Nicholas W. M. Ritchie

Spectrum Simulation in DTSA-II

Spectrum simulation is a useful practical and pedagogical tool. Particularly with complex samples or trace constituents, a simulation can help to understand the limits of the technique and the instrument parameters for the optimal measurement. DTSA-II, software for electron probe microanalysis, provides both easy to use and flexible tools for simulating common and less common sample geometries and materials. Analytical models based on (rhoz) curves provide quick simulations of simple samples. Monte Carlo models based on electron and X-ray transport provide more sophisticated models of arbitrarily complex samples. DTSA-II provides a broad range of simulation tools in a framework with many different interchangeable physical models. In addition, DTSA-II provides tools for visualizing, comparing, manipulating, and quantifying simulated and measured spectra.

EDS measurements of X-ray intensity at WDS precision and accuracy using a silicon drift detector.

The accuracy and precision of X-ray intensity measurements with a silicon drift detector (SDD) are compared with the same measurements performed on a wavelength dispersive spectrometer (WDS) for a variety of elements in a variety of materials. In cases of major (>0.10 mass fraction) and minor (>0.01 mass fraction) elements, the SDD is demonstrated to perform as well or better than the WDS. This is demonstrated both for simple cases in which the spectral peaks do not interfere (SRM-481, SRM-482, and SRM-479a), and for more difficult cases in which the spectral peaks have significant interferences (the Ba L/Ti K lines in a series of Ba/Ti glasses and minerals). We demonstrate that even in the case of significant interference high count SDD spectra are capable of accurately measuring Ti in glasses with Ba:Ti mass fraction ratios from 2.7:1 to 23.8:1. The results suggest that for many measurements wavelength spectrometry can be replaced with an SDD with improved accuracy and precision.

Monte Carlo modeling of secondary electron imaging in three dimensions

Measurements of critical dimensions (CDs), roughness, and other dimensional aspects of semiconductor electronics products rely upon secondary electron (SE) images in the scanning electron microscope (SEM). These images are subject to artifacts at the nanometer size scale that is relevant for many of these measurements. The most accurate measurements for this reason depend upon models of the probe-sample interaction in order to perform corrections. MONSEL, a Monte Carlo simulator intended primarily for CD metrology, has been providing the necessary modeling. However, restrictions on the permitted sample shapes are increasingly constraining as the industrys measurement needs evolve towards inherently 3-dimensional structures. We report here results of a collaborative project, in which the MONSEL physics has been combined with the 3D capabilities of NISTMonte, another NIST Monte Carlo simulator that was previously used principally to model higher energy electrons and x-rays. Results from the new simulator agree very closely with the original MONSEL for samples within the repertoire of both codes. The new codes predicted SE yield variation with angle of incidence agrees well with preexisting measurements for light, medium, and heavy elements. Capabilities of the new code are demonstrated on a model of a FinFET transistor.

Elemental mapping of microstructures by scanning electron microscopy-energy dispersive X-ray spectrometry (SEM-EDS): extraordinary advances with the silicon drift detector (SDD)

Elemental mapping at the microstructural level by scanning electron microscopy (SEM) with energy dispersive X-ray spectrometry (EDS), while widely applied in science, engineering, and technology, has been limited in performance by the throughput of the lithium-drifted silicon detector [Si(Li)-EDS] which restricts the number of X-ray counts measured per image pixel. The emergence of the silicon drift detector (SDD-EDS) has greatly extended the X-ray throughput, by a factor of 25 to 70 for the same spectral resolution. This improved performance enables practical X-ray spectrum imaging (XSI), in which a complete X-ray spectrum is recorded at each image pixel. By performing complete quantitative corrections for background, peak overlap, and matrix effects to each pixel spectrum, full compositional mapping can be achieved. Various elemental mapping collection strategies are described, including quantitative mapping at the major (concentration C > 0.1 mass fraction), minor (0.01 ≤ C ≤ 0.1), and trace (C < 0.01) constituent levels, extreme pixel density (gigapixel) mapping, rapid mapping (in 10 seconds or less), and high spatial resolution mapping with the thermal field emission gun scanning electron microscope.

Bridging the micro-to-macro gap: a new application for micro X-ray fluorescence.

X-ray elemental mapping and X-ray spectrum imaging are powerful microanalytical tools. However, their scope is often limited spatially by the raster area of a scanning electron microscope or microprobe. Limited sampling size becomes a significant issue when large area (>10 cm²), heterogeneous materials such as concrete samples or others must be examined. In such specimens, macro-scale structures, inclusions, and concentration gradients are often of interest, yet microbeam methods are insufficient or at least inefficient for analyzing them. Such requirements largely exclude the samples of interest presented in this article from electron probe microanalysis. Micro X-ray fluorescence-X-ray spectrum imaging (μXRF-XSI) provides a solution to the problem of macro-scale X-ray imaging through an X-ray excitation source, which can be used to analyze a variety of large specimens without many of the limitations found in electron-excitation sources. Using a mid-sized beam coupled with an X-ray excitation source has a number of advantages, such as the ability to work at atmospheric pressure and lower limits of detection owing to the absence of electron-induced bremsstrahlung. μXRF-XSI also acts as a complement, where applicable, to electron microbeam X-ray output, highlighting areas of interest for follow-up microanalysis at a finer length scale.

Uncertainty estimates for electron probe X-ray microanalysis measurements.

