Eric Lifshin

Win X-ray : A New Monte Carlo Program that Computes X-ray Spectra Obtained with a Scanning Electron Microscope

A new Monte Carlo program, Win X-ray, is presented that predicts X-ray spectra measured with an energy dispersive spectrometer (EDS) attached to a scanning electron microscope (SEM) operating between 10 and 40 keV. All the underlying equations of the Monte Carlo simulation model are included. By simulating X-ray spectra, it is possible to establish the optimum conditions to perform a specific analysis as well as establish detection limits or explore possible peak overlaps. Examples of simulations are also presented to demonstrate the utility of this new program. Although this article concentrates on the simulation of spectra obtained from what are considered conventional thick samples routinely explored by conventional microanalysis techniques, its real power will be in future refinements to address the analysis of sample classifications that include rough surfaces, fine structures, thin films, and inclined surfaces because many of these can be best characterized by Monte Carlo methods. The first step, however, is to develop, refine, and validate a viable Monte Carlo program for simulating spectra from conventional samples.

Development of a New Quantitative X-Ray Microanalysis Method for Electron Microscopy

Quantitative X-ray microanalysis of thick samples is usually performed by measuring the characteristic X-ray intensities of each element in a sample and in corresponding standards. The ratio of the measured intensities from the unknown material to that from the standard is related to the concentration using the ZAF or ϕ(ρz) equations. Under optimal conditions, accuracies approaching 1% are possible. However, all the experimental conditions must remain the same during the sample and standard measurements. This is not possible with cold field emission scanning electron microscopes (FE-SEMs) where beam current can fluctuate around 5% in its stable regime. Very little work has been done on variable beam current conditions (Griffin, B.J. & Nockolds, C.E., Scanning 13, 307-312, 1991), and none relating to cold FE-SEM applications. To address this issue, a new method was developed using a single spectral measurement. It is similar in approach to the Cliff-Lorimer method developed for the analytical transmission electron microscope. However, corrections are made for X rays generated from thick specimens using the ratio of the characteristic X-ray intensities of two elements in the same material. The proposed method utilizes the ratio of the intensity of a characteristic X-ray normalized by the sum of X-ray intensities of all the elements measured for the sample, which should also reduce the amplitude of error propagation. Uncertainties in the physical parameters of X-ray generation are corrected using a calibration factor that must be previously acquired or calculated. As an example, when this method was applied to the calculation of the composition of Au-Cu National Institute of Standards and Technology standards measured with a cold field emission source SEM, relative accuracies better than 5% were obtained.

Statistical Considerations in Microanalysis by Energy-Dispersive Spectrometry.

: X-ray counting statistics plays a key role in establishing confidence limits in composition determination by X-ray microanalysis. The process starts with measurements of intensity on one or more samples and standards as well as related background determinations. Since each individual measurement is subject to variability associated with counting statistics, it is necessary to combine all of the counting variability according to established mathematical procedures. The next step is to apply propagation of error calculations to equations for quantitative analysis and determine confidence limits in reported composition. Similar concepts can also be applied to trace element determination. This approach can then be combined with spectral simulation modeling, making it possible to predict detectability limits without additional measurements.

Microstructural and electrical characterization of gas cluster ion beam-smoothed YBCO films

The decrease in the critical current density (J/sub c/) of YBa/sub 2/Cu/sub 3/O/sub 7-x/ (YBCO) films with increasing film thickness was investigated for 0.2 - 2.4-/spl mu/m-thick films grown on single crystal substrates. Microstructural and electrical properties were characterized by focused ion beam (FIB) microscopy, X-ray diffraction, energy dispersive X-ray spectroscopy in a field emission scanning electron microscope, atomic force microscopy, and current-voltage measurements at 77 K in self-field. FIB cross sections directly showed that the top 30% -40% thickness of YBCO films contained pores, misoriented YBCO grains, and Ba-rich second phase particles that collectively produced a dead top layer which is believed to limit the J/sub c/ of YBCO films thicker than 1 /spl mu/m. A gas cluster ion beam etching and smoothing process partially removed the dead top layer and smoothed the film surface. In a 0.9-/spl mu/m-thick YBCO film, removal of a 0.22-/spl mu/m-thick dead layer yielded a 35% increase in J/sub c/ (up to 2.8 MA/cm/sup 2/) and a 25% decrease in film roughness. In a 1.3-/spl mu/m-thick YBCO film, removal of a 0.45-/spl mu/m-thick dead layer yielded an 85% increase in J/sub c/ (up to 1.1 MA/cm/sup 2/) and a 49% decrease in surface roughness. This study suggests that eliminating the dead top layer and smoothing the film surface might be key processing steps in the production of thick YBCO films with high J/sub c/.

