A Radioactive Tracer Dilution Method for Mass Determination in Licl-Kcl Radioactive Eutectic Salts

A Radioactive Tracer Dilution Method for Mass Determination in LiCl-KCl Radioactive Eutectic Salts

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree of Masters of Science from the Graduate School of The Ohio State University

Douglas Ernest Hardtmayer, B.Sc. Welding Engineering

Graduate Program in Nuclear Engineering

The Ohio State University 2018

Thesis Committee:

Dr. Lei. Cao, Advisor Dr. Vaibhav Sinha

ABSTRACT

Radioactive Tracer Dilution (RTD) is a new method where a radioactive tracer isotope is dissolved in a given substance, and the dilution thereof corresponds to the mass and volume of the substance in which the tracer was dissolved. This method is being considered commercially as a means of measuring the mass of Lithium Chloride-Potassium Chloride (LiCl-KCl) eutectic salt in electrorefiners where spent nuclear fuel has been reprocessed. Efforts have been ongoing to find an effective and efficient way of measuring the mass of this salt inside of an electrorefiner for nuclear material accountancy purposes. Various methods, including creating volume calibration curves with water and molten salt, have been tried but have numerous shortcomings, such as needing to recalibrate the fitted volume curve for a specific electrorefiner every time a new piece of equipment is added or removed from the device. Research at The Ohio State University has shown promise using Na22 as a tracer in LiCl-KCl eutectic salt, and that the interference from a common fission product found in an electrorefiners salt, Eu154, could be accounted for, and an accurate mass measurement could be determined. To more closely mimic the conditions in which this technique would be used, Cs137 was added to a larger mass of LiCl-KCl salt, to see if this would affect the measurement of the salt mass. Self-shielding effects were noticed with larger salt masses, and MCNP was utilized to validate and quantify this self-shielding effect. To further

Increase this interference, button sources of Cs137 were utilized to artificially raise the Cs137 activity to increase the dead time of a standard High Purity Germanium Detector. It was found that the addition of Cs137, and using a larger salt mass, did not affect the overall methodology used to determine salt mass, and in fact, simulation packages such as MCNP can be further used to increase the accuracy of this methodology. It was also found that idealistic correctional models could account for higher dead times incurred by the introduction of additional Cs137.

Dedication

This document is dedicated to my family and supportive group of many friends.

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Acknowledgements

I would like to first thank Dr. Lei (Raymond) Cao, my graduate advisor in the Ohio State Nuclear

Engineering program. He has been a tremendous source of inspiration, and was instrumental in

supporting me during my time studying at The Ohio State University. I would also like to thank

the Ohio State University Research Reactor lab staff, whose hard work and attention detail,

provided the data and results that made this study a success. Lastly, I would like to thank our

sponsors at the Idaho National Laboratory, who helped to fund and provide insight on this

project.

Vita

May 2012……………………………………………Hudson High School, Hudson, OH.

Dec. 2016…………………………………………...B.Sc., Welding Engineering, The Ohio State

University, Columbus, OH.

Jan 2012 to Present…………………………...... Graduate Research Associate, Nuclear

Engineering Program, The Ohio State University, Columbus, OH.

Publications

Lei Cao*, Josh Jarrell**, Andrew Kauffman, Susan White, Kevin Herminghuysen, Douglas

Hardtmayer**, Jeff Sanders, Shelly Li. (2017). A Radioactive Tracer Dilution Method to

Determine the Mass of Molten Salt. Journal of Radioanalytical and Nuclear Chemistry. doi:

10.1007/s10967-017-5417-5 [Published]

Fields of Study

Major Field: Nuclear Engineering

Table of Contents

ABSTRACT ...... ii Dedication ...... iii Acknowledgements ...... iv Vita ...... v List of Figures ...... vii List of Tables ...... viii Introduction ...... 1 Theory ...... 5 Radioactive Tracer Dilution ...... 5 Tracer Selection ...... 6 Isotopic Ratio Determination ...... 7 Experimental Procedure ...... 9 Radioactive Tracer Dilution ...... 9 Dead Time Measurement ...... 12 Sensitivity Analysis ...... 14 Results and Discussion ...... 15 Radioactive Tracer Dilution Results ...... 15 Preliminary Results ...... 15 Self-Attenuation Validation ...... 21 Dead Time Measurement and Correction ...... 25 Sensitivity study ...... 28 Summary ...... 31 Conclusions ...... 31 Future Work ...... 32 References ...... 33 Appendix: Supplemental Information ...... 36 1. MATLAB script for Dead Time Corrections ...... 36 2. MCNP Sample Input Deck for Gamma Spectroscopy ...... 36 3. Weight Measurements for Each Crucible and Salt Addition ...... 40 4. MCNP Input Deck for Attenuation Correction ...... 41 5. Liquid Source Handling Procedure from OSURR Staff ...... 45

List of Figures

Figure 1: Electrorefiner schematic showing the separation of uranium, Major Actinides, and Fission Products in LiCl-KCl Eutectic Salt ...... 2 Figure 2: Na22 activity vs LiCl-KCl eutectic salt mass from [14]...... 6 Figure 3: OSURR staff pipetting liquid source for addition to a crucible [14]...... 10 Figure 4: Spectral readout from the OSURR GRSS, with isotopic markers manually placed...... 11 Figure 5: Glassy carbon crucible containing melted LiCl-KCl eutectic salt and added isotopes...... 11 Figure 6: Molten salt casting from the miniature waffle maker ...... 12 Figure 7: Alumina crucible, with 5g of salt, on GRSS platform with a single Cs-137 button source...... 13 Figure 8: Na22 (tracer isotope) mass vs. activity comparison with trend line...... 16 Figure 9: Na22 (tracer isotope) mass vs. specific activity...... 16 Figure 10: Eu154 (fission product) mass vs. activity comparison with trend line...... 17 Figure 11: Eu154 (fission product) mass vs. specific activity...... 18 Figure 12 Cs137 (fission product) mass vs. activity comparison with a trend line...... 19 Figure 13: Cs137 (fission product) mass vs. specific activity...... 19 Figure 14: Volumetric source shown in the MCNP’s Visual Editor. This particular instance shows an alumina crucible containing 40 grams of salt...... 22 Figure 15: MCNP calculated specific activities compared to the observed specific activities ...... 23 Figure 16: Adjusted activities for alumina crucible measurements only...... 24 Figure 17: Na22 activity corrections, utilizing both the paralyzable and non-paralyzable method...... 27 Figure 18: Hypothetical gamma spectrum from a .5:1 ratio of Na22: Eu154 showing that the overlapping photopeak is comprised of approximately 70% Na22 counts...... 29 Figure 19: Hypothetical gamma spectrum from a 5:1 ratio of Na22: Eu154 showing that the overlapping photopeak is comprised of approximately 96% Na22 counts...... 30

vii

List of Tables

Table 1: Various tracer isotope candidates for RTD [14]...... 6 Table 2: Ratios of Cs137 to Eu154 present in ER Mk.IV and Mk.V salt at INL...... 8 Table 3: Summary of Na22 activity measurements and uncertainties ...... 15 Table 4: Summary of Eu154 activity measurements and uncertainties...... 17 Table 5: Summary of Cs137 activity measurements and uncertainties...... 18 Table 6: Summary of observed activities with MCNP calculated activity ...... 23 Table 7: Summary of statistical values with various corrective techniques...... 24 Table 8: Summary of Na22 readings using the paralyzable and non-paralyzable methods of dead time correction...... 27

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Introduction

Molten salts are currently used or being considered for use in a wide variety of industrial applications. Nitrate and chloride based salts are used for low distortion, quenching based metallurgical operations [1]. More recently, molten salts are being used at solar power plants to help combat electricity intermittency issues, and are used for their high heat capacity [2]. Also Known as Thermal Energy Storage

(TES), excess electricity is stored as heat in a low melting temperature salt, which is used to create superheated steam to create electricity when demand is high.

