# Hydrogenous content identification in heterogeneous cargoes via multiple
monoenergetic neutron radiography

Jill Rahon  Areg Danagoulian<EMAIL_ADDRESS>Massachusetts Institute of
Technology, Cambridge, MA 02139, USA

###### Abstract

The determination of hydrogenous content in commercial cargoes is an important
challenge in cargo security. Prior work has shown the feasibility of
hydrogenous cargo classification in radiographic applications. This result was
achieved by using the significant material to material differences in the
energy dependence of their neutron scattering cross-sections. The work
presented here details the application of this technique to multiple-
monoenergetic neutron transmission measurements of several heterogeneous cargo
mock-ups with the goal of quantifying hydrogenous content. It demonstrates the
ability to determine the hydrogenous content of a cargo container by
performing analysis of pulse-height data of transmitted neutrons. The set-up
used for these feasibility studies was able to detect and quantify areal
densities of up to 30 g/cm2 of high density polyethylene (HDPE), even when
mixed with metallic materials. Accurate determination of the hydrogenous
content of the cargo has two important uses: it can allow for better imaging
and discrimination of conventional contraband during cargo screening; it may
also allow the unfolding of the individual elemental contributions from an
effective atomic number, $Z_{\mathrm{eff}}$, as determined from multiple
monoenergetic gamma radiography (MMGR). This combination of capabilities could
make multiple monoenergetic neutron radiography applications a significant
contribution to cargo security.

###### keywords:

Active interrogation , Nuclear security , Radiography

††journal: Nuclear Instruments and Methods in Physics Research A

##  1 Introduction

Every day approximately 50 000 maritime ISO containers enter the United States
[1]. This flow of cargoes currently undergoes a variety of checks for the
presence of nuclear and conventional contraband. Significant efforts have
taken place over the last two decades on the development of passive, active,
and radiographic screening systems. The goal of these systems is to detect and
identify a variety of threats: radioactive materials; various Special Nuclear
Materials (SNM); fully assembled nuclear devices, whose danger is significant
in the contect of nuclear terrorism; and conventional contraband, which is
smuggled for a variety of economic reasons. Passive techniques primarily focus
on the detection of the natural emission of particles from the radioactive
materials. Active techniques involve irradiation of the cargo with various
particles with the purpose of triggering element-specific processes, whose
detection by proxy will allow the inference of the cargoe’s elemental
composition. Such techniques involve detection of photofission neutrons and
photons, detection of secondary bremsstrahlugn photons, nuclear resonance
fluorescence (NRF), etc [2, 3, 4]. Radiographic techniques, on the other hand,
use measurements of transmitted particle beams to infer the areal density and
in some cases, the effective atomic number $Z_{\mathrm{eff}}$ of the cargo [5,
6]. Imaging of the cargo based on $Z_{\mathrm{eff}}$, in addition to its
utility in locating actinides, can also be used to differentiate between
medium-Z and low-Z cargoes, thus providing additional information to the
operators in their effort to detect various contraband. The transmission of
neutron beams have been used in various configurations in combination with
photon transmission to estimate the areal density and composition of the
cargoes beyond what can be done with photons alone [7, 8, 9, 10, 11]. In
particular, work by Cutmore et al. shows that neutron counting along with
photon radiography can allow the imaging and improved identification of a
variety of hydrogenous materials[12]. These methods, however, use only neutron
counting, and do not exploit the spectral information of the transmitted
neutron flux. Additional work by others has showing that precise
reconstructions of neutron energy can allow for resonance radiography
applications which allow for the determination of carbon, oxygen, and
nitrogent contents of the cargo [13, 14, 15, 16]. Our work extends this by
showing that the analysis of the neutron deposited energy alone, which results
in a much simpler measurements, can provide information about the hydrogenous
content. It can then further improve the cargo content characterization and
thus provide additional information not available in simple neutron counting
based methods. It should be added that the work presented here details a new
technique which, rather than as a standalone system, can be combined with
other radiographic techniques to achieve the above mentioned improvements.
While the system described in this work uses a Radio Frequency Quadrupole
(RFQ) as a platform and the ${}^{11}B(d,n\gamma)^{12}C$ reaction as a source
of neutrons and photons, essentially any source of polychromatic neutrons
could be used, as long as it spans the neutron energy range of $\sim[1,10]$
MeV, where the variation of fast neutron scattering cross sections on hydrogen
is the greatest. Examples of such platforms could be:

  * •

A combination of deuteron-deuteron (DD) and deuteron-triton (DT) sources, or a
DT source with its 14 MeV neutron energy broadened with (n,2n) reactions. More
specifically, the technique described in Ref. [12] could be augmented with an
additional DD source, thus allowing to perform differential neutron
transmission measurements similar to the technique presented in this work.

  * •

an isotopic neutron source, such as 252Cf source

  * •

a source of neutrons from an 9 MeV X-ray scanner fitted with a berylium
neutron converter, producing neutrons in the [0, 6.5] MeV range via the
${}^{9}Be(\gamma,n)^{8}Be$ reaction.

This work builds upon and expands on the results achieved as part of
feasibility studies using multiple monoenergetic neutrons from the
${}^{11}B(d,n\gamma)^{12}C$ reaction [17]. The previous work showed that it is
possible to use spectroscopic analysis of transmitted multiple monoenergetic
neutrons to estimate the hydrogenous content of a homogeneous cargo. Similar
work done by other groups since the publication of these studies have shown
that the basic concept behind the technique can be scaled to a multi-sensor
system [18]. The original interest in the ${}^{11}B(d,n\gamma)^{12}C$
reaction, which is excited via a 3 MeV deuteron beam, focused on the 4.4 MeV
and 15.1 MeV photons which it produces. These photons can be used for
performing dual energy radiographic measurements which allow the determination
of the $Z_{\mathrm{eff}}$ of the cargo via multiple monoenergetic gamma
radiography (MMGR) [5]. However, such a determination is limited when it comes
to SNM detection. In a simple, non-tomographic radiography a given value of
$Z_{\mathrm{eff}}$ is not specific enough to determine a cargo type: various
combinations of different elements could produce the same $Z_{\mathrm{eff}}$.
This circumstance could enable the smuggler to combine uranium with
hydrogenous material (e.g. plastic, wood, water, etc) to reduce the effective
$Z$ of the cargo and thus avoid interception.

This circumstance creates the need for additional modalities for the detection
of SNM or clearing cargoes of their presence. Multiple monoenergetic neutron
radiography is uniquely sensitive to hydrogen content and given the multi-
particle nature of the reaction, it requires no additional source. This work
focuses on the study of neutron radiography of heterogeneous cargoes, where
various amounts of high density polyethylene (HDPE) were placed behind
metallic cargo objects of various thickness and atomic number. The analysis of
transmission data via the simple algorithm described in Ref. [17] shows that
the technique can detect hydrogenous content, even in small concentrations.
Furthermore, this analysis can estimate the HDPE fraction in a given pixel,
which, if combined with MMGR data on $Z_{\mathrm{eff}}$, can result in a
combined detection system of a higher specificity. Though the described
spectral analysis technique is based on neutrons generated by a single nuclear
reaction, it can be applied in any apparatus using dual or multi energy
neutron groups.

##  2 Concept

In standard transmission radiography, total counts of transmitted neutrons are
compared with the known flux of the incident beam to generate a ratio
representative of neutron interaction within the scanned material. The cross
section, $\sigma$, for neutrons of a defined energy is a constant for a given
isotope and type of interaction. This cross section can vary dramatically with
neutron energy, as is the case for the total $\sigma_{n}(E)$ for hydrogen and
neutron energies between 1 and 15 MeV. This shift results in a significant
change in neutron beam attenuation in hydrogenous materials, such as
polyethylene, based on incident particle energy. The final intensity, $I$ of a
neutron beam, transmitted through a mixed element target of thickness $x$ and
density $\rho$ is calculated by