It has been over 60 years since Castaing (Castaing, R. Application of Electron Probes to Local Chemical and Crystallographic Analysis. Ph.D. Thesis, University of Paris, Paris, France, 1951; translated by P. Duwez and D. Wittry, California Institute of Technology, 1955) introduced the technique of electron probe X-ray microanalysis (EPMA), yet the community remains unable to quantify some of the largest terms in the techniques uncertainty budget. Historically, the EPMA community has assigned uncertainties to its measurements which reflect the measurement precision portion of the uncertainty budget and omitted terms related to the measurement accuracy. Yet, in many cases, the precision represents only a small fraction of the total budget. This paper addresses this shortcoming by considering two significant sources of uncertainty in the quantitative matrix correction models--the mass absorption coefficient, [μ/ρ], and the backscatter coefficient, η. Understanding the influence of these sources provides insight into the utility of EPMA measurements, and equally important, it allows practitioners to develop strategies to optimize measurement accuracy by minimizing the influence of poorly known model parameters.

Analysis of 3D elemental mapping artefacts in biological specimens using Monte Carlo simulation.

In this paper, we present Monte Carlo simulation results demonstrating the feasibility of using the focused ion beam based X‐ray microanalysis technique (FIB‐EDS) for the 3D elemental analysis of biological samples. In this study, we used a marine diatom Thalassiosira pseudonana as our model organism and NISTMonte for the Monte Carlo simulations. We explored several beam energies commonly used for the X‐ray microanalysis to examine their effects on the resulting 3D elemental volume of the model organism. We also performed a preliminary study on the sensitivity of X‐ray analysis for detecting nanoparticles in the model. For the conditions considered in this work, we show that the X‐ray mapping performed using the 5 keV beam energy results in 3D elemental distributions that closely reflect the elemental distributions in the original model. At 5 keV, the depth resolution of the X‐ray maps is about 250 nm for the model organism. We also show that the nanoparticles that are 50 nm in diameter or greater are easily located. Although much work is still needed in generating more accurate biological models and simulating experimental conditions relevant to these samples, our results indicate that FIB‐EDS is a promising technique for the 3D elemental analysis of some biological specimens.

Getting Started with NIST * DTSA-II

Introduction Since its introduction in 2007, DTSA-II [1–3] has been adopted by numerous researchers, and it has been integrated into numerous educational programs. This is the first of a series of articles in Microscopy Today that will appear in the upcoming months to provide an introduction to use of the product. These articles also will provide details of how DTSA-II can be used to implement best practices for microanalysis in your laboratory or in your teaching environment. These articles will demonstrate how to form the most accurate type of spectrum quantification—standards-base quantification— as well as how to use simulation to optimize various types of measurement problems. They will focus on using DTSA-II to understand the physical process including the interaction of energetic electrons with your sample and the propagation of x-rays through matter and to the detector. DTSA-II provides many different tools, but the primary ones are for quantification, simulation, visualization, and manipulation of energy-dispersive x-ray spectra. Each of these tools will be introduced separately in forthcoming articles. The remainder of this article will provide an overview of the tools and introduce two important aspects of the program: (1) The way DTSA-II implements detectors for both quantification and simulation and (2) the way DTSA-II imports spectra from disks.

Using DTSA-II to Simulate and Interpret Energy Dispersive Spectra from Particles

A high quality X-ray spectrum image of a 3.3 mum diameter sphere of K411 glass resting on a copper substrate was collected at 25 keV. The same sample configuration was modeled using the NISTMonte Monte Carlo simulation of electron and X-ray transport as is integrated into the quantitative X-ray microanalysis software package DTSA-II. The distribution of measured and simulated X-ray intensity compare favorably for all the major lines present in the spectra. The simulation is further examined to investigate the influence of angle-of-incidence, sample thickness, and sample diameter on the generated and measured X-ray intensity. The distribution of generated X-rays is seen to deviate significantly from a naive model which assumes that the distribution of generated X-rays is similar to bulk within the volume they share in common. It is demonstrated that the angle at which the electron beam strikes the sample has nonnegligible consequences. It is also demonstrated that within the volume that the bulk and particle share in common that electrons, which have exited and later reentered the particle volume, generate a significant fraction of the X-rays. Any general model of X-ray generation in particles must take into account the lateral spread of the scattered electron beam.

Can X-ray spectrum imaging replace backscattered electrons for compositional contrast in the scanning electron microscope?

The high throughput of the silicon drift detector energy dispersive X-ray spectrometer (SDD-EDS) enables X-ray spectrum imaging (XSI) in the scanning electron microscope to be performed in frame times of 10-100 s, the typical time needed to record a high-quality backscattered electron (BSE) image. These short-duration XSIs can reveal all elements, except H, He, and Li, present as major constituents, defined as 0.1 mass fraction (10 wt%) or higher, as well as minor constituents in the range 0.01-0.1 mass fraction, depending on the particular composition and possible interferences. Although BSEs have a greater abundance by a factor of 100 compared with characteristic X-rays, the strong compositional contrast in element-specific X-ray maps enables XSI mapping to compete with BSE imaging to reveal compositional features. Differences in the fraction of the interaction volume sampled by the BSE and X-ray signals lead to more delocalization of the X-ray signal at abrupt compositional boundaries, resulting in poorer spatial resolution. Improved resolution in X-ray elemental maps occurs for the case of a small feature composed of intermediate to high atomic number elements embedded in a matrix of lower atomic number elements. XSI imaging strongly complements BSE imaging, and the SDD-EDS technology enables an efficient combined BSE-XSI measurement strategy that maximizes the compositional information. If 10 s or more are available for the measurement of an area of interest, the analyst should always record the combined BSE-XSI information to gain the advantages of both measures of compositional contrast.