For nuclear applications, molten salt is used as a separation media at the Idaho National

Laboratory (INL) for a spent nuclear fuel reprocessing technique known as pyroprocessing. INL has been using this technique to reprocess and safely dispose of spent nuclear fuel from their Experimental Breeder

Reactor-II facility since 1996 [3, 4]. Part of the pyroprocess involves the use of an electrorefiner (ER), which contains a eutectic molten salt mixture of Lithium Chloride-Potassium chloride (LiCl-KCl) salt. Before the fuel is loaded into an electrorefiner, the fuel is chopped and loaded into a perforated steel basket, which serves as the anode [5]. The purpose of electrorefining is to recover the uranium and major actinides, and separate them from the fission fragments, which are dispersed throughout the fuel. The LiCl-KCl salt serves as the electrolyte solution, and allows uranium and other major actinides to form dendritically on separate cathodes. A solid cathode collects the uranium, which is dissolved in the salt solution. When a certain ratio of actinides to uranium is reached, a liquid cadmium cathode is introduced to collect the remaining uranium and major actinides. This electrorefining process is illustrated in Figure 1 below.

Figure 1: Electrorefiner schematic showing the separation of uranium, Major Actinides, and

Fission Products in LiCl-KCl Eutectic Salt

Spent reactor fuel is comprised of many different fission fragment isotopes, which remain in the salt after pyroprocessing and accumulate over time when pyroprocessing is repeated.

The International Atomic Energy Agency (IAEA) requires various Nuclear Material Accountancy

(NMA) methods for member nations. Tracking the usage of nuclear materials is imperative for implementing non-proliferation strategies [6]. An electrorefiner used for fuel reprocessing is no exception for the need of nuclear material accountancy [7, 8, 9]. For this to occur, the mass of the salt inside of an electrorefiner must be determined, which can be difficult given the complex geometry of an electrorefiner and the highly radioactive environment in which it is situated. Various methods have been implemented to try to determine salt mass within an electrorefiner.

The first method is to use volume level measurements and previous ER volume calibration data.

This method presents its own set of challenges, since an ER is not a perfectly cylindrical shape, and any deviation in internal geometry from this perfect shape does not correlate directly to a specific volume. To try to correlate these volume level measurements more accurately, calibrations were performed by filling the volume of an ER twice, once with water and once with salt, and correlating these measurements with a specific volume [10]. More recently, a study was performed at INL’s Fuel Conditioning Facility to estimate salt density by using a thermodynamic model, in which mass fractions of each chloride that could be present in the salt were determined using the REBUS/RCT-3 code [11].

These methods would present many challenges if pyroprocessing were to be implemented commercially. For Example, if a new piece of equipment were to be removed or placed into the ER, a new calibration curve would need to be calculated, so that records for the facilities NMA logs are accurate.

Furthermore, these calibration curves may not be available to a third-party IAEA inspector, who would need the curves in order to validate a facility’s NMA records. In addition, depending on the location of the

ER, this volumetric calibration may be impossible to perform once in operation, illustrating that a new method is needed for accurate calculation of the mass of molten salt present in an ER.

Radioactive Tracer Dilution (RTD) has been suggested as a method for determining salt mass. RTD has been similarly used for other applications, such as for flow rate measurements [12], and has even been used in molten salt mixtures to determine transport numbers [13]. The Nuclear Analysis and

Radiation Sensing (NARS) laboratory at The Ohio State University (OSU) provided a proof of concept [14] that RTD could be used to determine the mass of molten salt accurately. This study showed that Na22, the tracer, could be dissolved into small quantities of LiCl-KCl eutectic salt, and were able to show that a linear relationship between salt mass and measured activity exist.

Based on these results, it was determined to repeat the experiment, this time introducing more variables that would more closely mimic the environment of an electrorefiner. It was decided that the addition of Cs137 would be needed. This addition was made because Cs137 is a prevalent fission fragment in ER salt, and the effect of its high activity with detector dead time and Compton plateau would need to be documented. It was also determined to increase the mass of the salt used, to determine if a larger salt mass affected the tracer’s ability to mix homogenously in the salt. Lastly, a sensitivity study would need to be performed, in order to determine the minimum amount of tracer that would be needed to accurately determine the mass of the salt.

Theory

Radioactive Tracer Dilution

RTD is based on the measured dilution of a tracer isotope in a given medium, which can be correlated to mass by the inversely proportional relationship between tracer isotope concentration and mass. A tracer of a given activity is measured and recorded. A material of unknown mass is then “spiked” with the tracer isotope. After thorough mixing, the small sample of the unknown mass is taken, and measured for mass and activity. By using the following equation, the unknown mass can be determined.

퐴 푀 = ∗ 푚 퐴

Eq. 1

Where 푀 is the unknown total mass, 퐴 is the measured activity of the tracer before spiking, 퐴 is the measured activity of the tracer after spiking, and 푚 is the measured mass of the smaller sample taken from the unknown, large mass. Eq. 1 was proven previously [14] in which a tracer was mixed with

20 grams of LiCl-KCl eutectic salt. This report found that by using the tracer, Na22, that the relationship between mass and activity was linear, indicating that any given sample size, 푚, could be used to determine an unknown quantity of salt mass, 푀. This linear relationship is illustrated in Figure 2.

Figure 2: Na22 activity vs LiCl-KCl eutectic salt mass from [14].

Tracer Selection

An important consideration of tracer isotope selection should be considered for each application.

In certain applications, the solubility of the tracer in each medium needs to be considered to ensure that the tracer will mix homogenously throughout the medium. The half-life of the tracer must be considered as well, since too much decay of the initial activity will lead to a non-linear relationship. Various tracer isotopes are outlined in Table 1 below.

Table 1: Various tracer isotope candidates for RTD [14].