$I=I_{0}\text{exp}\Big{\\{}-\rho
xN_{A}\frac{\sum_{i}c_{i}\sigma_{i}(E)}{\sum_{i}c_{i}A_{i}}\Big{\\}},$ (1)

where $I_{0}$ is the incident flux, the sum is over the $i$ elements in the
material, $N_{A}$ is Avogadro’s number, $\sigma_{i}$ is the energy dependent
total neutron interaction cross section for element $i$, $c_{i}$ is the
elemental fraction in the molecule of the material, and $A_{i}$ is the atomic
weight, respectively. Eq. 1 can be rewritten as

$\frac{I}{I_{0}}=e^{{-\Sigma_{tot}x}}$ (2)

where
$\Sigma_{tot}=N_{A}\rho\frac{\sum_{i}c_{i}\sigma_{i}(E)}{\sum_{i}c_{i}A_{i}}$
is the total macroscopic cross section for all neutron interactions which
effectively remove particles from the beam. Integrating the transmitted
neutron counts, $I$, over a particular energy region gives the total count of
non-attenuated monoenergetic neutrons. Comparing this value for two energy
regions yields an indication of the $\sigma_{n}$ of the transited material.
This ratio, $S$, defined as

$S=\frac{I_{[E_{2},E_{3}]}}{I_{[E_{0},E_{1}]}},$ (3)

presents a method of assessing the variability of $\sigma_{n}$ for a certain
material, sensitive to the energy regions selected for integration. Therefore,
the sharp decrease in hydrogen’s cross section for neutrons with energies
included in the integration regions will result in a markedly different $S$
value than that of other, low $\sigma_{n}(E)$-varying elements. Fig. 1 plots
the dependence of transmission on energy, for three different materials,
showing the significant difference between HDPE and metals - primarily caused
by the strong energy dependence in hydrogen scattering cross section.

Figure 1: The neutron transmission ratio for various materials. The presence
of hydrogen in HDPE causes a strong variations in transmission amplitude
across the MeV energies. Vertical lines indicate discrete neutron energies
generated by 3.0 MeV deuteron in the ${}^{11}B(d,n)^{12}C$ reaction.

By choosing broadly spaced energy regions, this method mitigates the effects
of material-specific $\sigma_{n}(E)$ resonances, such as the gradual increase
of $\sigma_{n}(E)$ in lead from 5.5 b at 1 MeV incident neutron energy to 8 b
at 4 MeV.

###  2.1 Multiple Monoenergetic Neutron Radiography

The 3.0 MeV deuteron used in this research generates neutron lines at the
energies of 16.51, 12.2, 8.86, and 4.01 MeV, ideally suited for differential
transmission analysis due to their wide energy spacing. For a more detailed
discussion of neutron production from the ${}^{11}B(d,n)^{12}C$ reaction see
Table 1 in Ref. [17] and Section IV in Ref. [19]. These neutron energy groups
broaden as a function of the deuteron’s energy straggle within the boron
target thickness. The organic scintillator detector can only detect the
(partial) energy deposition of the neutrons. Due to the dependence of the
deposited energy on the neutron scattering angle, which is isotropic in the
center of mass frame, the observed spectra are continuous, monotonic
distributions. These distributions however do retain a correlation to the
incident neutron energy, and as such can be used as a metric of the energy
dependence of the incident neutrons. These effects result in a quasi-
monoenergetic neutron beam manifesting as a series of stacked, rectangular
energy distributions for each energy group, visible in Fig. 2.

Figure 2: Normalized spectra of energies deposited by transmitted neutrons
from the 11B(d,n$\gamma$)12C reaction in the experimental data. The
integration regions overlaid, and is chosen based on the optimization studies
described in Ref. [20]. Cargoes are 30 g/cm2 of HDPE, graphite, aluminum, and
lead.

