We propose instrumental neutron activation analysis for rapid analysis of used nuclear fuel suitable for modern forensics applications and as a complementary technique to bolster results obtained by mass spectroscopy. Two samples of noble metal phase from high burnup commercial used nuclear fuel dissolved in carbonate-peroxide solution and nitric acid were studied using neutron activation analysis. Stable and quasi-stable nuclides were identified and characterized. Mass quantities of Mo-98, Mo-100, Ru-102, Ru-104, Rh-103, I-127, I-129, and Te-130 are reported with associated uncertainties and an average uncertainty budget is presented. Differences in iodine quantities between samples are discussed in relation to elemental fractionation effects of UO2 dissolution via carbonate-peroxide solution versus nitric acid.

1. Measuring the Isotopic Composition of Extracted Noble
Metal Phase from Used Nuclear Fuel
R.I. Palomares, K. Dayman, S. Biegalski, S. Landsberger
Nuclear Engineering Teaching Laboratory
Nuclear and Radiation Engineering Program
The University of Texas at Austin
Research Report
March 2013

2. 2
Abstract
We propose instrumental neutron activation analysis for rapid analysis of used nuclear fuel suitable for
modern forensics applications and as a complementary technique to bolster results obtained by mass
spectroscopy. Two samples of noble metal phase from high burnup commercial used nuclear fuel
dissolved in carbonate-peroxide solution and nitric acid were studied using neutron activation analysis.
Stable and quasi-stable nuclides were identified and characterized. Mass quantities of 98
Mo, 100
Mo, 102
Ru,
104
Ru, 103
Rh, 127
I, 129
I, and 130
Te are reported with associated uncertainties and an average uncertainty
budget is presented. Differences in iodine quantities between samples are discussed in relation to
elemental fractionation effects of UO2 dissolution via carbonate-peroxide solution versus nitric acid.

3. 3
Introduction
Overview
There is current interest in developing rapid analysis techniques to characterize used nuclear fuels
for nuclear safeguard and accountancy purposes. At present, nuclide composition data of used fuels are
being collected to expand upon a Spent Fuel COMPOsition (SFCOMPO) database to develop intrinsic
signatures for nuclear forensics [1]. The SFCOMPO database would provide information for comparing
unknown nuclear materials with qualified sets of nuclide compositions to allow for the determination of
material origin. Enhancements to qualified data sets might ultimately allow for signature development to
characterize material via reactor type, age, and possibly even operating conditions.
This research is part of a collaborative scoping study to investigate Neutron Activation Analysis
(NAA) for measurement of used nuclear fuel inventories. NAA has been historically utilized for the
quantitative measurement of fission products such as 129
I [2-4]; however, there has been limited
application of these methods towards isotopic characterization of used nuclear fuel and similar activation
techniques have fallen out of favor in light of more recent development and maturation of techniques such
as mass spectroscopy. We propose NAA as a technique for the analysis of trace analytes in UNF both as
an approach to rapid analysis suitable for modern forensics applications and as a complementary
technique that can bolster the results obtained by mass spectroscopy during the attribution process.
Neutron Activation Analysis (NAA)
NAA provides several advantages over other analysis techniques such as alpha, beta, and gamma
spectroscopy and mass spectrometry. NAA is dependent on activation products as opposed to analytes
that may or may not produce signals, e.g. gamma rays, in sufficient quantities to be observable above
background. Activation to shorter-lived radionuclides with high specific activity and signal outputs allows
NAA to be used to detect stable and long-lived nuclides (whose very slow to nonexistent decay rates
provide difficulty for passive spectroscopy techniques). NAA is able to quantify multiple nuclides in a
single experimental run and is also non-destructive; therefore, samples that retain high analyte to
activation product ratios may be deemed reusable for analysis after sufficient decay time has elapsed.
Lastly, analysis by NAA is relatively rapid in comparison to destructive techniques such as mass
spectrometry. No pre-chemistry is necessary and analysis is independent of sample phase. Samples may
be liquid or solid and sample processing capacities may be optimized when using tools such as automated
pneumatic and cyclic irradiation methods. With calibrated analysis systems in place, hundreds of samples
may be analyzed in reasonably short timeframes.