[15]

Regarding ER salt, other fission products present must be considered as well. For example, Eu154 is a fission product that shares a gamma ray with the same energy as the main Na22 gamma ray at 1274.5 keV, which must be accounted for if Na22 is to be used as the tracer for RTD in ER salt. This can be done, as demonstrated in. [14], where the contribution of Eu154 in the 1274.5 keV photo peak was calculated and subtracted by using the branching ratios from other Eu154 gamma energies (e.g. 123.07 keV at 40.4%,

723.3 keV at 20.06%, and 1004.76 keV at 18.01%).

Since this interference from Eu154 can be accounted for if Na22 is used as the tracer for RTD, Na22 is an ideal selection for a tracer in ER salt. This is because Na22 is very soluble in chloride-based salts, it is not a fission product, and has a high energy and intensity (e.g. 1274.5 keV at 99.94%) gamma ray that falls outside of the energy ranges and Compton plateaus caused by the various fission fragments that would be present in used ER salt. Given these qualities, it was again decided that Na22 would be used as the tracer for this experiment.

Isotopic Ratio Determination

A goal of this study is to determine the effect of Cs137 on the dead time of a standard gamma measurement system, and to closely mimic the composition of ER salt, a relative ratio of the two investigated fission fragments, Cs137 to Eu154, needed to be determined. A way this could be performed is to perform burnup analysis of a given fuel type using a simulation package such as MCNP, SCALE, or

ORIGEN. To ensure the accuracy of results yielded from these simulations, many variables need to be considered. Due to the sheer complexity and number of the variables needed to use simulation codes accurately for burnup calculations, it was decided to use internal documentation provided by INL that had isotopic compositions of two types of ER salt (Mk. IV and Mk. V) which have been used to electrorefine spent nuclear fuel. Ratios of Eu and Cs in both salts are summarized in Table 2 below.

Table 2: Ratios of Cs137 to Eu154 present in ER Mk.IV and Mk.V salt at INL.

Cs-137 Eu-154 Salt Type Wt. Frac Activity (Ci) Wt. Frac Activity (Ci) Ratio Cs:Eu Mk. V 1.48E-04 1.28E-02 2.79E-07 7.55E-05 1.70E+02 Mk. IV 2.93E-03 2.54E-01 1.63E-06 4.41E-04 5.76E+02

Ratios of 576:1 or 170:1 would not be possible obtain directly, since Ohio State’s office of

Radiation Safety limit the activity of radioactive sources [16] that can be used at one time, and such a high ratio would have exceeded this limit. Therefore, it was decided to artificially increase this ratio by adding multiple button sources at varying distances to create the ratios of Cs: Eu desired.

Experimental Procedure

Radioactive Tracer Dilution

Based on the ratios of Cs to Eu from the INL internal documentation, and the given source safety limitations outlined in OSU’s radiation safety guidelines [16], it was decided that a 10:3:1 ratio of Cs137:

Eu154: Na22 would be used as the source for mixing into the 100 grams of salt. To begin, an empty, 150 ml glassy carbon crucible (SPI Supplies) was weighed on a Laboratory Classic PMW-320 scale (Intelligent

Weighing Technology) (uncertainty = ± 0.001 g), which is located in a PureLab HE 4-port glovebox (Inert).

This glovebox was backfilled with argon gas, and was kept at or less than 4.0 parts per million (ppm) of O2 and 0.3 ppm of H2O, and was also kept at a negative pressure. After weighing, the glassy carbon crucible was shipped and sent to the Ohio State University Research Reactor (OSURR) lab, where liquid chloride sources of 137CsCl, 154EuCl, 22NaCl (Eckert & Ziegler) were added to the empty, glassy carbon crucible.

Each isotope was added individually, and was allowed to dry in an oven at 60°C for approximately

1 hour. After drying, the source was counted on a coaxial high purity germanium (HPGe) (efficiency ε=15%) gamma ray spectroscopy system (GRSS) (Canberra Industries) using a LYNX digital signal analyzer (MIRION

Technologies) where the data was analyzed using Genie-2000 (Canberra Industries) software. This GRSS was calibrated using NIST standard point sources placed inside of empty crucibles that would be used in later steps. Counting times varied, and were considered complete when a counting statistical uncertainty of ± 1% was achieved. Following the counting of the first isotope addition, this process was repeated until all isotopes were added, dried, and counted in the glassy carbon crucible. This isotope addition is illustrated in Figure 3 below.

Figure 3: OSURR staff pipetting liquid source for addition to a crucible [14].

After all the isotope activities were counted, the glassy carbon crucible was packaged and delivered to the NARS laboratory, where the crucible could safely be handled inside of the PureLab glovebox. Once inside the glovebox, 122.293 grams of LiCl-KCl eutectic salt (APL Engineered Materials Inc.) was weighed and added to the glassy carbon crucible. This larger salt mass was used because of the availability of extra salt, which would only serve to increase the total mass of salt tested. The crucible was then placed into an Electro-Melt furnace (Kerr) at 500°C. After six hours of melting without stirring, and upon cooling, the crucible was removed and weighed on the PMW-320 scale multiple times, where an average weight was recorded. The crucible was then sent back to the OSURR for activity measurements on the GRSS. A sample spectrum readout from the GRSS is shown in Figure 4.

Figure 4: Spectral readout from the OSURR GRSS, with isotopic markers manually placed.

Figure 5: Glassy carbon crucible containing melted LiCl-KCl eutectic salt and added isotopes.

Following these measurements, the filled glassy carbon crucible was then sent back to the NARS laboratory, where it was then re-melted and cast into a miniature waffle maker (DASH). This casting is shown in Figure 6. Casting the salt into a minature waffle maker was performed based on recommendations from previous work [14], where directly casting the salt onto a flat metal surface led to an irregularly shaped casting that was difficult to break apart. The “waffle-shaped” casting was intended

11 to break apart easier. Upon breaking this casting apart into smaller pieces by hand inside of a re-sealable plastic bag. The smaller casting pieces were measured into approximate 5, 10, 20, and 40g groupings. Each grouping was added to a 100 ml alumina high-form crucible (AdValue Technology), and was melted individually in the Electro-Melt furnace at 500°C for two hours each. Upon cooling, the alumina crucibles were weighed on the PMW-320 scale multiple times, and an average weight was recorded. These four alumina crucibles were then picked up by OSURR staff, and taken back to OSURR for activity measurements. The glassy carbon crucible, which still contained some salt, was taken as well for proper disposal.

Figure 6: Molten salt casting from the miniature waffle maker

Each Crucible was individually measured on the GRSS with different geometries, where their respective activities were recorded and plotted against their respective mass. A least squares fit trend line could then be plotted, and the relationship between activity and mass could then be observed.

Dead Time Measurement

Further analysis was required to determine the effect that high dead times in a detection system, which would be incurred should this process be used on ER salt used for pyroprocessing, and to see if this could be accounted for. As stated previously, an accurate ratio of Cs137 to Eu154 could not be directly

12 introduced due to safety restrictions for handling radioactive sources. Therefore, using additional Cs137

NIST button sources would be required to increase this ratio. By doing so, this artificially increased activity during GRSS measurements will produce a higher system dead time, which can be quantified.