The variability of the total neutron cross section for hydrogen and hydrogen-
containing materials affects the energy-dependant attenuation of neutrons
within the cargo volume. Examining the ratio of attenuation of high energy
neutrons to those attenuated at low energy by the same sample provides
information about hydrogenous content. By selecting two energy regions
optimally spaced to exploit the greatest cross sectional energy dependence,
the $S$ ratio described in Eqn. 3 becomes a representation of attenuation
levels due to hydrogenous content. Previous research has determined that the
$S$ value is a statistically significant indicator of the presence of
hydrogenous material [20]; the work presented here demonstrates that it also
has the ability to quantify and image the areal density of scanned hydrogenous
material in a heterogeneous mix.

###  2.2 Methods of spectral analysis and optimization

Without prior knowledge of the content and areal density of the cargo, a
single set of integration bounds which universally generates the strongest
signal of hydrogenous content must be identified. To determine these bounds,
$S$ values were compared in several sets of homogeneous, non-hydrogenous
transmission spectra with those of hydrogen-containing materials’ transmission
spectra. Defining $S_{H}$ as the attenuation measurement for the hydrogenous
spectra, this number quantifies the amount of variation from the spectra of
any other material, $X$, using

$R=\frac{\Bigl{\lvert}1-\frac{S_{X}}{S_{H}}\Bigl{\rvert}}{\sigma_{\frac{S_{X}}{S_{H}}}}.$
(4)

This $R$ value yields units of standard deviation by dividing the absolute
difference of the $S$ value ratios from unity by the propagated error,
$\sigma_{\frac{S_{X}}{S_{H}}}$. For any set of integration windows,
$\\{E_{0},E_{1},E_{2},E_{3}\\}$ for identically-binned energy histograms, $R$
provides a figure of merit for the analyzing power of the set. For example,
$R=2$ represents a 95% discrimination capability between hydrogenous and non-
hydrogenous materials for a certain set of integration windows. The bounds
identified in this manner yield the lowest fractional error of all possible
sets.

Using an iterative $R$ value search to generate the highest discrimination of
hydrogenous and non-hydrogenous cargo, an optimal set of bounds for cargo
areal densities in increments of 10
$\mathrm{g}\mathrm{/}\mathrm{c}\mathrm{m}^{2}$ was determined [17]. These
bounds were applied to several experimental runs at their respective areal
density and provided only a 3% average improvement on $R$ value over the
trials in which a universal, areal density-agnostic set of integration bounds
were used111For the experimental setup used in this research and histogrammed
spectra with 0.06 MeV bin sizes, the universal integration bounds were
$\\{E_{0},E_{1}\\}$ = $\\{10,31\\}$ and $\\{E_{2},E_{3}\\}$ = $\\{42,149\\}$..

The neutron counting statistics used in this particular experimental setup
limit hydrogenous material content to areal densities of $\leq$30
$\mathrm{g}\mathrm{/}\mathrm{c}\mathrm{m}^{2}$; greater hydrogenous content
creates levels of neutron attenuation and energy downscatter too high to
effectively employ the $R$ value spectral analysis.

##  3 Experiment

As in previous publications regarding this work, this research was conducted
at MIT’s Bates Research and Engineering Center in Middleton, MA.

An AccSys Technology Model DL-3 radio-frequency quadrupole (RFQ) linear
accelerator was used to bombard a 1 mm thick natural boron target with 3.0 MeV
deuterons. The ${}^{11}B(d,n\gamma)^{12}C$ reaction generates monoenergetic
gammas of 4.4 and 15.1 MeV energies. The neutron energies were listed in
Section 2.1, with additional information in References [17, 19]. The
accelerator was operated at a current of 2 to 15 $\mu$A, a beam repetition
rate of 300 Hz, and a pulse length of 100 $\mu$s. Deuterons impinge on the
boron target and the resulting high energy particles were collimated into a
fan beam.Various cargo phantoms with an areal density of 30
$\mathrm{g}\mathrm{/}\mathrm{c}\mathrm{m}^{2}$ were placed 4 m from the source
target and transmitted neutrons were collimated via a second set of concrete
blocks to the detector, 7 m from the cargo. The general layout of the
experiment can be seen in Fig. 3.