4. 4
Samples
The University of Texas at Austin received two samples from Pacific Northwest National
Laboratory (PNNL) in November, 2012. Sample descriptions were provided by PNNL [5]. The samples
consist of noble metal phase chemically separated from high-burnup commercial UO2 fuel (Approved
Testing Material 109) [6]. ATM 109 was produced using fuel irradiated in reactor I at the Quad Cities
nuclear power plant (NPP). Fuel was fabricated by General Electric for use in 7×7 assemblies. Fuel was
3.0 % enriched and irradiated between February 1979 and September 1987 and again between November
1989 and September 1992 with an approximate burnup of 67 MWd/kgU - 70 MWd/kgU. As of early
2013, fuel has been cooling for approximately 21 years.
The noble metal phase is an alloy of metallic molybdenum, technetium, ruthenium, rhodium, and
palladium. Particles up to a few microns in diameter were recovered from used fuel, slurried in water, and
placed in polyethylene vials. Slurries were then dried into opaque crusts at the bottom of the vials.
Samples differ only by chemical solvent used to dissolve the UO2. The first sample (sample C) was
prepared from used fuel dissolved in an ammonium carbonate and hydrogen peroxide solution whereas
the second sample (sample N) was prepared from used fuel dissolved in nitric acid. Actinides and other
fission products in solution were chemically separated from the undissolved noble metal phase but
quantities of fission products and transuranic elements remain. Sample C weighs approximately 0.8 mg
and sample N weighs approximately 2.0 mg.
Sample N was examined to estimate intrusive fission product quantities [5]. Total plutonium
content was estimated at approximately a microgram. Total uranium content was estimated at no more
than ten micrograms and 235
U content was estimated to be very low due to very high fuel burnup. Noble
metal phase was estimated to be ten to twenty percent 99
Tc (~7μg in sample N). 90
Sr was reported to be in
approximately equal ratio to 137
Cs. The sample was also counted for measurement of gamma emitters.
Activities of intrusive fission products, in microcuries, with one sigma counting uncertainties are
presented in Table I.

5. 5
Table I. Intrusive Fission Products: Listed are the highest activity actinide and non-
noble metal fission products present in the noble metal phase samples. Not listed is 90
Sr,
although it was reported by PNNL that the ratio to 90
Sr to 137
Cs was approximately one.
Nuclide Activity (µCi) Uncertainty
60
Co 1.88E-1 ± 2%
125
Sb 5.77E-1 ± 2%
126
Sn 1.69E-2 ± 25%
134
Cs 4.09E-2 ± 2%
137
Cs 2.01E+1 ± 2%
154
Eu 1.28E-1 ± 6%
155
Eu 4.91E-2 ± 10%
241
Am 1.45E-1 ± 6%
Method
1. Experiment
Planning
Analysis was performed to determine viable NAA candidate nuclides and likely noble metal
composition of the samples. Technetium-99 and all ground state and isomeric isotopes of palladium (102-
110), rhodium (103-105), ruthenium (96-106), and molybdenum (92-100) were considered. NAA is
dependent on observation of activation products; therefore, nuclides whose activation products do not
emit gamma rays and/or are stable or quasi-stable (very long-lived) were considered to be poor candidates
for analysis by NAA. Moreover, activation products must emit gamma rays at a rate observable above
background. Thus, a gamma ray intensity threshold for activation products was set at one percent
(although limits may vary depending on the sensitivity of the spectrometer, background of the facility,
and/or sample). Thirteen noble metal nuclides were identified as candidates suitable for analysis via
NAA.
Sample composition was then estimated to determine whether the aforementioned candidates are
likely to be present in samples obtained from PNNL. This analysis was based on fission yields and decay
chains. The samples are derived from used fuel that has been cooling for approximately 21 years;
therefore, the samples are composed of nuclides in secular equilibrium with long-lived parent nuclides,
stable nuclides, or quasi-stable nuclides.
Focus was shifted towards stable and quasi-stable noble metals at the end of high-yield fission
product decay chains. Fission yields were obtained from ENDF data [7]. Noble metals with short half-
lives that decay to non-noble metal stable or quasi-stable states were eliminated from further
consideration. Stable and quasi-stable noble metal nuclides not associated with the decay of high yield

