parameter Value Accelerating voltage 2 kv Chamber pressure 266 Pa (2 Torr) Chamber gas Water vapor Beam-gas path length 2 mm Condenser 7% Projection aperture 5 µm Imaging mode BSED GSED voltage Minimum (28 VDC) EDS solid angle.51 sr Magnification 6, Abbreviations: GSED = gaseous secondary electron detector, EDS = energy dispersive spectrometer, BSED = backscattered electron detector.

3 322 Scanning Vol. 23, 5 (21) electron, backscattered electron, and x-ray generation and distributions in solids. Elastic scattering of the primary electron beam in a gas is described by the ESEM model of Joy (1996) incorporated in Electron Flight Simulator - E (Small World Inc., Vienna, Va., USA). This Monte Carlo model allows the user to input a sample-to-detector distance, accelerating voltage, gas composition, gas pressure, and the area over which the user would like the scattering calculated. The starting parameters for the model simulation are listed in Table II. Note that the parameters except voltage, gas, pressure, and working distance are held constant as they are representative of the instrument detector combination. Figure 1 is a schematic of the relationship between the specimen, LWDD, and the EDS detector. Simulations were run on the Electron Flight Simulator model with the same starting conditions as the experimental data collections, 2 kv accelerating voltage, 266 Pa (2 Torr) water vapor, and 2 mm BGPL (labeled working distance in the model). Each parameter was varied individually while the others were held constant. Theory and Data Manipulation TABLE II Starting model settings The model plots a visual display of electron trajectories and chooses a default plot width or distance over which the trajectories are displayed. The model also calculates and displays an overlay histogram of the radial intensity distribution (Fig. 2). Different scattering conditions will be displayed with different plot widths. Since the plot width is divided into 5 histogram bins, the different scattering conditions are not directly comparable because their histogram bins have different widths. All simulations are therefore rescaled to display 1 µm such that all histogram bins are the same width (2 µm). Exporting the bin data to a spreadsheet gives columns of bin limits and intensity percentages. The data are manipulated into a form that is comparable with experimental data by removing the normalization and then correcting for the fraction falling on the copper. The experiment where the copper block is moved under the beam and x-ray spectra are collected at regular intervals approximates the modeled situation. The model calculates a radial distribution by calculating the distance a scattered electron lands from the primary beam and decides in which of 5 evenly spaced bins it belongs. At the end of the simulation, the contents of the bins are divided by 2n+1 (where n is the bin number) to account for the difference in the area of the circular bins as the bins get farther from the primary electron beam. The result is an intensity distribution as a function of radius with no effect of size. The simulation determines a default plot width for the display that is dependent on the scattering conditions. This plot width is divided into the 5 equal size bins. Different conditions will generate different plots and consequently different bin widths. Care must be taken not to compare radial intensity distribution simulations that were not rescaled and recalculated at the same plot width. The model data are multiplied by 2n+1 (n = bin number) to remove the normalization that is applied by the software and then multiplied by the area correction fraction. The bins are summed for intensity percentage histograms >2 µm, and both model and experiment are plotted versus the variable on the same plot. A correction factor is calculated for the fraction of the area of the skirt that is not falling on the copper block. The problem is demonstrated in the schematic Figure 3, in which the + represents the primary beam 2 µm off the FIG. 1 Schematic shows the relationship between the parts inside the environmental scanning electron microscope chamber. A) Energy dispersive spectrometer detector, B) long working distance gaseous secondary electron detector, C) backscattered electron detector, D) specimen, and E) stage. Parameter Value Sample type ESEM Window type Quantum (.3 µm thick) Horizontal distance 1 mm Working distance 2 mm Detector (take-off) angle 3 degrees Azimuth angle 1 degrees Detector type EDS Accelerating voltage 2 kev Tilt degrees Trajectories 32, Gas Water Pressure 266 Pa. (2 Torr) Abbreviations as in Table I. FIG. 2 output display, conditions as listed in Table II. A 12 mm B C 19 mm 2 mm D E

