Efficient Simulation of Secondary Fluorescence Via NIST DTSA-II Monte Carlo

Abstract

Secondary fluorescence, the final term in the familiar matrix correction triumvirate Z·A·F, is the most challenging for Monte Carlo models to simulate. In fact, only two implementations of Monte Carlo models commonly used to simulate electron probe X-ray spectra can calculate secondary fluorescence-PENEPMA and NIST DTSA-II a (DTSA-II is discussed herein). These two models share many physical models but there are some important differences in the way each implements X-ray emission including secondary fluorescence. PENEPMA is based on PENELOPE, a general purpose software package for simulation of both relativistic and subrelativistic electron/positron interactions with matter. On the other hand, NIST DTSA-II was designed exclusively for simulation of X-ray spectra generated by subrelativistic electrons. NIST DTSA-II uses variance reduction techniques unsuited to general purpose code. These optimizations help NIST DTSA-II to be orders of magnitude more computationally efficient while retaining detector position sensitivity. Simulations execute in minutes rather than hours and can model differences that result from detector position. Both PENEPMA and NIST DTSA-II are capable of handling complex sample geometries and we will demonstrate that both are of similar accuracy when modeling experimental secondary fluorescence data from the literature.

Secondary Fluorescence Correction for Characteristic and Bremsstrahlung X-Rays Using Monte Carlo X-ray Depth Distributions Applied to Bulk and Multilayer Materials

“…For bulk materials, the difference between the correct angular distribution and isotropic production is not significant (Ritchie, 2009). For a thin film on a substrate, even though bremsstrahlung X-rays tend to be emitted in the direction of the traveling electrons (Ritchie, 2017), this isotropic angular distribution assumption is only used for the calculation of the bremsstrahlung fluorescence intensities, which are relatively small in most cases and mostly due to the substrate and not the film. In the case of a thin film where the approximation is not valid, the effect of the approximation on the bremsstrahlung fluorescence correction can be ignored as the bremsstrahlung intensity generated from the thin film is relatively small.…”

“…Unsurprisingly, this generality with minimal approximations results in long computation times. DTSA-II uses a simpler continuous slowing down model for electron transport, after which the ionization of the primary X-ray is modeled in each electron trajectory segment (Ritchie, 2017). Then the secondary fluorescence is simulated by propagating the primary X-rays isotropically.…”

“…Then the secondary fluorescence is simulated by propagating the primary X-rays isotropically. DTSA-II is much faster than PENEPMA but still not as efficient as analytical models (Ritchie, 2017).…”

Measuring the Thickness of Metal Films: A Selection Guide to the Most Suitable Technique

“…Both the absolute thickness [136,137] as well as the mass thickness [138][139][140][141] were taken into consideration for the quantification. In the last fifty years, many pieces of software were written to simulate EDS spectra [142]; many of them are written by researchers and some were commercial: MAGIC [143,144], STRATAGEM [145][146][147], GMRFILM [122], Electron Flight Simulator [148,149], ThinFilmID [150] and LayerProbe [150,151], pyPENELOPE [152,153], Win X-Ray [154,155] and MC X-Ray [154,156], XFilms [157], CASINO [124,[158][159][160][161], CalcZAF [162,163] and DTSA-II [164][165][166]. Many of these pieces of software exploit the PENEPMA algorithm [153].…”

Correction of Secondary Fluorescence Across Phase Boundaries in Electron Probe Microanalysis of Mineral Inclusions

“…The advantage of the Monte Carlo method is that it can be applied to samples with relatively complex geometries (see, e.g., Jennings et al, 2019aJennings et al, , 2019b. Its main drawback is that results are affected by statistical uncertainties, which in principle can only be reduced by increasing the simulation time, but recent progress in variance reduction techniques along with the increasing availability of fast computers have enhanced the attractiveness of this method for SF calculations (Llovet & Salvat, 2017;Ritchie, 2017;Yuan et al, 2019). The Monte Carlo simulation program PENEPMA (Llovet & Salvat, 2017) has the advantage over other existing codes that it simulates not only the transport of primary and secondary electrons but also that of generated X-rays, thus providing the SF contribution without any further calculation.…”