To do this experimentally, the alumina crucible with 5 grams of added salt was measured to within

± 1 % certainty. Button sources, shown with the 5 gram crucible in Figure 7, were individually added to approximately create ratios of 3:1, 65:1, 130:1, and 170:1. This last ratio is that which most closely recreates the ratio found in Mk. V salt shown in Table 2.

Button Source

Figure 7: Alumina crucible, with 5g of salt, on GRSS platform with a single Cs-137 button

source.

By using a MATLAB script [Appendix item 1], dead time correction models that can be found in Knoll [17] were used to calculate what the real measured activity of each isotope was, instead of what was counted by the GRSS directly. These corrective models, which are usually applied for Ideal detectors in hypothetical situations, are known as the paralyzable and non-paralyzable method. These methods will be further explained in the results and discussion section, Dead Time Measurement and Correction.

Sensitivity Analysis

Another important goal of this study was to theorize the minimum amount of tracer one would need to add to a given medium in order to accurately determine the tracer activity. In this case for the ER salt, a preliminary examination was performed to ascertain what quantity of Na22 would be needed in order to accurately determine the mass of the molten salt within the ER.

To do this, a simulation package known as Monte-Carlo N-Particle, or MCNP, was used to perform a “pulse height tally”. This MCNP model [Appendix item 2] was created in accordance with the MCNP manual [18] using methodology described in [19]. A representative HPGe Detector was created using the procedure outlined in [20], and modified to meet the dimensions and environment most closely resembling the

OSURR GRSS. A representative disc source was modeled 7.65 cm from the base of the detector. This simulation was run for both Na22 and Eu154 until 100 million particles were tracked, which passed MCNP’s

10 statistical checks. This data could then be examined in a standard spreadsheet program to examine the photopeak properties of the simulated HPGe detector at 1274.5 keV. By varying the activity of Na22, more pulse height tallies could be created and compared, and were used to examine the statistics of the 1274.5 keV photopeak, in terms of what fraction of counts in that channel could be attributed to each isotope.

Results and Discussion

Radioactive Tracer Dilution Results

Preliminary Results

Following counting, every weight for every corresponding crucible was plotted using SigmaPlot

(Systat Software Inc.) where activity vs. mass, and specific activity vs. mass was to be observed. If linearity was preserved for activity vs. mass, and that specific activity vs. mass, or concentration, was constant for all measured masses, one could conclude the same trends found in [14] hold true for a larger salt mass. It is important to note here that the approximate 5, 10, 20, and 40g masses were measured in the alumina crucibles, and the total mass, 122 g, was measured in the glassy carbon crucible. The preliminary results for each added isotope present in the salt are listed and discussed below.

Table 3: Summary of Na22 activity measurements and uncertainties

Figure 8: Na22 (tracer isotope) mass vs. activity comparison with trend line.

Figure 9: Na22 (tracer isotope) mass vs. specific activity.

Table 4: Summary of Eu154 activity measurements and uncertainties.

Figure 10: Eu154 (fission product) mass vs. activity comparison with trend line.

Figure 11: Eu154 (fission product) mass vs. specific activity.

Table 5: Summary of Cs137 activity measurements and uncertainties.

Figure 12 Cs137 (fission product) mass vs. activity comparison with a trend line.

Figure 13: Cs137 (fission product) mass vs. specific activity.

The above data in Figure 8, Figure 10, and Figure 11 show a strong linear trend and correlation for Na22, Cs137, and Eu154 respectively regarding mass and measured activity. Measured weight uncertainties were, relatively speaking, much smaller than the total mass measured. These weight measurements were accurate to ± 0.001 g per the manufacturer’s guidelines [21]. Activity uncertainties

19 were calculated using the GENIE-2000 software [22]. This calculation assumes a typical Gaussian or

Poisson distribution, where, in radiation detection, the uncertainty is simply the square root of the total number of counts during the entire counting period. This uncertainty is noticeably higher for Na22 measurements, since the combination of the 1274.5 keV peak from Eu154 needs to be subtracted before uncertainty can be calculated. Because all three isotopes were counted at once, the counting times for each isotope were the same. Therefore, Na22 was the limiting factor, and was used to set the collection time since it would naturally have the highest uncertainty as described above. Statistics even with this obfuscation from Eu154 were still well within reason, averaging approximately ± 1.5% for Na22.

However, even though linear trends were strong enough to indicate a successful experiment,

Figure 9, Figure 11, and Figure 13 (specific activities for Na22, Cs137, and Eu154 measurements, respectively) showed a decrease in specific activities with increasing salt mass. Furthermore, the slope of the trend line in mass vs. activity relationships should theoretically be exactly that of the measured specific activity for the trend line’s respective isotope. This decreasing trend indicates potentially one of two things. First, that the tracer and other isotopes are not homogenously mixed throughout the LiCl-KCl salt medium, potentially proving that using RTD for a larger salt mass can lead to inaccurate results

This is likely not the case, since the trend of decreasing specific activity with increasing salt mass is predictable. This means that hypothetically, if a larger salt mass were measured (> 122 grams), that this larger mass will have a lower concentration than the smaller mass sample. This would not be the case if the Na22 tracer were not homogenously mixed within the salt medium. If this tracer were not evenly mixed throughout, there would be no correlation between results, meaning that this hypothetical, heavier salt mass could be of either higher or lower concentration than the lighter salt mass. So, this is likely not the case meaning that the more likely reason for this trend is that as the mass of salt within a crucible increases, so does the volume. With this expanding volume, photons emitted from the isotopes within

20 the salt are more likely to be attenuated, if not, blocked, before reaching the detector. This illustrates a

“Self-shielding effect” which has been extensively been observed and studied [23] [24] [25]

This reason is very similar to typical attenuation calculations used to determine shielding thickness and stands to reason that the trend observed with specific activity vs. mass are similar.

퐼 = 퐼푒

Eq. (2)

Where 퐼 corresponds to some initial flux, 휇 is a given materials mass attenuation coefficient, and 푥 corresponds to the shielding material thickness. This exponential decay function produces a similar trend to what is seen in these results. It also helps validate that the initial calibrations for the GRSS, which were performed using NIST point sources, would not hold up if a volumetric source were to be counted on this system. This is precisely the case when measuring these molten salt masses, indicating that some sort of correctional factor will need to be derived to provide more accurate results. Eq. 2 is far too simple to use for this correction, since it assumes the shielding material is not also a source with a certain specific activity. Therefore, a more complex integration was performed using MCNP validate that self-attenuation of the source was occurring, and to see if more accurate activity readings could be derived.

