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31 January - 3 February 2009

San Antonio, Texas
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12-16 July 2009
Minneapolis, Minnesota
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NORM and TENORM
16-18 July 2009
Minneapolis, Minnesota
21 November 2008

The Effect of the Time-Temperature Heating Profile Design on the Precision and Accuracy of Thermoluminescent (TL) Glow Curve Peak Areas for LiF: Mg, Ti

M.L. Rodrigues; K.J. Kearfott; S.-H. Hsu; J.E. Schlicht; L.W. Parker; and L.R. Baumgarten (University of Michigan)

Some thermoluminescent (TL) materials research, e.g. new material characterization, fading studies, or modeling of TL behavior, requires the analysis of individual TL glow curve peaks. The amount of the light emitted as a function of time depends upon the heating rate, maximum temperatures achieved, and length of time that temperatures are held. The standard design for most TL readers limits the number of temporal data points available for glow curve analysis. Glow curve analysis involves fitting these points with sums of Gaussians or other functions using processes that are subject to uncertainty and inaccuracy. The accuracy and precision of the glow curve peak areas determined using these fits depend upon both the noise in the individual data points as well as the temporal sampling for the glow curve. For this work, the effects of varying the time-temperature profiles (TTPs) on the resulting determination of the areas of various glow peaks is examined. A Harshaw 4500 TLD Reader, with a 200-channel glow curve collection capability, was used with standard LiF: Mg, Ti (TLD-100) and the vendor-supplied analysis software, WINGCF, for the study. A total of 60 detectors, held in 15 cards, are individually calibrated and read out using the reader's pair of hot gas jets. The detectors are exposed to a Cs-137 source for varying amounts of time to achieve different doses, ranging from nearly detectable to 5 mSv. The irradiations are repeated and variations in pre-heat, acquisition, annealing times and temperatures used to obtain the glow curve data. For a given fit of data from a TL detector, the total peak areas are determined. Averages and standard deviations are computed for each time-temperature profile type and dose level. A comparison of these data reveals information about an optimized TTP.

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