4 S. A. Wight: ESEM model vs. experimental beam spread 323 copper edge. The concentric circles represent the 2 µm wide bins that the model uses to count electrons. The dark gray area represents the fraction of that annulus that is actually falling on the copper and therefore has the possibility of creating a copper x-ray. That fraction is calculated for each circular bin by calculating the area of each circle, then subtracting adjacent areas to get the area of each donut-shaped bin. The area falling on the copper (represented by the dark gray area in Fig. 3) is calculated using the formula for the area of a segment of a circle (CRC Handbook 1955) [ ] πr x Asegment = x r x + r Sin () 2 r r = radius, x = perpendicular distance and subtracting the previous segment to get the area in each circular bin that is on the copper. That area divided by the area of the corresponding entire circular bin yields the correction fraction for each bin. The results are displayed graphically in Figure 4. This plot, which approaches.5 asymptotically, confirms the observation above that less than half of the skirt could reach the copper if the beam is off the copper. A similar correction factor is calculated for the experimental data collected as a function of distance from the copper block. The area of a segment of a circle is calculated for each distance measurement and a correction is determined to account for the skirt that does not fall on the copper. The extent of the skirt is assumed to extend 5 µm when calculating the correction factor. This assumption is supported by x-ray data that fall off to near zero intensity at that distance. This approach represents a first order correction, since it takes care of the area factor between the experiment and a simple Monte Carlo. An improved approach would be to write a Monte Carlo routine that actually calculated the specific arrangement of target and beam. Results The experimental data collected as the beam was moved off the copper and onto the epoxy and the model output for the same conditions are compared in Figure 5a. The experimental data are corrected for geometry by dividing by the fraction falling on the copper. The data in the 2 µm region is of interest and is expanded in Figure 5b. Error bars for the experimental data are ± twice the square root of counts for each data point. Error bars for the model data are calculated for ± twice the square root of the number of simulated scattered electrons. Comparison of model and experiment as a single parameter is varied and will display trends in the data that should have the same slope and magnitude. To compare the trends, the data collection and manipulation are modified. The experimental data are collected with the beam 2 µm away from the copper edge such that only those electrons scattered 2 µm in that direction will strike the copper and generate copper x-rays. Background-subtracted, integrated copper K-alpha x-rays are measured as a function of the variation in a given parameter, such as chamber pressure. The intensities are converted to percentages of the counts collected when the beam is placed in the center of the copper. Chamber pressure data are plotted in Figure 6. calculations versus experimental results for the short sample-to-detector distances are plotted in Figure 7. Scattering is considerably greater for the large BGPL distances, such as 1 and 19 mm, with 29.5 and 5.9%, respectively, of the electrons scattered beyond 2 µm. The accelerating voltage applied to the primary electrons has an effect on the skirt intensity, as shown in Figure 8. To remove x-ray generation and absorption effects from the data, the spectra were collected twice for each voltage, in Radii (µm) Fraction falling on the copper , Annular radius (µm) 1,2 FIG. 3 Schematic representation of 2 µm wide bins with beam positioned 2 µm from the copper edge. FIG. 4 Correction factor for the fraction of the bin falling on the copper to be applied to the model histogram before comparison with the experimental copper x-ray data.