Figure 3: Top-down schematic view of the experimental radiographic layout (not
to scale).

A 5.08 x 5.08 cm cylindrical detector containing EJ-309 liquid organic
scintillator was used for fast neutron detection. The analog waveforms were
digitized via a CAEN V1720 12 bit 250 MHz digitizer. The PMT voltage was
provided via a SY1527 CAEN high voltage mainframe unit. The ADAQ framework, an
in-house developed software package, provides control of the digital
acquisition systems and comprehensive online and offline data analysis
capabilities through its integration of the ROOT toolkit [21]. The waveforms
from the detector were analyzed with the pulse shape discrimination technique,
to separate the neutron hits from the photon hits. For a more detailed
overview see Ref. [17], Section 3.2.

Fig. 6 shows a cargo schematic of a typical mixed-cargo experimental run. Four
phantoms comprised of varying amounts of hydrogenous and non-hydrogenous
materials were moved on a step motor-driven belt through the collimated beam
line. The hydrogenous phantoms consisted of blocks of HDPE doped with
$\mathcal{O}(\%)$ fractions of boron, whose effect is ignored due to its small
concentrations. Transmission neutrons and gammas were detected by the EJ-309
scintillator and neutron events isolated using the pulse shape discrimination
(PSD) method.

##  4 Results

The $S$ value, defined in Eqn. 3, is generated by applying the universal
integration bounds from Sec. 2.2 to a given neutron spectrum. Experimental
runs to determine the $S$ values of mixed hydrogenous and non-hydrogenous
cargoes showed a strong dependence on HDPE content, with little effect from
the additional non-hydrogenous cargo. Combined heterogeneous cargo phantoms
(HDPE-aluminum, HDPE-lead, HDPE-carbon) with effective areal densities in
combined thicknesses ranging from 1
$\mathrm{g}\mathrm{/}\mathrm{c}\mathrm{m}^{2}$ to 50
$\mathrm{g}\mathrm{/}\mathrm{c}\mathrm{m}^{2}$ were tested. The resulting
plots of $S$ value to HDPE content for each material combination indicate good
correlation between HDPE content and $S$ value, which is largely unaffected by
the magnitude of higher-Z contributions to combined areal density. Fig. 4
displays the $S$ value’s dependence on the actual HDPE areal density for the
experimental scenarios where the combined areal density was 50
$\mathrm{g}\mathrm{/}\mathrm{c}\mathrm{m}^{2}$.

The $S$ value’s strong correlation with absolute HDPE content in a sample
illustrates the predictive power of $S$ in inferring the hydrogenous content
of the cargo. A linear least squares fit was applied to the data in Fig. 4.
The $S$ value (which can be related to thickness, $x$, from Eqn. 2) to HDPE
areal density dependence is represented by an exponential relationship which
can be described as
$S=\frac{I_{h,0}}{I_{l,0}}\exp{[x(\Sigma_{l}-\Sigma_{h})]}$, where the
subscripts $l$ and $h$ refer to the low and high energy ranges, respectively,
and the subscript $0$ refers to the initial flux. In practice however, low
energy downscatter at high HDPE ratios softens the exponential rise to be
better fit by a linear relationship.

Despite a variety of the material types and thicknesses combined with HDPE
samples the $S$ value has a good linear dependence on the actual HDPE content,
as shown by the fit in Fig. 4. This indicates the strength of the correlation
between HDPE quantity and $S$ value. The linear equation from the fit,
$y=0.019x+0.33$ was used as a predictive model to infer HDPE areal density
through observed $S$ values of cargoes of unknown composition and is the basis
for the radiographic reconstruction in Fig. 5. Here it should be clarified
that the simple linear model is purely empirical and is used here only to
prove the concept. Future research should pursue the development of more
precise models and reconstruction algorithms.