Improving Scanning Electron Microscope Resolution for Near Planar Samples Through the Use of Image Restoration

A method is presented for determining the point spread function (PSF) of an electron beam in a scanning electron microscope for the examination of near planar samples. Once measured, PSFs can be used with two or more low-resolution images of a selected area to create a high-resolution reconstructed image of that area. As an example, a 4× improvement in resolution for images is demonstrated for a fine gold particle sample. Since thermionic source instruments have high beam currents associated with large probe sizes, use of this approach implies that high-resolution images can be produced rapidly if the probe diameter is less of a limiting factor. Additionally, very accurate determination of the PSFs can lead to a better understanding of instrument performance as exemplified by very accurate measurement of the beam shape and therefore the degree of astigmatism.

Measurement of the Electron Beam Point Spread Function (PSF) in a Scanning Electron Microscope (SEM)

A knowledge of the spatial distribution of the electron beam current density, often referred to as the point spread function (PSF), is valuable for understanding the behavior of scanning electron microscopes (SEM) and various other instruments. Previously, a number of attempts at PSF determination have been made based on experimental measurements or electron optical calculations [1-7]. Some of the experimental methods employed knife edge or other scans[1, 8]. Liddle et al. [5] used a TEM image of a reference sample to determine the PSF for an electron beam lithography tool. They assumed an elliptical Gaussian shape for the electron beam and determined its standard deviations in two orthogonal directions using an iterative method to match the reference and blurred images. Babbin et al. developed a test sample that can be used to estimate the PSF using a Fourier transform method[6]. All these approaches are limited in the sense that they do not provide the fine, often irregular, details in the electron beam shape that may not be symmetric or monotonic. A more accurate determination of a PSF is critical, however, if the goal is to improve SEM resolution by deconvolution using the method described by Lifshin et. al [9].

Scanning Electron Microscope Point Spread Function Determination Through the Use of Particle Dispersions

Over the years, significant advances have been made in scanning electron microscope (SEM) resolution primarily due to hardware improvements including higher brightness electron sources with smaller energy spreads and better electron optics that decrease the final probe size. Although these advancements represent significant developments, they commonly come with added complexity and cost. In addition, while a small probe diameter may be necessary for high resolution imaging, it may not be attainable in all instances, most notably low voltage where chromatic aberrations in the electron optics limit the minimum probe size. Other scenarios such as long working distance settings as with retractable backscatter detectors and other analytical operating conditions can lead to larger beams at the sample surface. Situations in which there is a need for a high signal to noise ratio can also present an issue as the probe size often increases with probe current leading to decreased resolution due to beam broadening.

Viability of Point Spread Function Deconvolution for SEM

An image is understood as the point spread function (PSF) of an imaging system convolved with the scene being imaged. An image can be restored to more accurately depict the scene by performing a deconvolution of the PSF and the image. In a scanning electron microscope (SEM), the PSF describes the shape of the electron beam. PSF deconvolution is a promising image restoration technique for SEM images [1] and is of special interest at low beam voltages (< 3kV), where resolution is hindered by multiple factors. This technique’s viability for SEM application is based on invariance of beam shape with respect to position and sample. Using Aura Workstation [2], we can determine the beam shape to test for invariance and perform restorations for image quality evaluation.

The Use of Regularized Least Squares Minimization for the Deconvolution of SEM Images

Major advances are currently taking place in image processing algorithm development. When combined with today’s high speed computers utilizing multicore processing and very large memories the door is opened to the practical application of regularization techniques to the restoration of SEM images with improved spatial resolution. It is well recognized that an observed SEM image can be thought of as the convolution of a point spread function (psf) arising from measurement broadening and the true structure imaged. However, even with the abovementioned advances, a variety of additional limitations arise that are preventing the practical implementation of deconvolution to SEM image restoration. These factors include noise as well as a lack of detailed knowledge of the psf since no experimental technique is currently available to directly measure it with level of spatial resolution required. Furthermore, the problem is complicated by other factors such as specimen drift, contamination, the three dimensionality of specimen, signal excitation volume considerations, non-linearity in the scanning system and also nonlinear behavior in the detection chain [1].

Improved SEM Image Resolution Through the Use of Image Restoration Techniques

Improving spatial resolution has been a major goal of scanning electron microscope (SEM) development since the first commercial instrument was introduced in the mid-1960s. While the early SEMs had resolutions in the 25 to 50 nm range when operated around 20 KV, more recently available microscopes can provide resolutions around 1 nm even below 1 KV. Critical to this development were improved electron optics including more advanced electron guns, lenses and aberration correctors to produce the smallest possible electron probes. High performance comes, however, with increased cost and it is unclear as to just what the next steps will be to obtain still better resolution. The need for a small probe is based on the fact that as magnification is increased the pixel size must be decreased such that the probe size is approximately equal to the pixel size, and thus information is unique to each pixel. If the probe size is larger than the pixel size then oversampling and blurring occurs.