Self-Attenuation Validation

To validate this internal attenuation, a model similar to that described in the Sensitivity Analysis section was employed (see Appendix #4) with various changes made depending on which case was being simulated. For this set of simulations, a surface current tally (F1) was used to count the fraction of all photons hitting the detector, assuming the only source present was Cs137. It is important to note that only the Cs137 results were validated to simply show a proof of concept that MCNP could be used to correct for

21 improper initial detector calibrations. Both crucibles, alumina and glassy carbon, were modeled separately and run for both point source scenarios and respective volumetric sources (i.e. 5, 10, 20, and

40g sources for the alumina crucible model, and 122g for the glassy carbon crucible model). Volumes were calculated by dividing the measured mass by the density at room temperature for LiCl-KCl salt, which is given by the formula [26]:

휌(푇) = 2.0286 − (5.2676퐸 − 4)(푇)

휌(293°퐾) = 2.0286 − (5.2676퐸 −4)(293°퐾)

푔 휌 = 1.874 ,° 푐푚

Eq. (3)

Figure 14: Volumetric source shown in the MCNP’s Visual Editor. This particular instance

shows an alumina crucible containing 40 grams of salt.

The flux found for each point source was used as an absolute reference for each crucibles volume source.

The flux found for each volume source was divided by the reference point source flux found for the volume sources respective crucible. This factor was then multiplied by both the activity measurements and specific activity and plotted to show a stronger correlation. The results of this are summarized below.

Table 6: Summary of observed activities with MCNP calculated activity

Mass Observed Activity Corrected Activity Observed Sp. Activity Corrected Sp. Activity Correctional Factor (g) (nCi) (nCi) (nCi/g) (nCi/g) 4.967 1.029 415.000 427.200 83.551 86.008 10.017 1.026 789.000 809.822 78.766 80.845 19.999 1.102 1464.000 1613.464 73.204 80.677 40.164 1.213 2736.000 3318.955 68.121 82.635 122.396 1.228 7733.000 9498.014 63.180 77.601

Figure 15: MCNP calculated specific activities compared to the observed specific activities

These MCNP calculated factors produce a much more reasonable concentration trend, and increase the average specific activity of all measurements from 73.4 with a standard deviation of 7.26 nCi/g, to 81.6 with a standard deviation of 2.43 nCi/g, indicating that the MCNP concentrations are more tightly grouped, as expected. When the MCNP derived activities are plotted and a linear regression is performed, the R2 value increases from .9971 to .9992, and the slope more closely resembles that of the expected specific activity, increasing from 64.001 to 78.178.

These results can be further improved if the last data point in this series is removed. This is because this last data point was measured in the glassy carbon crucible, which as a much lower density than that of alumina. While MCNP should account for the difference in attenuation coefficients, reducing the amount of experimental setup variation further improves these results, as summarized below.

Table 7: Summary of statistical values with various corrective techniques.

Corrected Original Corrected (Alumina Only) Mean Concentration (nCi/g)(µ) 73.4 81.6 82.5 Std. Dev (σ) 7.26 2.43 2.14 Slope (m) 64.001 78.781 82.223 R^2 0.9971 0.9992 0.9996

Figure 16: Adjusted activities for alumina crucible measurements only.

The above data shows that even with an improper initial calibration on a detection system, MCNP can be used to accurately accommodate for this by applying correctional factors derived from MCNP.

Dead Time Measurement and Correction

Another main goal of this study was to determine if these statistics and accuracy could be maintained with significantly higher dead times. Dead time, or the time a detector system cannot make any counts, is a property of every detector and its respective instrumentation setup. While these counting losses from the dead time have significantly improved with the advent of new detection technologies [27]

[28] [29], there will always be a need to derive adequate corrective models for this phenomenon, where various methods have been extensively studied [30] [31] [32] . In most of these methods and explained in

[17], simple dead-time corrections can be made by utilizing a form of the paralyzable and non-paralyzable correction methods. The non-paralyzable method assumes a fixed dead time, and the fraction of dead time is simply the product of the dead time and the observed counts.

푛 − 푚 = 푛푚휏

Eq. (4)

Where 푛 is the true count rate, 푚 is the observed count rate, and 휏 is the dead time. Rearranging this for 푛 yields: 푚 푛 = 1− 푚휏 Eq. (5)

The paralyzable model assumes that dead time is not fixed, and is “extendable” based on the interaction rate, making a distribution of possible times that can be described as probabilities. The probability that an interval larger than 휏 , 푃(휏), is expressed by integrating all incremental probabilities,푃(푇) from 휏 to infinity:

푃(휏) = 푃(푇)푑푇 = 푒

Eq. (6)

Multiplying this solution by true rate yields the paralyzable approximation,

푚 = 푛푒

Eq. (7)

While these studies acknowledge that these corrective methods can only purely be applied to an ideal detector, the basis of many extensive models for real detectors is based on these methods. Most corrective models use a combination of these two methods and others to estimate real detector counting rates, which may not be necessary to derive for this phase of the experiment. Therefore, it was decided to assume an ideal detection setup, and apply the corrective methods to see if adequate correction could be achieved. These results for correcting Na22 counts are summarized below by using calculations shown by Eq. (5) and Eq. (7) .

Table 8: Summary of Na22 readings using the paralyzable and non-paralyzable methods of

dead time correction.1

Figure 17: Na22 activity corrections, utilizing both the paralyzable and non-paralyzable method.

1 Button sources of Cs137 were used to increase the Cs:Eu ratio for all measurements except the 3:1 measurement, which was the natural ratio created from the addition of liquid chloride sources described in the experimental procedure.

As seen in Figure 17 and Table 8 above, these ideal models can be used to correct for dead time incurred from higher activities. While further analysis should still be done to derive a more accurate model of dead time correction, these methods are sufficient for this setup.

Sensitivity study

A useful property to know with this method would be the minimum detectable amount, or MDA

[33], of tracer that would be needed to use RTD for this application. MDA is generally detector dependent

[34] and application dependent [35] [36]. Generally speaking, a statistically reasonable MDA should be known by every detector operator. However, for RTD in LiCl-KCl salt used for pyroprocessing, an MDA for

Na22 can vary because of the presence of Eu154, and the amount of variation of activities of other isotopes present in the salt. This is shown in both the Mk IV and Mk V salt, which are used for the same purpose, yet the ratios of Cs to Eu vary drastically. These two factors, and others discussed in previous sections, make it particularly difficult for one to determine the exact MDA for Na22 for use with this process.

However, if the activity of Eu154 is known, a relative ratio for Na22: Eu154 can be hypothetically approximated by using the same MCNP setup as before (see Appendix 2). Determining this ratio can be done by determining what percentage of the overall photopeak is composed of both Eu154 and Na22. For instance, if the operator desires that the ratio of tracer to Eu154 creates a photopeak that is 99% tracer isotope, then statistically, an approximate activity of tracer can be determined. This percentage, 99%, should be user defined based on the calculations the operator’s gamma spectroscopy system uses to determine activity. Since different software packages use different methods to determine isotope activity, this number is something that should be user defined. A few hypothetical ratios of Na22: Eu154 were tested and plotted below.