6. 6
fission products were also eliminated from further consideration. Table II displays all NAA candidate
nuclides predicted to be in the samples.
Table II. Candidate Nuclides: Listed are all noble metal nuclides identified as viable
NAA candidates and predicted to be present in extracted noble metal phase from used
fuel as determined by fission yield and decay chain analysis. All but 99
Tc and 100
Mo are
stable analytes. Half-lives of 99
Tc and 100
Mo are approximately 2×10%
years and 1×10&'
years, respectively.
Unactivated
Analyte
Observable Activation
Product(s)
Highest Intensity Gamma
Ray(s) of Activation Product(s)
Half-Life of
Activation Product(s)
98
Mo 99
Mo 12% 65.94 H
100
Mo 101
Mo 19% 14.61 M
99
Tc 100
Tc 7% 15.80 S
102
Ru 103
Ru 91% 39.26 D
104
Ru 105
Ru 47% 4.44 H
103
Rh 104
Rh, 104m
Rh 2%, 48% 42.30 S, 4.34 M
106
Pd 107m
Pd 48% 21.30 S
108
Pd 109
Pd, 109m
Pd 4%, 56% 13.70 H, 4.70 M
Having identified target nuclides, focus was shifted towards optimization of experimental
parameters. Near-optimal irradiation time1
was derived using activation product activity calculations.
Radiative capture cross sections were coupled with neutron flux profiles to estimate activation activities
using the expression:
𝐴)(𝑡,--) = 𝑁, 𝜑 𝜎, (1 − 𝑒678 9:;;), (1)
where φ is the average neutron flux during irradiation; Ni and σi are the number density and radiative
capture cross section of the unactivated analyte, respectively; tirr is the irradiation time; and λj and Aj are
the decay constant and activity of the activation product, respectively. Cross sections used here were
radiative capture cross sections at 0.0253 eV obtained from Kaeri [8]. Number densities were unknown
therefore expressions were normalized by number density of the analyte in order to obtain specific
activities as functions of irradiation time.
Specific activities for all candidate nuclides and intrusive fission products with appreciable cross
sections (e.g. 154
Eu, 134
Cs) were plotted as a function of irradiation time. Activation products of intrusive
fission products were included due to peak interference concerns with noble metal activation products.
Nuclides with the lowest induced specific activities are presented in Figure 1. Estimated ruthenium and
molybdenum induced specific activity was the lowest of all candidate noble metals and are limiting
factors for near-optimal irradiation time determination. Since production was relatively linear for the short
1
Optimal experimental parameters would be unique to each nuclide analyzed. An experimental protocol, e.g. timing
and neutron spectrum, was chosen to provide suitable analysis of all nuclides of interest and are deemed near-
optimal.

7. 7
irradiation times as shown in Figure 1, it was predicted that molybdenum and ruthenium production
would be approximately similar for any irradiation time less than one hour via linear extrapolation. The
decision was thus made to keep the irradiation time as short as possible to prevent buildup of actinide and
undesirable fission product (e.g. 154
Eu) activation products. An irradiation time of 3 minutes was deemed
sufficient to produce observable gamma-ray emission rates.
Figure 1. Irradiation Plot for Lowest Induced Activities: Specific activities of
activation products of noble metal candidates and intrusive fission products in samples
were plotted as a function of irradiation time to determine near-optimum irradiation time.
Noble metal and undesirable fission product nuclides not shown had estimated activities
greater than the scale shown. Nuclides with lowest induced activities were of most
importance as they limit near-optimal irradiation time determination.
Irradiation and counting
Prior to irradiation, passive counts were obtained to establish a baseline to which post-irradiation
spectra could be compared. Pre-irradiation spectra indicated no presence of noble metals; only fission
products presented in Table I were observed. Samples C and N were irradiated for three minutes at 500
kW in a thermal neutron flux at the University of Texas TRIGA Mk-II research reactor using a pneumatic
irradiation system (tPNT facility). Counting was performed using an HPGe detector system.