5 324 Scanning Vol. 23, 5 (21) Percentage scattered onto the copper (a) Distance (µm) 8 1, high-vacuum mode at each accelerating voltage. The vacuum was then set to 266 Pa (2 Torr) and the spectra were recollected for each accelerating voltage. Each of the low vacuum peak counts was divided by the high-vacuum peak counts for the same accelerating voltage. This canceled out the overvoltage effects on x-ray production and measured differences due to scattering. Another useful result is that the choice of chamber gas can significantly reduce the electron scattering. Figure 9 plots the experimental and model predictions of scattering in five different gases (argon, air, nitrogen, water, and helium). The data are normalized by dividing the number of counts resulting from each gas scattering by the number of counts collected on copper at high vacuum. This normalization is designed to remove the x-ray generation from the comparison such that the data for the gases represent rel- Percentage scattered onto the copper (b) Distance (µm) FIG. 5 (a) Comparison of model and corrected experimental scattering at 266 Pa (2 Torr) water vapor as a function of distance from the copper edge, 2 kv, 2 mm beam-gas path length. (b) Expanded portion of Figure 5a. Percentage scattered > 2 µm (5) 133 (1) 1995 (15) 266 (2) 3325 (25) Pressure, Pascal (Torr) FIG. 6 Comparison of measured x-rays and simulated electrons as a function of chamber pressure, 2 kv, water vapor, 2 mm beam-gas path length. Percentage scattered beyond 2 µm Percentage scattered > 2 µm Beam-gas path length (mm) FIG. 7 Comparison of measured x-rays and simulated electrons as a function of beam-gas path length, 2 kv, 266 Pa (2 Torr) water vapor Accelerating voltage (kv) FIG. 8 Comparison of measured x-rays and simulated electrons as a function of accelerating voltage, 266 Pa (2 Torr) water vapor, 2 mm beam-gas path length.

6 S. A. Wight: ESEM model vs. experimental beam spread 325 ative scattering. scattering results for six gases (nitrogen, air, argon, carbon dioxide, helium, and water) are plotted in Figure 1. The plot in Figure 1 is scattered percentage over the pressure range 62 to 133 Pa (.5 to 1 Torr) for 2 kv accelerating voltage and 2 mm BGPL. Discussion Percentage scattered > 2 µm FIG. 9 Comparison of measured x-rays and simulated electrons as a function of chamber gas, 2 kv, 266 Pa (2 Torr), 2 mm beam-gas path length. Scattered percentage Carbon dioxide Argon Nitrogen Air Water Helium Ar Air N 2 H 2 O He 266 (2) 532 (4) 798 (6) 164 (8) 133 (1) 1596 (12) Pressure, Pascal (Torr) FIG. 1 results for several gases as a function of pressure, 2 kv, 2 mm beam-gas path length. Guidelines for reducing the electron skirt intensity are available in previously published work (Bache et al. 1997; Doehne and Bower 1993; Gilpin and Sigee 1995; Griffin 1992; Griffin and Nockolds 1996; Griffin et al. 1993, 1994, 1995; Wight et al. 1997) and are reviewed here for completeness. Minimizing the distance the primary beam has to travel through the gas is the most effective improvement. Use of the LWDD can significantly cut down on the BGPL and is highly recommended. Similarly, lowering the chamber gas pressure reduces the number of gas molecules in the path of the beam. However, this may not be possible with wet specimens and may compromise charge neutralization of insulating specimens. Raising the accelerating voltage reduces scattering because the higher energy electrons have a small cross section for elastic scattering with the gas molecules. The last recommendation is to use a gas of lower atomic number to reduce the scattering power. Helium scatters much less than air, water, or argon (Stowe and Robinson 1998). However, pure helium has a high first ionization potential and may not be adequate for ESEM imaging. A few percent of methane added to helium may improve imaging conditions. These four simple tips, especially when used together, can significantly reduce the number of scattered electrons in the ESEM or LVSEM. Selection and preparation of the appropriate test specimen for the scattering experiments involves making some assumptions and decisions. Under scattering conditions in the ESEM, the primary beam is a small intense probe surrounded by a large low-intensity skirt simultaneously. The ideal imaging device is a high-resolution, electron-sensitive detector that has the dynamic range to measure the intense beam center and single electrons in the skirt simultaneously. Considering possible specimen geometry, it is decided that the simple binary system with a straight-line interface and both sides large relative to the