The transmitted neutron count statistics became limited at areal densities
greater than 30 $\mathrm{g}\mathrm{/}\mathrm{c}\mathrm{m}^{2}$ of HDPE, at
which point higher energy neutron attenuation and lower energy neutron down-
scatter degrades the $S$ values analyzing power. Thus this work is only
focused on scenarios corresponding to HDPE content of $\leq$ 30
$\mathrm{g}\mathrm{/}\mathrm{c}\mathrm{m}^{2}$.

Figure 4: Plot illustrating the relationship between $S$ value and areal
density of HDPE in cargo. Data collected from cargoes with varying thicknesses
of HDPE and lead, each cargo with an effective areal density of 30
$\mathrm{g}\mathrm{/}\mathrm{c}\mathrm{m}^{2}$. Linear fit (least squares):
$y=0.019x+0.33$.

Fig. 5 shows a step-wedge cargo mock-up on the left and an S-value
reconstructed radiograph on the right. The areal density at the center of each
HDPE step was inferred from the observed $S$ and the linear model described
earlier. The top shelf holds a bare HDPE step wedge and the bottom shelf holds
an identical step wedge, combined with 2 cm (5.4
$\mathrm{g}\mathrm{/}\mathrm{c}\mathrm{m}^{2}$) of aluminum. The accompanying
radiograph and $S$ value bar scale indicate an ability to determine HDPE
content to $\pm 1$ cm, with the aluminum shielding resulting in a slight
underestimation of HDPE quantity. Fig. 6 shows a mixed-material cargo setup
and its radiograph which is reconstructed from $S$ value. This image
demonstrates the effectiveness of the radiographic technique in inferring the
areal density of hydrogenous materials, even when combined with varying
densities of non-hydrogenous materials. These reconstructions show that it may
be possible to use the $S$ value method of neutron radiography to provide a
quantitative determination of hydrogenous content up to 30
$\mathrm{g}\mathrm{/}\mathrm{c}\mathrm{m}^{2}$ of hydrogenous material for
heterogeneous cargoes. Table 1 shows the effectiveness of the $S$ value
reconstruction technique by comparing the phantom’s HDPE areal density with
its calculated density.

Figure 5: Experimental set-up and radiograph of shielded and un-shielded HDPE step wedges. Left: a photo of a step-wedge setup of different thicknesses of HDPE without (top) and with (bottom) a 2 cm aluminum plate as shielding. Right: radiograph illustrating a reconstructed areal density map of the unshielded and shielded HDPE step wedges. The data was binned into 10 cm bins, and the measurement lasted 20 minutes.  Figure 6:  Top: Cargo schematic with the areal densities overlaid. The left two objects are a mix of metal and HDPE, the right two objects are solely HDPE and aluminum, respectively. From left to right, total phantom areal densities are: A:33.3, B:70.1, C:12.7, and D:36.0 $\mathrm{g}\mathrm{/}\mathrm{c}\mathrm{m}^{2}$. For objects A, B, and C the HDPE content was 12.7 g/cm2. Inset shows sidelong view of the mock-up, revealing 12.7 $\mathrm{g}\mathrm{/}\mathrm{c}\mathrm{m}^{2}$ of HDPE behind the aluminum. Bottom: Transmission radiograph of the cargo mock-up. Scan performed at a speed of 0.03 $\mathrm{c}\mathrm{m}\mathrm{/}\mathrm{s}$ with a beam current of 12 $\mu$A. Each pixel contains a relative error of 0.3 to 1.2 percent, based on total areal density of each pixel. Phantom outlines are overlaid on the radiograph for placement. The vertical binning is approximately 7 cm, while the horizontal binning is 4.6 cm.  Sample |  Actual areal density $a_{0}$[g/cm2] |  Reconstructed average areal density $a_{rec}$[g/cm2] |  Difference: $(a_{rec}-a_{0})/a_{0}$
---|---|---|---
A | 12.7 | 12.3 | -0.03
B | 12.7 | 12.6 | -0.01
C | 12.7 | 13.2 | 0.043
D | 0 | 2 | -
Table 1: Table comparing the areal density of the HDPE in each phantom in Fig.
6 and its reconstructed areal density.