8. 8
Samples were allowed to decay for three minutes prior to initial counts as initial detector dead
times immediately after irradiation were approximately 90% and 99% for samples C and N, respectively.
Longer source-detector distances (14cm) were used in cases of high detector dead times. Once dead times
subsided to ≤ 20%, shorter (9 cm) geometries were used. It was expected that short-lived activation
products would be masked by larger peaks from high activity nuclides such as 137
Cs. By utilizing shorter
decay and count times immediately after irradiation, masking effects from high activity fission products
were successfully mitigated. Summaries of count parameters are presented in Tables III and IV.
Table III. Sample C Count Times: Various decay and count times were used to
maximize identification of short-lived activation products. As decay time increased,
count time was allowed to increase. A longer source-detector distance was used for the
first two counts after irradiation to reduce detector dead time. Post-irradiation spectrum 7
was only used to confirm the presence of 103
Ru, which has a half-life of roughly 39 days.
Count Pre-Irr. Post 1 Post 2 Post 3 Post 4 Post 5 Post 6 Post 7
Count Time 1 H 2 M 5 M 15 M 1 H 4 H 6 H 4 H
Decay Time N/A 3 M 7 M 18 M 40 M 2 H 27 H 16 D
Geometry 9 cm 14 cm 14 cm 9 cm 9 cm 9 cm 9 cm 9 cm
Table IV. Sample N Count Times: An attempt was made to replicate experimental
parameters used for sample C but problems arose as a result of higher sample activity. As
a result of very high detector dead times, there were longer count real times to obtain
desired count live times. A longer source-detector distance was also used to mitigate
detector dead time.
Count Pre-Irr. Post 1 Post 2 Post 3 Post 4 Post 5 Post 6 Post 7
Count Time 2 H 1 M 5 M 15 M 1 H 4 H 6 H 4 H
Decay Time N/A 3 M 11 M 25 M 52 M 2.3 H 48 H 33 D
Geometry 9 cm 14 cm 14 cm 14 cm 14 cm 14 cm 14 cm 9 cm
Analysis
Identification
Spectral analysis was based on spectra comparison via reverse chronology. The first step was to
strip peaks associated with pre-irradiation spectra as no noble metals were observable above background
prior to irradiation. The fastest approach was to compare spectral results in parallel using spreadsheets.
Peak energies for all spectra were collected and listed in ascending order, according to spectrum.
Spreadsheet data provided a visual representation of peak decay behavior.

9. 9
Peaks present in all spectra were eliminated from further consideration as only long-lived fission
products were present in pre-irradiation spectra. Peaks present for only a short time after irradiation (post-
irradiation spectra 1 - ~3) were associated with short-lived activation products and peaks present in all
spectra with exception of the pre-irradiation spectrum were associated with longer-lived activation
products. A spreadsheet analysis example is provided in Table V.
Table V. Spectral Comparison Example: Spectra were compared in parallel with
observed peak energies in ascending order. Time progresses from left to right. Peaks of
interest were short-lived (455 keV and 482 keV series) and long-lived activation products
(475 keV and 469 keV series). Peaks associated with the pre-irradiation spectrum were
eliminated from further consideration as they corresponded to long-lived fission products
presented in Table I (e.g. 463 keV series).
Pre-Irr. Post 1 Post 2 Post 3 Post 4 Post 5 Post 6
455.57 454.96
463.45 462.67 462.7 462.96 462.99 463.39 463.38
467.15
469.5 469.01 469.29 469.98 470.96
475.03 475.07 477.77 474.81 476.51 476.07
481.99 482.07 482.2 482.45
Quantification
Quantification of unactivated analytes was based on activation products. Derivation of the
quantification expression is as shown below.
Let the activity of a nuclide at the beginning of counting (i.e. at a time td after the end of
irradiation, as determined from a gamma with energy Eγ) denoted as A(td,Eγ), be defined as
𝐴 𝑡<, 𝐸? =
𝐶 𝐸?
𝜀 𝐸? 𝛾 𝐸? 𝑒678 C
𝑑𝑠
9FG9H
9F
, (2)
where C(Eγ) is the number of net counts of the gamma Eγ, ε(Eγ) is the efficiency factor for the particular
energy, γ is the intensity for the particular gamma, tc is the count time for the spectrum, and λj is the decay
constant of the activation product.
The activity at the end of irradiation, A(0,Eγ), is defined as
𝐴(0, 𝐸?) =
𝐶 𝐸? 𝑒6789F
ε 𝐸? 𝛾 𝐸? 𝑒678 C
𝑑𝑠
9FG9H
9F
= 𝑁) 𝜆), (3)