1.00E+05 .5:1 Na to Eu Partial Spectrum

1.00E+04 ~70% of peak is Na22

1.00E+03

1.00E+02

1.00E+01 Sum

154 Counts (a.u.) Counts EuEu 1.00E+00 Na22Na22

1.00E-01

1.00E-02

1.00E-03 1.26 1.27 1.28 1.29 1.3 Energy (MeV)

Figure 18: Hypothetical gamma spectrum from a .5:1 ratio of Na22: Eu154 showing that the

overlapping photopeak is comprised of approximately 70% Na22 counts.

1.00E+05 5:1 Na to Eu Partial Spectrum

1.00E+04 ~96% of peak is Na22

1.00E+03

1.00E+02

1.00E+01 Sum

Counts (a.u.) Counts EuEu154 1.00E+00 Na22Na22

1.00E-01

1.00E-02

1.00E-03 1.26 1.265 1.27 1.275 1.28 1.285 1.29 1.295 1.3 Energy (MeV)

Figure 19: Hypothetical gamma spectrum from a 5:1 ratio of Na22: Eu154 showing that the

overlapping photopeak is comprised of approximately 96% Na22 counts.

Using MCNP shows that relatively small ratios of Na22 to Eu154 can lead to the tracer being the dominant composition, and can further be increased so that essentially all counts in this overlapping region are from the tracer, making this MDA for Na22 user defined. For some applications, the total activity of the added tracer may not matter, but for others, using the smallest activity possible is desirable. Each case should be considered carefully and in regards to the application. This ambiguity truly makes the MDA for the tracer user defined. Future work should comprise of a more detailed sensitivity study, using methods described in other studies [35] [36]. In this study, a ratio of 1:3 Na22 to Eu154 (less than simulated above) was accurate enough to ensure a linear trend between salt mass and measured activity.

Summary

Conclusions

Radioactive Tracer Dilution was successfully performed on a larger salt mass at The Ohio State

University’s Nuclear Analysis and Radiation Sensing laboratory. Despite increasing the overall mass of the

LiCl-KCl salt used, tracer behavior was unaffected, and could still mix homogenously in the salt medium without the need for stirring. Because of this, a linear relationship between salt mass and measured activity was repeated, demonstrating the validity of previous work and potential for future use of

Radioactive Tracer Dilution for salt mass measurement applications for salt masses up to 122 grams. Self-

Shielding affects will be prevalent in larger sample sizes, however, MCNP was used to validate this effect.

When applied to the nuclide Cs137, the slope of a linear regression and the average specific activity were in agreement with each other to within 1%. Artificially increased dead times from Cs button sources did show a decrease in measured activity with increasing dead time, however; assuming an ideal detector setup and using paralyzable and non-paralyzable corrective measures could accommodate for lost data due to dead times up to 16% introduced by Cs137:Eu154 ratios of 170:1. Lastly, while determining a minimum detectable ammount of tracer for this application is challenging, ratios as small as 1:3 Na22 to

Eu154 can be used to determine salt mass accurately.

Future Work

Future work should be continued to ensure the accuracy of Radioactive Tracer Dilution for use in a highly radioactive environment, such as that exhibited in the salt used in an electrorefiner for pyroprocessing. Future studies should include additional fission product isotopes, to more closely mimic the intended end-usage environment. Not only could this help ensure the accuracy of Radioactive Tracer

Dilution in more radioactive environments, but the additional isotopes would help create a higher detector dead time and could potentially be used to show the accuracy of the outlined correction methods at higher dead times. Additionally, higher Cesium activities should be used to more closely recreate the ratios that would be found in electrorefiner salt used for pyroprocessing. Lastly, a more detailed sensitivity study should be performed, which could provide more insight into what the minimum amount of tracer isotope would be to ensure accurate salt mass calculations.

References

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[2] T. Mancini, "Advantages of using molten salt," Sandia National Labs, 10 January 2006. [Online]. Available: https://www.webcitation.org/60AE7heEZ?url=http://www.sandia.gov/Renewable_Energy/solarth ermal/NSTTF/salt.htm. [Accessed 6 March 2018].

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[4] C. E. Till and Y. I. Chang, Plentiful Energy, The Story of the Integral Fast Reactor, 2011.

[5] Y. I. Chang, "Technical Rationale for Metal Fuel in Fast Reactors," Argonne National Laboratory, Argonne, 2007.

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[7] R. W. Benedict, A. M. Yacout, D. Vaden, K. M. Goff and R. W. Keyes, "Material Accountancy in an Electrometallurgical Fuel Conditioning Facility," Argonne National Laboratory, Argonne, 1996.

[8] P. L. Lafreniere, D. S. Rappleye, R. O. Hoover, M. F. Simpson and E. D. Blandford, "Demonstration of Signature-Based Safeguards for Pyroprocessing as Applied to Electrorefining and the Ingot Casting Process," Nuclear Technology, vol. 189, no. 2, 2015.

[9] H. E. Garcia, M. J. Lineberry, S. E. Aumeir and H. F. McFarlane, "Proliferation Resistance of Advanced Sustainable Nuclear Fuel Cycles," in Proceedings of institute of nuclear material management (INMM) annual meeting, Phoenix, 2003.

[10] A. M. Orechwa and R. G. Bucher, "Fuel conditioning facility electrorefiner," in American Nuclear Society Topical Meeting on DOE Spent Nuclear Fuel and Fissile Materials Management, 1996.

[11] R. D. Mariani and D. E. Vaden, "Modeled Salt Density for Nuclear Material Estimation in the Treatment of Spent Nuclear Fuel," Journal of Nuclear Materials, vol. 404, no. 1, pp. 25-32, 2010.

[12] V. Teknilinen and E. Tutkimuskeskus, "Flow-Rate Measurement Using Radioactive Tracers and Transit Time Method," International Atomic Energy Agency, INIS, 1986.

[13] A. M. Yacout, R. G. Bucher and Y. Orechwa, "Fuel Conditioning Facility Material Accountancy," Argonne National Laboratory, Argonne, 1995.

[14] L. Cao, J. Jarrell, S. White, K. Herminghuysen, A. Kauffman, D. E. Hardtmayer, J. Sanders and S. Li, "A Radioactive Tracer Dilution Method to Determine the Mass of Molten Salt," Journal of Radioanalytical Chemistry, vol. 314, no. 1, pp. 387-393, 2017.

[15] Idaho National Laboratory, "Mk-IV and Mk-V ER Salt Fractions," Idaho Falls.

[16] The Ohio State University, "Radiation Safety Standards for The Ohio State University," Environmental Health and Safety office at The Ohio State University, Columbus, 2018.

[17] G. F. Knoll, Radiation Detection and Measurement, Fourth Edition, Ann Arbor: John Wiley & Sons, Inc., 2010.

[18] Oak Ridge National Laboratory, "RSICC Computer Code Collection, MCNP6.1/MCNP5/MCNPX," Radiation Safety Information Computaional Center, Oak Ridge, 2013.

[19] J. K. Shultis and R. Faw, "An MCNP Primer," Kansas State University , Manhattan, 2011.

