Automated Inclusion Microanalysis in Steel by SEM 1083
steels. Steel samples were polished to a 1 µm metallographic finish (using diamond suspension) before analysis. Inclu-
sions in such steel samples have similar CaO–Al2O3–MgO compositions (with slightly different Ca, Al, and Mg ratios due to the extent of Ca reacting with original Al2O3 orMgO– Al2O3 inclusions) as used in the simulation. The matrix was taken to be pure iron (Fe) with a density of 7.9 g/cm3.
Figure 1. The measured distribution of inclusion compositions is much narrower when the same sample area is analyzed at 10kV (results at left) instead of 20kV (results at right); measured using an ASPEX Explorer instrument. Originally published by AIST in the AISTech 2015 Proceedings (Tang & Pistorius, 2015).
(inclusions with apparent diameter in the range from ~1 to 4 μm, and with a hemispherical or sunken sphere shape) (Pistorius et al., 2013). The errors can be reduced considerably by using 10kV instead, whereas the matrix effect is even larger at 15kV (Pistorius & Verma, 2011; Pistorius & Patadia, 2012; Pistorius et al., 2013, 2015). As an example of the effect of accelerating voltage, Figure 1 shows the measured distribution of compositions for analyses performed on CaO–Al2O3–MgO inclusions in the same Ca-treated Al-killed low-carbon steel sample at 10 and 20kV. (In this figure, the symbol areas in the ternary com- position plot are scaled proportional to the total exposed area of inclusions with that composition.) Compared with the 20kV analysis, the range of measured compositions is nar- rower when analysis is performed at 10kV—confirming the smaller matrix effect for analysis at 10 kV. (Details of the method used to quantify inclusion compositions are given in the Materials and Methods section. The compositions shown in Figure 1 represent the oxidic part of the inclusions: manganese was assumed to be present as MnS and subtracted from the analysis; any sulfur remaining after sub- tracting MnS from the inclusion composition was assumed to be CaS and also subtracted before plotting the inclusion compositions as combinations of CaO, MgO, and AlO1.5.) Although analysis at the lower voltage improves analysis
accuracy, a concern is that the analysis time could be longer when using 10 kV (because of lower X-ray count rate and lower BSE current). These effects were quantified (using both simulations and experimental measurements), and are reported in this paper.
MATERIALS ANDMETHODS
Compositions For simulations, inclusions were taken to have the compo- sition Ca4Al4MgO11 (density: 3.5 g/cm3), spherical in shape, and surrounded by a 0.1-μm thick calcium sulfide (CaS) shell, corresponding to a fully Ca-modified spinel inclusion, and as used in previous work (Pistorius & Verma, 2011). For experimental work, samples used for manual and automated inclusion analyses were Ca-treated Al-killed low-carbon
Simulations
The Monte Carlo simulation package PENEPMA was applied; the package builds on the general-purpose code PENELOPE to model interactions of a monoenergetic elec- tron beamwith matter (Salvat et al., 2007). The generation of both BSE and characteristic X-rays was calculated, for spherical inclusions of various sizes and for different loca- tions of the polishing plane relative to the center of the spherical inclusions. The number of simulated electron trajectories was 107 for X-rays and 105 for BSE. MATLAB was used to simulate the effect of pixel dwell time on noise in BSE images.
Instruments
The SEMs used in this work were an FEI/Philips XL30 SEM (XL30) and an FEI ASPEX Explorer SEM (ASPEX) (FEI,
now ThermoScientific, Hillsboro, OR, USA). The XL30 is a field-emission SEM equipped with a silicon drift detector (35° takeoff angle; 10mm2 active area); automated inclusion microanalysis was performed with INCA Feature software (Oxford Instruments, Abingdon, Oxfordshire, UK), which uses the XPP phi-rho-z algorithm for composition quantifi-
cation (Pouchou & Pichoir, 1991). The ASPEX is a tungsten filament SEM with a silicon drift detector (45° takeoff angle; active area 30mm2); automatic feature analysis (AFA) soft- ware controlled the instrument for automated inclusion microanalysis. Both instruments used solid-state BSE detec- tors. Measured EDX spectra were converted to compositions using the Merlet phi-rho-z algorithm (Merlet, 1994), implemented in an Excel spreadsheet. For use with the Merlet algorithm, virtual standards were generated using DTSA-II (Version Jupiter, released May 4, 2016) (Ritchie, 2009), for materials that were taken to be homogeneous mixtures of iron and relevant oxides and sulfides. When calculating compositions with the Merlet algorithm, iron was included in the composition quantification, and subse- quently normalized out of the inclusion compositions. Stage current was measured with a picoammeter; beam current was measured using a brass Faraday cup mounted on an aluminum stub.
RESULTS AND DISCUSSION
BSE Images: Beam Current, Pixel Dwell Time, Accelerating Voltage, and Image Noise
BSE image quality affects detection of inclusions, and the ability to distinguish phases in complex (multiphase)
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