10. 10
Letting the number density and decay constant of the unactivated analyte be N0 and λi,
respectively, and the number density of the activation product to be Nj, we assume
𝑑𝑁)
𝑑𝑡,--
= 𝑁K 𝑒6L:M9:;; − 𝑁) 𝜆). (4)
Therefore we obtain an expression for the number density of the activation product:
𝑁) 𝑡,-- =
𝐴(0, 𝐸?)
𝜆)
𝜎, 𝜙𝑁K
𝜎, 𝜙 − 𝜆)
𝑒6789:;; − 𝑒6L:M9:;; , (5)
where tirr is the irradiation time. Substituting expression (3), integrating, and simplifying gives the final
expression for the mass of the unactivated analyte as a function of experimental parameters:
𝑀9F, QR
,
=
𝑀𝑊
𝑁T
𝐶 𝐸? 𝑒789F
𝜀 𝐸? 𝛾 𝐸?
𝑒6789F − 𝑒678 9FG9H
𝜆)
𝜎, 𝜙 − 𝜆)
𝜆) 𝜎, 𝜙
1
𝑒6789:;; − 𝑒6L:M9:;;
,
where MW is the molecular weight of the unactivated analyte and NA is Avogadro’s number.
Quantification was specific to a particular nuclide (i, MW), with associated activation product (j, γ), for a
particular spectrum containing the nuclide (td, tc, C), using a particular gamma-ray (Eγ).
Uncertainty in determined mass was calculated using propagation of error using the standard
formula:
𝑢 𝑋 =
𝜕𝑋
𝜕𝑥,
Y
𝑢(𝑥,) Y
Z
,[&
where X is a function of xi for i = 1, 2, …, N, and u(xi) is the standard uncertainty of the random variable
xi. Sources of uncertainty include counts, efficiency, gamma-ray intensity, decay constant, cross section,
neutron flux, irradiation time, and decay time.
The counts and efficiency for each peak utilized in the analysis, as well as the associated
uncertainties for these values were obtained from spectral analysis using GammaVision [9]. Gamma
intensities, decay constants, and associated uncertainties were obtained from the literature. The irradiation
and decay times were measured using timers installed at the Nuclear Engineering Teaching Laboratory
(NETL) and the uncertainties in these values were estimated from experience. Lastly, cross sections and
fluxes for the tPNT facility were calculated.
The neutron energy spectrum was derived using a model of the TRIGA Mk-II reactor at The
University of Texas built in MCNP5. Using KCODE, the neutron group fluxes was derived for the tPNT
facility in the core, and these flux values were used to assemble one-group cross sections using the
CINDER90 cross section library. The uncertainties in these values were tabulated by propagating
the uncertainties in the group fluxes as calculated by MNCP. Lu determined the total flux in the tPNT