##  5 Conclusions and future work

Screening of commercial cargoes for the presence of nuclear and conventional
smuggling remains a significant challenge. This work describes a novel
technique which leverages the spectroscopy of fast, multiple monoenergetic
neutrons to infer the hydrogenous content of the cargo which they have
traversed. The results have shown that not only is the technique sensitive to
the presence of hydrogenous materials, but can also be used to accurately
determine the areal density of the material—even in heterogeneous
configurations where the hydrogenous samples are masked by materials of higher
atomic number, including lead. This information can be useful both in
screening cargoes for the presence of conventional contraband, as well as in
the context of SNM detection. The ability to determine the density of
hydrogenous materials in the cargo can contribute towards improved specificity
in SNM detection via gamma radiography techniques, as it allows to further
constrain the possible values of cargo $Z$ from a non-unique observed
$Z_{\mathrm{eff}}$.

The multiple monoenergetic neutron radiography technique would be most
effective when combined with other radiographic techniques, including ones
which include neutron detectors, such as the one described in Ref. [11]. This
methodology can be extended to any other radiographic system where multiple
monoenergetic neutrons are emitted and detected. The configuration currently
being developed at MIT using a 12 MeV proton cyclotron is an example of such a
platforms. Proton-induced reactions on such elements as carbon and oxygen can
produce monoenergetic photons in the range of 4.4 - 10 MeV. Simultaneously,
the ${}^{13}C(p,n)^{13}N$ reaction on ${}^{13}C$, which has 1% natural
abundance, can produce monoenergetic neutrons. For a 12 MeV incident proton
and a thick carbon target, the neutron energies will be at approximately 9, 6,
5 and 2 MeV. These neutrons can then be detected and their spectral analysis
used to determine the hydrogenous content of the cargo.

Future research could exploit other nuclear reactions and other sources of
neutrons. While this work only focused on one type of hydrogenous cargo (HDPE)
as part of a proof of concept demonstration, future experiments should include
measurements on a variety of other hydrogenous materials - such as liquids,
celluose (wood), and a variety of plastics. Furthermore, more complex and
mixed cargo scenarios need to be studied, and more advanced reconstruction
algorithms, using broader sets of training data, can be developed.

##  6 Acknowledgements

This work is supported in part by the U.S. Department of Homeland Security
Domestic Nuclear Detection Office under a competitively awarded collaborative
research DE-AC52-07NA27344. It has also been supported in part by the United
States Army and the United States Military Academy. The authors would like to
thank their colleagues at MIT, in particular Richard Lanza and Zachary Hartwig
for assistance and support. The authors are also grateful to their
collaborators at Georgia Institute of Technology and University of Michigan.
In particular the authors would like to thank Igor Jovanovich and Jason
Nattress for useful discussions and comments.

## References

## References

  * [1] R. Kouzes, J. McDonald, D. Strachan, S. Bowyer, Radiation Detection and Interdiction at U.S. Borders, Oxford University Press, 2011.
  * [2] A. Danagoulian, et al., Prompt neutrons from photofission and its use in homeland security applications, in: Technologies for Homeland Security (HST), 2010 IEEE International Conference on, IEEE, 2010, pp. 379–384.
  * [3] W. Bertozzi, R. Ledoux, Non-intrusive method to identify presence of nuclear materials using energetic prompt neutrons from photon-induced fission, uS Patent 8,718,219 (May 6 2014).
URL https://www.google.com/patents/US8718219

  * [4] W. Bertozzi, et al., Nuclear resonance fluorescence excitations near 2 MeV in 235U and 239Pu, Phys. Rev. C 78.
  * [5] B. E. O. III, Z. S. Hartwig, R. C. Lanza, A. Danagoulian, Initial results from a multiple monoenergetic gamma radiography system for nuclear security, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 832 (2016) 68 – 76.  doi:http://dx.doi.org/10.1016/j.nima.2016.05.117.
URL http://www.sciencedirect.com/science/article/pii/S0168900216305198