[20] C. C. Conti, I. P. Salinas and H. Zylberberg, "A Detailed Procedure to Simulate an HPGe Detector with MCNP5," Progress in Nuclear Energy , vol. 1, no. 66, pp. 35-40, 2013.

[21] Intelligent-Lab, "Intelligent-Lab Milligram Balance," [Online]. Available: https://www.intelligentwt.com/wp-content/uploads/2016/06/PMW-320-Data-Sheet.pdf. [Accessed 09 03 2018].

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[23] D. Sahin and K. Unlu, "Determination of Self Shielding Factors and Gamma Attenuation Effects for Tree Ring Samples," Journal of Radioanalytical and Nuclear Chemistry , vol. 291, no. 2, pp. 549- 553, 2011.

[24] M. Fujita and T. Noda, "Nuclear Reactions and Self-Shielding Effects of Gamma-Ray Database for Nuclear Materials," National Research Institute for Metals, Tsukuba, Ibaraki.

[25] A. M. Khater and Y. Y. Ebaid, "A Simplified Gamma-Ray Self-Attenuation Correction in Bulk Samples," Applied Radiation and Isotopes, vol. 66, pp. 407-413, 2007.

[26] K. Sridharan, "Thermal Properties of LiCl-KCl Molten Salt for Nuclear Waste Separation," University of Wisconsin-Madison, Madison , 2012.

[27] M. Yousaf, S. Akyurek and S. Usman, "A Comparsion of Traditional and Hyprid Radiation Detector Dead-Time Models and Detector Behavior," Progress in Nuclear Energy , vol. 83, pp. 177-185, 2015.

[28] G. Grida, S. Castelletto, I. P. Degiovanni, C. Novero and M. L. Rastello, "Quantum efficiency and dead time of single-photon counting photodiodes: a comparison between two measurement techniques," Metrologia, vol. 37, no. 5, pp. 625-628, 2000.

[29] J. S. Glaser and D. Reusch, "Comparison of deadtime effects on the performance of DC-DC converters with GaN FETs and silicon MOSFETs," in Energy Conversion Congress and Exposition , Milwaukee, 2016.

[30] E. Mendoza , D. Cano-Ott, C. Guerrero and E. Berthoumieux, "Pulse Pile-Up and Dead Time Corrections for Digitzed Signals from a BaF2 Calorimeter," Nuclear Instruments and Methods in Physics Research A, vol. 768, pp. 55-61, 2014.

[31] L. Abbene and G. Gaetano, "High-Rate Dead-Time Corrections in a General Purpose Digital Pulse Processing System," Journal of Synchrotron Radiation, no. 22, pp. 1190-1201, 2015.

[32] S. M. Karabidak, "Dead Time in Gamma Spectrometry," INTECH, 2017.

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[35] J. I. McIntyre, T. W. Bowyer and P. L. Reeder, "Calculation of Minimum Detectable Concentration Levals of Radioxenon Isotopes using the PNNL ARSA System," Pacific Northwest National Laboratory , Richland, 2006.

[36] M. J. Davis, "Measurement Uncertainties and Minimum Detectable Concentrationsfor the in-situ NaI Gamma Spectroscopy Systems Used at Fernald," Argonne National Laboratory, Argonne, 2004.

Appendix: Supplemental Information

1. MATLAB script for Dead Time Corrections 2. clc 3. clear 4. syms n % set "n" as an independent variable 5. m=52; % Recorded activity in nCi 6. t= 16e-4; % Recorded dead time __%__E-4, this is for 16% DT 7. P= n*exp(-n*t); % non-paralyzable model 8. NP=n/(1+n*t); % non-paralyzable model 9. ll=0; %plotting limits, used for trimming 10. ul=100; 11. 12. fplot(NP,[ll ul]); %plot non paralyzable model 13. hold on 14. fplot(P,[ll ul],'k'); %plot paralyzable model 15. hold on 16. fplot(m,[ll ul]) %plot observed value (in nCi) 17. hold off 18. eqn1= P==m; 19. para=vpasolve(eqn1,n,[ll ul]) % paralyzable corresponding value 20. eqn2= NP==m; 21. nonpara=vpasolve(eqn2,n,[ll ul]) % Non-paralyzable corresponding value

2. MCNP Sample Input Deck for Gamma Spectroscopy MCNPX Visual Editor Version X_24E

1 1 -5.36 ((1 -3 -5 ):(3 -4 -6 ):-9 )#2 #4 #5 $ crystal

2 0 ((1 -2 -7 ):(2 -8 ))#5 $crystal hole

3 0 (21 -31 -27 )#1 #2 #4 #5 $vacuum

4 1 -5.36 (1 -11 -5 7 ):(11 -5 12 -3 ):(3 -9 12 ):(11 7 -13 -2 ):

(2 8 -14 )

5 5 -2.7 (1 -22 -25 ):(1 -4 5 -26 ):(20 -21 -28 ):(21 -24 27 -28 ):

(23 -24 29 -27 )

6 6 -1.85 31 -23 -27 $ Be window

7 4 -0.93 (43 -42 28 -44 ):(42 -41 -44 ) $plastic cover

101 2 -0.00127 -100 #1 #2 #3 #4 #5 #6 #7 $surrounding

102 8 -8.96 100 -200 #1 #2 #3 #4 #5 #6 #7 #101 $copper lining

103 7 -11.3 200 -300 $lead shielding

203 0 300

c crystal

1 px 0

2 px 5.17

3 px 5.35

4 px 6.35

5 cx 3.2

6 cx 2.2

7 cx 0.7

8 sx 3.9 1.45

9 tx 5.35 0 0 2.2 1 1 c dead layer

11 px 0.056

12 cx 3.1 $external surface

13 cx 0.8 $ hole

14 sx 3.9 1.5 c Aluminum Casing

20 px -0.6 $ external base of casing

21 px -0.5 $ internal base of casing

22 px 5.3 $ electrical contact

23 px 6.85 $ internal top of casing

24 px 6.95 $ external top of casing

25 cx 0.2 $ electrical contact

26 cx 3.3 $ cup

27 cx 4.025 $ internal casing

28 cx 4.125 $ external casing

29 cx 3.125 c Beryllium

31 px 6.75 c Plastic Cover

41 px 5 $ base

42 px 7.25 $ internal top

43 px 7.5 $ external top

44 cx 4.5 $ radius

100 rcc -0.7 0 0 35.3 0 0 11.43

200 rcc -1.7 0 0 37.4 0 0 12.53

300 rcc -10.7 0 0 57.4 0 0 22.53

mode p e m1 32000.02p 1 $germanium m2 7000.02p -0.755636 $air (US S. Atm at sea level)

8000.02p -0.231475 18000.02p -0.012889 m3 1000.02p -0.111915 $Water (density of 1 assumed)

8000.02p -0.888085 m4 1000.02p -0.143711 $polyethylene

6000.02p -0.856289 m5 13000.02p -1 $aluminum m6 4000.02p -1 $beryllium metal m7 82000.02p 1 $lead m8 29000.02p 1 $copper imp:p 1 9r 0 $ 1, 203 imp:e 1 9r 0 $ 1, 203 phys:p phys:e sdef cel 101 pos= 7.65 0 0 rad=d1 ext=0 axs= 1 0 0 erg=1274.5 par=2 wgt=1