11. 11
facility using multiple activation wires and calculated cross sections at a reactor power of 100 kW [10].
The flux at 500 kW was linearly extrapolated from this value.
Quantification was specific to the nuclide, peak energy, and spectrum used in the analysis. The
mass of each noble metal nuclide observed in the spectra was determined independently using multiple
spectra and the method outlined above. Determined values were examined for consistency (e.g. to ensure
no outliers were present which could indicate previously unknown interferences), averaged over all
gamma energies (for a particular nuclide) and spectra, and uncertainties were propagated to yield a single
mass quantity per nuclide per sample.
Results
Comparative peak analysis was successful in identifying 5 of the 8 noble metals considered to be
viable analytes for NAA. Peaks corresponding to 99
Mo, 101
Mo, 103
Ru, 105
Ru, and 104m
Rh were observed.
Peaks corresponding to 104
Rh and 109
Pd were observed but eliminated from further consideration due to
poor counting statistics and/or interferences with intrusive fission product lines: 104
Rh was rejected due to
interference with 91
Sr at 555 keV and 109
Pd was rejected due to interference with 155
Eu at 188 keV. A
summary of gamma lines used for identification is presented in Table VI.
Table VI. Characteristic Gamma Signatures: Noble metal activation products were
identified using the given peaks. Peaks were verified using count ratios derived from
peak intensities. Peak energies are reported in keV and the intensity of each peak is given
in parenthesis. High-intensity peaks rejected due to interference include 739.5 keV (12%)
shared by 99
Mo and 130
I, 181.1 keV (6%) shared by 99
Mo and 154
Eu, and 590.1 keV (19%)
shared by 101
Mo and 154
Eu. All other peaks with intensities greater than 1% not listed
were not observable or well-defined.
Activation Product
Observed
Gamma Lines Used for Identification [keV] and
Intensities
99
Mo 140.5 (90.7%)
101
Mo 191.9 (18.2%), 1012.5 (13.0%), 505.9 (11.6%)
103
Ru 497.1 (91.0%)
105
Ru 724.3 (47.3%), 469.4 (17.6%), 676.3 (15.7%), 316.5 (11.1%)
104m
Rh 51.4 (48.3%), 97.1 (3.0%)
To confirm the attribution of the gamma rays shown in Table VI, peak ratios and count rates as
functions of time after irradiation were examined. For each observed activation product, the ratios of the
net areas of each of the peaks shown in Table VI were compared to the ratio of the gamma intensities.
Consistency between these two ratios (to within uncertainty) confirmed the source of the observed
photopeaks. Nuclide identification was further confirmed through analysis of count rate as a function of

12. 12
decay time. Count rates included efficiency factors to correct for changes in geometry. Data were fit to
exponentials to obtain decay constants which were used to approximate half-lives for observed nuclides.
Estimated half-lives were then compared to actual values. Results in agreement with literature values
bolster confidence in nuclide identification. Figure 2 portrays an example of the regression analysis as
performed on 104M
Rh for sample C.
Mass quantities for samples C and N derived following the process outlined above are presented
in Tables VII and VIII. Mass quantities are given in parts-per-million (ppm) as the two samples were of
different mass quantities. Uncertainties associated with presented mass quantities are reported at two
standard deviations. All observable gamma lines with intensities greater than 1% were used for
quantification assuming they preserved appreciable counting statistics and associated decay behavior as
dictated by nuclide half-life. Only 104m
Rh was used for quantification of 103
Rh due to the aforementioned
interference of 104
Rh with 91
Sr. A comparison of samples is presented in Table IX. An average uncertainty
budget, representative of both samples, is presented in Table X. Uncertainty contributions were averaged
for all nuclides and were calculated using all gamma ray energies used in the quantification process.
Table VII. Sample C Mass Quantities: The averaged mass quantities for the observed
noble metal nuclides and associated propagated uncertainties for the carbonate-peroxide
sample are listed. Uncertainties are reported at two standard deviations.
Analyte Mass [ppm] ± Mass [ppm]
98
Mo 1.63×10_ 3.74×10b
100
Mo 1.63×10b
2.87×10Y
102
Ru 9.53×10Y
4.06×10Y
104
Ru 2.28×10b
2.62×10Y
103
Rh 6.13×10Y
1.42×10Y
Table VIII. Sample N Mass Quantities: The averaged mass quantities for the observed
noble metal nuclides and associated propagated uncertainties for the nitric acid sample
are listed. Uncertainties are reported at two standard deviations.
Analyte Mass [ppm] ± Mass [ppm]
98
Mo 6.65×10b
1.51×10b
100
Mo 1.36×10b
2.76×10Y
102
Ru 6.04×10Y
3.48×10Y
104
Ru 9.56×10Y
1.22×10Y
103
Rh 1.46×10b
3.71×10Y

13. 13
Figure 2. Count Rate Decay Plot Analysis: Count rates for particular spectra for
particular peaks were plotted as a function of time for observed noble metal activation
products. Data were fit to exponentials to obtain decay constants. Decay constants were
used to derive approximate nuclide half-lives which were compared to actual values.
Negligible deviations were used as indicators of accurate nuclide identifications.
Table IX. Sample Comparison: The percent mass differences for the noble metal
nuclides in samples C and N are listed. Reported percent difference is normalized in
relation to sample N, e.g. sample C contains 145.20% more 98
Mo than the quantity in
sample N.
Analyte Percent Mass Difference (Relative to N)
98
Mo 145.20%
100
Mo 22.79%
102
Ru 57.80%
104
Ru 138.62%
103
Rh -57.93%