skirt size is the most straightforward to deconvolute. is chosen as the material to embed in epoxy because it has both highand low-energy x-ray lines (Kα at 8.47 kev, Lα at.928 kev) and is readily available in high purity. This system is problematic to compare with model results because the farther the primary beam gets away from the copper, the less skirt area falls on the copper (Fig. 11). When the primary electron beam is well inside the copper, the entire skirt falls on the copper (Fig. 11a). When the beam falls on the interface between the copper and epoxy, exactly half of the scattered electrons fall on the copper (Fig. 11b). As the primary beam gets farther from the copper, a small change in primary beam location has a large effect on the skirt area that falls on the copper (Fig. 11c,d). Review of the plots of experimental measurements compared with model predictions demonstrates the strengths and weaknesses of the model for predicting this system. Good agreement exists between the two data sets as a function of distance in Figure 5a and b. It is difficult to draw significant conclusions about the model s performance since this comparison represents only one set of operating conditions. The chamber pressure data sets in Figure 6 agree on the magnitude of the trend but not within the error bars. This plot makes it easy to see why chamber pressure should be kept as low as possible for EDS analysis. There is a deviation between model and experiment above 655 Pa (5 Torr) which is possibly explained by multiple scattering events. Chamber pressure and BGPL (sometimes referred to as working distance) are closely related because they both affect how many molecules the electrons pass through before reaching the sample. The BGPL data

7 326 Scanning Vol. 23, 5 (21) in Figure 7 demonstrate a small effect and agree within the error. This may be because there is very little scattering at these short distances and the measurement error is high. The accelerating voltage data in Figure 8 agree very well with each other, indicating that the model handles the voltage component correctly. The gas data in Figure 9 show a deviation that widens with increasing molecular weight of the gas. During the experimental measurement, the only change is to admit different gases. Therefore, the data should be accurate relative to one another and may indicate a problem with the model. Problems with comparing electron distributions to generated x-ray measurements could artificially create a systematic deviation between the model and experiment. Choosing a gas and pressure for a particular experiment can be greatly simplified by modeling the gases that are available at the pressures routinely. Six gases (nitrogen, air, argon, carbon dioxide, helium, and water) are plotted with their scattered percentage over the pressure range 62 to 133 Pa (.5 to 1 Torr) in Figure 1. Calculations like this of frequently used conditions and gases can greatly simplify the gas selection process and guide understanding of experimental results. The uncertainty associated with the experimental data is depicted graphically in Figure 12. The two sets of data are repeated experimental measurements at the same instrumental conditions. Both sets of data have error bars added, Counts but they are hard to see because they are smaller than the data markers. The error bars represent the expected uncertainty and are ± twice the square root of counts for each measurement where the square root of counts is the standard deviation for Poisson-distributed counting data. The two data sets agree well, and the only significant deviation is with the beam on the copper and may be due to a contamination effect. The uncertainty in the model output is graphically demonstrated by the plot in Figure 13. Six repetitions of model simulations are calculated for the same starting conditions. They are graphed as a high-low plot, where the ends of each data point represent the highest and lowest data point and the horizontal tick marks represent where the other data points fall in between, to demonstrate the spread in the data that is possible. The low number of 25, 2, 15, 1, Primary beam Scattered skirt (a) 5, , Distance from edge (µm) FIG. 12 Repeated experimental measurements with error bars, 2 kv, 266 Pa (2 Torr) water vapor, 2 mm beam-gas path length. 1. (b).8 (c) Fraction (d) FIG. 11 Illustration demonstrating the overlap of the skirt with the binary system interface , Distance (µm) FIG. 13 High-low plot of six repeated model outputs of the same starting conditions, 2 kv, 266 Pa (2 Torr) water vapor, 2 mm beamgas path length.