  * [6] P. Rose, A. Erickson, M. Mayer, J. Nattress, I. Jovanovic, Uncovering special nuclear materials by low-energy nuclear reaction imaging, Scientific reports 6 (2016) 24388.
  * [7] B. Sowerby, J. Tickner, Recent advances in fast neutron radiography for cargo inspection, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 580 (1) (2007) 799–802.
  * [8] B. W. Blackburn, G. Chen, W. A. Franklin, E. E. Ihloff, G. E. Kohse, R. C. Lanza, B. McAllister, D. R. Perticone, V. Ziskin, Fast neutron resonance radiography for homeland security, in: Nuclear Science Symposium Conference Record, 2007. NSS’07. IEEE, Vol. 2, IEEE, 2007, pp. 1016–1020.
  * [9] J. Nattress, M. Mayer, A. Foster, A. B. Meddeb, C. Trivelpiece, Z. Ounaies, I. Jovanovic, Capture-gated spectroscopic measurements of monoenergetic neutrons with a composite scintillation detector, IEEE Transactions on Nuclear Science 63 (2) (2016) 1227–1235.
  * [10] S. Van Liew, X-ray and neutron interrogation of air cargo for mobile applications, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 784 (2015) 417–422.
  * [11] B. Sowerby, J. Tickner, Recent advances in fast neutron radiography for cargo inspection, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 580 (1) (2007) 799–802.
  * [12] N. G. Cutmore, Y. Liu, J. R. Tickner, Development and commercialization of a fast-neutron/x-ray cargo scanner, in: Technologies for Homeland Security (HST), 2010 IEEE International Conference on, IEEE, 2010, pp. 330–336.
  * [13] G. Chen, R. C. Lanza, Fast neutron resonance radiography for elemental imaging: theory and applications, IEEE transactions on nuclear science 49 (4) (2002) 1919–1924.
  * [14] D. Perticone, B. W. Blackburn, G. Chen, W. A. Franklin, E. E. Ihloff, G. E. Kohse, R. C. Lanza, B. McAllister, V. Ziskin, Fast neutron resonance radiography for elemental imaging, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 922 (2019) 71–75.
  * [15] I. Mor, V. Dangendorf, M. Reginatto, F. Kaufmann, D. Vartsky, M. Brandis, D. Bar, M. B. Goldberg, Reconstruction of material elemental composition using fast neutron resonance radiography, Physics Procedia 69 (2015) 304–313.
  * [16] J. Overley, M. Chmelik, R. Rasmussen, R. Schofield, G. Sieger, H. Lefevre, Explosives detection via fast neutron transmission spectroscopy, Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 251 (2) (2006) 470–478.
  * [17] J. Rahon, A. Danagoulian, T. D. MacDonald, Z. S. Hartwig, R. C. Lanza, Spectroscopic neutron radiography for a cargo scanning system, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 820 (2016) 141–145.
  * [18] M. Sweany, P. Marleau, Design and expected performance of a fast neutron attenuation probe for light element density measurements, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 833 (2016) 134–141.
  * [19] T. Taddeccui, R. Sheffield, T. Massey, et al., Neutron and gamma-ray production with low-energy beams, Tech. rep., Los Alamos National Laboratory (2007).
  * [20] J. Rahon, A. Danagoulian, T. D. MacDonald, Z. S. Hartwig, R. C. Lanza, Spectroscopic neutron radiography for a cargo scanning system, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 820 (2016) 141 – 145.  doi:http://dx.doi.org/10.1016/j.nima.2016.03.025.
URL http://www.sciencedirect.com/science/article/pii/S0168900216300419

  * [21] Z. S. Hartwig, The adaq framework: An integrated toolkit for data acquisition and analysis with real and simulated radiation detectors, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 815 (2016) 42 – 49.  doi:http://dx.doi.org/10.1016/j.nima.2016.01.017.
URL http://www.sciencedirect.com/science/article/pii/S0168900216000206