Multi-Spectral XRF Counting: Squeeze Twice as much Information from Your Detector

Counting small peaks on large backgrounds in XRF applications is a process limited by the statistics of estimating both the counts and the background in the peak region. Improving energy resolution ΔE helps by increasing peak/background ratio and providing a more accurate estimate of the background but also reduces counting statistics due to increased pileup losses. Time variant filtering techniques have not been useful because their detector response functions vary with counting rate, precluding the accurate use of standards. Here we present a new time variant approach that takes a small set of shaping filters, applies the longest one to each detector output pulse, and places the result into a spectrum specific to that filter. By not commingling the filters’ results, we produce multiple spectra whose detector response functions do not depend upon input count rate and can thus be used with standards-based analyses. Both theoretical and experimental measurements show that this approach allows the filters’ information to be fully preserved, so that an optimized multi-spectral spectrometer can achieve the same signal to noise ratio in approximately half the counting time required by an optimized single filter spectrometer.