Improvements in SDD Effi ciency
eff ects on the nitrogen peak in spectra of CrN.
Figure 2 : A selection of X-ray element maps acquired from a steel L profi le with an average input count rate of 884 kcps at 0.12 µs amplifi er processing time. (a) Phase map showing steel (yellow) and a Ni-rich inclusion (blue). Inside the Ni-rich inclusion, a Mo-rich phase is shown in bright purple and yellow, and a Si-rich phase is shown in cyan. The epoxy embedding material (green) is carbon-rich. (b) Ni map. (c) Mo map. (d) C map. Image width = 800 µm.
detectors will have a thin window to protect the detector itself from the exterior environment. T ese windows will have a support grid to prevent the structure from collapsing. Figure 1 shows that the support grid can obscure a signifi cant part of the active area of the EDS detector. T us, one should consider both the open area of the support grid as well as the active area of the detector when comparing diff erent detector types. Window material . T e composition of the window is another parameter to consider. Earlier systems used Be windows that had very limited transmission in the low-energy range. Current EDS detectors typically have a 300 nm thick polymer window or a <100 nm thick silicon nitride window. Assuming all other parameters are the same (detector-to-sample distance, detector area, support grid coverage), an analysis of a nitrogen- containing sample would result in roughly twice the number of counts in the nitrogen peak for a detector with a silicon nitride window compared to a polymer window. Figure 2 shows transmission curves for the two window materials and their
Output X-ray count rate . With an understanding of the geometric and material aspects aff ecting the input count rate to the SDD, we can now turn to the relationship of input to output count rate that leads to throughput. T e X-ray count throughput is of primary importance to the microanalyst because this is the measure of counts that are actually used in the generation of spectra, linescans, and element maps. T e series of processes that describes the ICPS to OCPS conversion is referred to as the “charge-to-voltage conversion.” T is encompasses (1) the X-ray photon energy conversion to a number of electron-hole pair events
in the SDD sensor and (2) the charge-to-voltage converter and pulse-shaping amplifi er in the electronics [ 5 ]. While Si(Li) detectors commonly had the entire preamplifi er external to the detector crystal itself, SDDs oſt en integrate a JFET (junction gate fi eld-eff ect transistor) on the detector chip to reduce capacitance and noise [ 6 ]. Some recent systems employ an external CMOS (complementary metal-oxide semiconductor) preamplifi er, which results in further reductions in capacitance and noise, allowing better performance at high count rates and better low-energy response [ 7 ]. Following the preamplifi er is the pulse processor, which generates a voltage output pulse typically consisting of a triangular or trapezoidal curve with a fl at at the top ( Figure 3 ). T e total pulse processing time is the amount of time it takes to analyze a single X-ray event and place it in the spectrum; consequently, this factor determines the number of
Figure 3 : Illustration of pulse processor ramp signal and timings. 48
Figure 4 : Energy resolution (Mn Kα at FWHM) as a function of processing time for two generations and sizes of SDD detectors (Super being roughly twice the area of Plus) where the newer (Octane Elite) employs CUBE technology and shows signifi cant improvements in resolution at fast processing times. The same digital pulse processor was used for all measurements.
www.microscopy-today.com • 2017 March
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