14. 14
Table X. Uncertainty Budget: Uncertainty budgets for the two samples were similar
therefore they were averaged. This uncertainty budget represents all sources of
uncertainty and their respective averaged contributions to total uncertainty for both
samples. Count time (determined by multichannel analyzer) was not listed as an
uncertainty source as it was taken to be exact.
Uncertainty Source Average Contribution to Total Uncertainty [%]
Counts 15.96 %
Cross Sections (σ) 14.83 %
Decay Times 3.62 %
Irradiation Times 6.67 %
Efficiency Factors 3.12 %
Decay Constants (λ) 2.09 %
Gamma Ray Intensities (γ) 7.16 %
Neutron Flux (φ) 46.55 %
Mass quantities for iodine and tellurium nuclides were also measured as they are of interest when
comparing UNF dissolution via carbonate-peroxide solution versus nitric acid. Iodine-127, 129
I, and 130
Te
were deemed viable NAA candidates and isotopes of interest following fission yield and decay chain
analysis. Gamma signatures used for identification and quantification of iodine and tellurium are
presented in Table XI and determined mass quantities for samples C and N are presented in Tables XII
and XIII, respectively. Lastly, a comparison of iodine and tellurium quantities in samples C and N is
presented in Table XIV.
Table XI. Iodine and Tellurium Characteristic Gamma Signatures: 127
I, 129
I, and
130
Te activation products were identified using the given peaks. Peaks were verified using
count ratios derived from peak intensities. Peak energies are reported in keV and the
intensity of each peak is given in parenthesis. The 739.5 keV (82%) peak for 130
I was
rejected due to interference with 99
Mo. All other peaks with intensities greater than 1%
not listed were not observable or well-defined.
Activation Product
Observed
Gamma Lines Used for Identification [keV] and
Intensities
128
I 442.9 (16.85%), 526.6 (1.58%)
130
I 536.1 (99.0%), 668.5 (96.13%), 418.0 (34.16%)
131
Te 149.7 (68.8%)

15. 15
Table XII. Sample C Iodine and Tellurium Mass Quantities: The averaged mass
quantities for iodine and tellurium nuclides of interest and associated propagated
uncertainties for the carbonate-peroxide sample are listed. Uncertainties are reported at
two standard deviations.
Analyte Mass [ppm] ± Mass [ppm]
127
I 8.90×10&
2.28×10&
129
I 7.90×10Y
9.00×10&
130
Te 9.47×10Y
2.38×10Y
Table XIII. Sample N Iodine and Tellurium Mass Quantities: The averaged mass
quantities for iodine and tellurium nuclides of interest and associated propagated
uncertainties for the nitric acid sample are listed. Uncertainties are reported at two
standard deviations.
Analyte Mass [ppm] ± Mass [ppm]
127
I 1.12×10&
1.27×10&
129
I 9.69×10&
1.92×10&
130
Te 4.79×10Y
1.28×10Y
Table XIV. Sample Comparison: The percent mass differences for iodine and tellurium
in samples C and N are listed. Reported percent difference is normalized in relation to
sample N, e.g. sample C contains 715.40% more 129
I than the quantity in sample N.
Analyte Percent Mass Difference (Relative to N)
127
I 696.33%
129
I 715.40%
130
Te 97.80%
Discussion
Noble Metals
Derived mass quantities for all nuclides for all spectra, prior to averaging, were consistent within
the range of experimental uncertainty; the maximum (constant) deviation between mass values and mean
values was roughly one order of magnitude occurring for 127
I for sample C. From Table X, it was evident
that most uncertainty associated with experiment, i.e. decay and irradiation times, and efficiency factors
were relatively low in comparison to nuclear data, which indicates good experimental data.
Two of the largest sources of uncertainty were cross sections and flux profiles derived from
codes. For future experiments, the cross sections may be refined by using more sophisticated methods,
e.g. using NJOY99 to include chemical binding effects and higher precision MCNP calculations to obtain