38 si1 0 2.25

*f8:p,e 1 fu8 0000132000.00005 $compton scattering ft8 geb 0.0011265 0.0012670 0.00127429 e8 0 2048i 2.5 nps= 1e6 mphys

3. Weight Measurements for Each Crucible and Salt Addition Glassy Carbon Cruicible + Tracer Tracer Addition+ Empty GC weight g Average Average Average Salt AdditionSalt + Tracer Tracer Addition Crucible+Salt 1 67.030 67.044 189.426 2 67.02767.029 67.042 67.042 0.012 189.425 189.4256667 122.384 122.396 3 67.031 67.039 189.426

Pre Melt Al2O3-1 Weight Tracer+Sal Measure Calculated Average Average Post Heating Average post-pre (g) t Addition (Cruicible + Addition Tracer + Salt) 1 124.538 129.531 129.528 2 124.532 129.538129.529 5.018 129.529 129.527 3 124.498 129.519 129.525 -0.002 4 124.492 124.511 5.016 5 124.476 6 124.480 7 124.560 Al2O3-2 Pre Melt Weight Tracer+Sal Measure Calculated Average Average Post Heating Average post-pre (g) t Addition (Cruicible + Addition Tracer + Salt) 1 124.596 134.965 134.596 -0.054 2 124.937 134.943134.944 10.071 134.945 134.889 3 124.936 134.923 134.937 124.872 9.961 4 124.924 134.965 5 124.911 134.950 6 124.930 134.943 Al2O3-3 Pre Melt Weight Tracer+Sal Measure Calculated Average Average Post Heating Average post-pre (g) t Addition (Cruicible + Addition Tracer + Salt) 1 144.610 164.577 164.590 0.000 2 144.572 164.591164.585 19.999 164.578 164.585 3 144.606 164.586 164.586 144.585 19.992 4 144.598 5 144.567 6 144.559 Al2O3-4 Pre Melt Weight Tracer+Sal Measure Calculated Average Average Post Heating Average post-pre (g) t Addition (Cruicible + Addition Tracer + Salt) 1 137.613 177.775 177.767 0.004 2 137.597 177.750177.759 40.161 177.763 177.763 3 137.571 177.753 177.759 137.599 40.182 4 137.622 5 137.608 6 137.582 Al2O3-5 Pre Melt Weight Tracer+Sal Measure Calculated Average Average Post Heating Average post-pre (g) t Addition (Cruicible + Addition Tracer + Salt) 1 115.971 121.029 120.942 -0.063 2 115.973 120.989121.004 5.030 120.937 120.941 3 115.956 121.004 120.943 115.974 5.008 4 115.995 121.004 5 115.972 121.000 6 115.974 120.996

4. MCNP Input Deck for Attenuation Correction

1 1 -5.36 ((1 -3 -5 ):(3 -4 -6 ):-9 )#2 #4 #5 $ crystal

2 0 ((1 -2 -7 ):(2 -8 ))#5 $crystal hole

3 0 (21 -31 -27 )#1 #2 #4 #5 $vacuum

4 1 -5.36 (1 -11 -5 7 ):(11 -5 12 -3 ):(3 -9 12 ):(11 7 -13 -2 ):

(2 8 -14 )

5 5 -2.7 (1 -22 -25 ):(1 -4 5 -26 ):(20 -21 -28 ):(21 -24 27 -28 ):

(23 -24 29 -27 )

6 6 -1.85 31 -23 -27 $ Be window

7 4 -0.93 (43 -42 28 -44 ):(42 -41 -44 ) $plastic cover

101 2 -0.00127 -100 -502 #1 #2 #3 #4 #5 #6 #7 #204 #205 $air

102 8 -8.96 100 -200 -501 #1 #2 #3 #4 #5 #6 #7 #101 #204 $copper li

#205

103 7 -11.3 200 -300 -501 $lead shielding c Crucible

204 10 -3.95 -301 302 c Molten Salt

205 9 -1.875 -401 -302

206 2 -0.00127 -502 300 100 -501 #1 #2 #3 #4 #5 #6 #7

207 2 -0.00127 -502 501 100 #1 #2 #3 #4 #5 #6 #7 $atmos c vacuum void

208 0 502 #1 #2 #3 #4 #5 #6 #7 $void

c crystal

1 px 0

2 px 5.17

3 px 5.35

4 px 6.35

5 cx 3.2

6 cx 2.2

7 cx 0.7

8 sx 3.9 1.45

9 tx 5.35 0 0 2.2 1 1 c dead layer

11 px 0.056

12 cx 3.1 $external surface

13 cx 0.8 $ hole

14 sx 3.9 1.5 c Aluminum Casing

20 px -0.6 $ external base of casing

21 px -0.5 $ internal base of casing

22 px 5.3 $ electrical contact

23 px 6.85 $ internal top of casing

24 px 6.95 $ external top of casing

25 cx 0.2 $ electrical contact

26 cx 3.3 $ cup

27 cx 4.025 $ internal casing

28 cx 4.125 $ external casing

29 cx 3.125 c Beryllium

31 px 6.75 c Plastic Cover

41 px 5 $ base

42 px 7.25 $ internal top

43 px 7.5 $ external top

44 cx 4.5 $ radius

100 rcc -0.7 0 0 80.6 0 0 11.43

200 rcc -1.7 0 0 82.7 0 0 12.23

300 rcc -10.7 0 0 102.7 0 0 22.53 c crucible

301 trc 52.25 0 0 6.8 0 0 1.75 2.9 $exterior

302 trc 52.55 0 0 6.8 0 0 1.45 2.6 $interior c Salt Level

401 px 55.0141 c Cave Height

501 px 35.3 c Atmos limit

502 so 65

mode p imp:p 1 13r 0 $ 1, 208 m1 32000.02p 1 $germanium m2 7000.02p -0.755636 $air (US S. Atm at sea level)

8000.02p -0.231475 18000.02p -0.012889 m3 1000.02p -0.111915 $Water (density of 1 assumed)

8000.02p -0.888085 m4 1000.02p -0.143711 $polyethylene

6000.02p -0.856289 m5 13000.02p -1 $aluminum m6 4000.02p -1 $beryllium metal m7 82000.02p 1 $lead m8 29000.02p 1 $copper m9 3000.02p -0.22 $LiCl-KCl

19000.02p -0.28 17000.02p -0.5 m10 13000.02p 3 $Alumina

8000.02p 2

43 phys:p sdef x=d1 y=d2 z=d3 erg=.6617 par=2 cel=205 si1 52 56 sp1 0 1 si2 -3 3 sp2 0 1 si3 -3 3 sp3 0 1 f1:p 1 ctme 60 mphys

5. Liquid Source Handling Procedure from OSURR Staff