8 S. A. Wight: ESEM model vs. experimental beam spread 327 electrons (maximum of 32,) run by the simulation results in more spread than we see in the experimental data. The largest variation is in the area where the slope is high and the sensitivity to distance is very high. Conclusion As a practical matter, the effect that the analyst must understand is the scattering of primary electrons some distance from the intended analysis spot that can produce x- rays from some other phase or material. A combination of modeling and experimental measurements of known systems will benefit ESEM and LVSEM operators by raising awareness of the potential for spectral contamination. Bolon (1991) reported that at 3 Torr (399 Pa), 45% of the primary beam was scattered more than 25 µm and at 5 Torr (665 Pa) it was 66% at a working distance of 15 mm. This work finds that those percentages can be reduced by a factor of two or greater by decreasing the BGPL to 2 mm. Scattering of electrons in the gas can be reduced even further by following the recommendations outlined in this paper. The model reasonably predicts the amount of electron scattering for given conditions but needs to run more than 32, trajectories. Problems of x-ray production and experimental geometry have to be considered when comparing the modeled electron distribution to the measured x-ray distribution. In experimental measurements, not all scattered electrons are going to strike the copper and produce x-rays, and not all x-rays are going to arrive at the EDS detector to be measured and recorded. Consequently, the model can be used as a guide or to determine the worst case scenario, but test measurements must be made under the experimental conditions to be sure there are no spurious contributions to the EDS spectrum. Ideally, the ESEM scattering model would take the next step and run the electrons that impinge on a multicomposition specimen through the x-ray generation model and predict the EDS spectrum. The two pieces exist independently but are not connected. Furthermore, measurements of scattered electron distributions that do not rely on x-ray production are more likely to elucidate any disparities between the model and the true electron distribution. Acknowledgment The author would like to thank Dale Newbury for many fruitful discussions. References Bache IC, Kitching S, Theil BL, Donald AM: Variations in the probe beam broadening with operating conditions in ESEM: Monte- Carlo simulations and EDX measurements. Microsc Microanal 3, (suppl 2) (1997) Bolon RB: X-ray microanalysis in the ESEM. Proc. 26th Annual Conference of the Microbeam Analysis Society, San Jose, Calif. Microbeam Anal, (1991) CRC Handbook of Chemistry and Physics. Chemical Rubber Publishing Company, 37 th Ed (1955) Danilatos GD: Foundations of environmental scanning electron microscopy. Adv Electronics Electr Phys 71, (1988) Doehne E, Bower NW: Empirical evaluations of the electron skirt in the environmental SEM: Implications for energy dispersive x- ray analysis. Proc. 27th Annual Microbeam Analysis Society, Los Angeles, Calif. Microbeam Anal, 2, S35 S36 (1993) Gilpin C, Sigee DC: X-ray microanalysis of wet biological specimens in the environmental scanning electron microscope. 1. Reduction of specimen distance under different atmospheric conditions. J Microsc, Pt. 1, 179, (1995) Griffin BJ: Effects of chamber resolution and accelerating voltage on x-ray resolution in the ESEM. Proc 5th Ann Mtg of EMSA, Boston, Mass (1992) Griffin BJ, Nockolds CE: Quantitative EDS analysis in the environmental scanning electron microscope (ESEM) using a Bremsstrahlung intensity-based correction for primary electron beam variation and scatter. Proc. Microscopy and Microanalysis, Minneapolis, Mn. Microsc Microanal (1996) Griffin BJ, Trautman RL, Coffey J: X-ray resolution at low chamber pressures and chamber gas fluorescence in the electroscan ESEM. Microbeam Anal 2, S37 S38 (1993) Griffin BJ, van Riessen A, Egerton-Warburton L, Hatch J, Trautman RL: A review of EDS x-ray microanalysis and element mapping in high pressure SEM (ESEM). Proc. 28th Annual Meeting of the Microbeam Analysis Society, New Orleans, La. Microbeam Anal, (1994) Griffin BJ, van Riessen A, Egerton-Warburton L: A review of qualitative and quantitative EDS x-ray microanalysis of hydrated and non-hydrated samples and associated imaging strategies. Microbeam Anal, (1995) Heinrich KFJ, Newbury DE,Yakowitz H (Eds.): Use of Monte Carlo Calculations in Electron Probe Microanalysis and Scanning Electron Microscopy. NBS Special Publication (1976) Joy DC: ing the electron-gas interaction in low-vacuum SEMs. Microsc Microanal, (1996) Stowe SJ, Robinson VNE: The use of helium gas to reduce beam scattering in high vapour pressure scanning electron microscopy applications. Scanning 2, 57 6 (1998) Wight SA, Gillen G, Herne T: Environmental SEM electron damage imaging of self assembled monolayers with SIMS. Microsc Microanal 3, (suppl 2) (1997)