16. 16
more refined collapsed cross section values. Uncertainty in flux values may be improved by performing
activation wire measurements at the exact experimental power level. Additionally, the irradiation, decay,
and count times used in the experiment could be optimized for each nuclide to improve the counting
statistics and ensure low dead times during sample counting2
, further improving the accuracy and
precision of the results.
Moreover, no 99
Tc was quantified although it was reported that twenty percent of the sample was
99
Tc. This is likely a consequence of the 15 second half-life of 100
Tc. In future investigations, it would be
of interest to survey cyclic irradiation for quantification of 99
Tc. The cyclic irradiation facility at the
University of Texas has a pneumatic shuttle time of approximately 10 seconds and has been used to
quantify 110
Ag, which has a half-life of 24.3 seconds [12]. It is conceivable that 100
Tc is detectable
assuming the signal is high enough above background at longer detector-source geometries.
Iodine and Tellurium
Results for iodine quantities were interesting for their application to elemental fractionation
studies. It has been reported that carbonate-peroxide solution is of interest for UNF dissolution
applications due to its slightly alkaline properties and its use at room temperature [13]. According to
Soderquist and Hanson, “Certain fission products that are volatile in boiling nitric acid are much less
volatile at room temperature and pH 10 (bromine, iodine),” and moreover, “This [carbonate-peroxide]
would be a good dissolution method for analysis of fuel for bromine and iodine, which would otherwise
be lost up the exhaust stacks if the fuel were dissolved in nitric acid.”
Experimental data presented in Tables XIII-XV appear to support this assertion. Results indicate
that iodine retention in noble metal phase is roughly 700% greater for UNF dissolved in carbonate-
peroxide solution versus nitric acid. Spectra were also analyzed for 79
Br and 81
Br but none were found
above typical background levels.
Rapid Analysis
Instrumental NAA has the potential for high sample-processing rates and rapid analysis.
Separation of the noble metal phase from the actinides and remaining fission products greatly improved
NAA results in comparison to preliminary results from NAA of diluted ATM, performed in 2012 [14].
Having implemented an experimental protocol, numerous noble metal phase samples (similar to the ones
studied here) may be analyzed in a matter of hours.
2
In 12 of 16 cases, the dead time of the detector was in excess of 20%, which exceeds the recommended
specifications of the detector. Above this range, nonlinearity in detector response is expected and results are less
reliable [11].

17. 17
References
[1] M.C. Brady Raap, B.A. Collins, C.J. Francy, FY11 Summary Report on the Augmentation of the
Spent Fuel Composition Database for Nuclear Forensics: SFCOMPO/NF, 2012
[2] J.H. Chao, et al., Analysis of I-129 in Radwastes by Neutron Activation, 1999
[3] D.H. Day, et al. The Management of Radioactive Wastes, 1985
[4] X. Hou, et al., Determination of Cl-36 in Nuclear Waste from Reactor Decommissioning, 2007
[5] C. Soderquist (personal communication, November 14, 2012)
[6] R. Orton, The Multi-Isotope Process Monitor: Non-destructive, Near-Real-Time Nuclear Safeguards
Monitoring at a Reprocessing Facility, 2010, Thesis (Ph.D.), Ohio State University
[7] T.R. England and B.F. Rider, LA-UR-94-3106, ENDF-349
[8] Korea Atomic Energy Research Institute, information extracted from the Table of Nuclides,
http://atom.kaeri.re.kr/ton/nuc8.html
[9] GammaVision-32, Version 6.08, 2010
[10] C. Lu, Determination of Fission Yields Using Gamma Ray Spectroscopy, 2012, Unpublished Thesis
(M.S.), University of Texas
[11] G. Gilmore, Practical Gamma-Ray Spectrometry, John Wiley & Sons Ltd, England, 2008
[12] T.H. Pun, S. Landsberger, Determination of Silver Using Cyclic Epithermal Neutron Activation
Analysis
[13] C. Soderquist, B. Hanson, Dissolution of Spent Nuclear Fuel in Carbonate-Peroxide Solution, 2010
[14] R.I. Palomares, et al., Predictive Modeling of Neutron Activation Analysis of Spent Nuclear Fuel for
the Detection of Stable and Long-Lived Radionuclides, 2012, University of Texas