Solid Earth, 7, 1281–1292, 2016
www.solid-earth.net/7/1281/2016/
doi:10.5194/se-7-1281-2016
© Author(s) 2016. CC Attribution 3.0 License.
Recent developments in neutron imaging with
applications for porous media research
Anders P. Kaestner1, Pavel Trtik1, Mohsen Zarebanadkouki2, Daniil Kazantsev3,4, Michal Snehota5,
Katherine J. Dobson6,7, and Eberhard H. Lehmann1
1Laboratory for Neutron Scattering and Imaging, Paul Scherrer Institut, Villigen, Switzerland
2Division of Soil Hydrology, University of Goettingen, Goettingen, Germany
3Manchester X-Ray Imaging Facility, School of Materials, University of Manchester, Manchester, UK
4Manchester X-Ray Imaging Facility, Research Complex at Harwell, Didcot, UK
5Faculty of Civil Engineering, Czech Technical University in Prague, Prague, Czech Republic
6Ludwig-Maximilians Universität München, Department für Geo-und Umweltwissenschaften, 80333 Munich, Germany
7Department of Earth Sciences, Durham University, Durham, DH1 3LE, UK
Correspondence to: Anders P. Kaestner (anders.kaestner@psi.ch)
Received: 30 October 2015 – Published in Solid Earth Discuss.: 4 December 2015
Revised: 3 June 2016 – Accepted: 11 July 2016 – Published: 6 September 2016
Abstract. Computed tomography has become a routine
method for probing processes in porous media, and the use
of neutron imaging is especially suited to the study of the
dynamics of hydrogenous fluids, and of fluids in a high-
density matrix. In this paper we give an overview of recent
developments in both instrumentation and methodology at
the neutron imaging facilities NEUTRA and ICON at the
Paul Scherrer Institut. Increased acquisition rates coupled to
new reconstruction techniques improve the information out-
put for fewer projection data, which leads to higher volume
acquisition rates. Together, these developments yield signifi-
cantly higher spatial and temporal resolutions, making it pos-
sible to capture finer details in the spatial distribution of the
fluid, and to increase the acquisition rate of 3-D CT volumes.
The ability to add a second imaging modality, e.g., X-ray
tomography, further enhances the feature and process infor-
mation that can be collected, and these features are ideal for
dynamic experiments of fluid distribution in porous media.
We demonstrate the performance for a selection of experi-
ments carried out at our neutron imaging instruments.
1 Introduction
The knowledge of how hydrous fluids are redistributed
within a pore network is central to many porous media ex-
periments, and 3-D imaging using a variety of different imag-
ing modalities (e.g., X-ray and neutron tomography) has be-
come a useful tool since it can provide information about
the displacements of fluids as well as the solid structures of
the pore network within the sample. X-rays (XCT) are cur-
rently the most widely used imaging modality because of the
high spatial and temporal resolution that can be achieved at
modern synchrotron X-ray sources (e.g., Wildenschild and
Sheppard, 2013; Cnudde and Boone, 2013; Dobson et al.,
2016) and the relative availability of laboratory X-ray CT
systems. However, neutron imaging (Anderson et al., 2009)
has also proven very useful for in situ studies (e.g., Kard-
jilov et al., 2011). Neutron imaging is generally less acces-
sible as there are fewer neutron imaging facilities worldwide
(Lehmann and Kaestner, 2009), and while the lower fluxes
mean it cannot always compete with X-ray imaging in speed,
it has a distinct advantage in the excellent fluid-matrix con-
trast that arises from the high sensitivity to hydrogen. This
difference comes from the neutron matter interaction, which
is sensitive to the nucleus constellation instead of the elec-
tron shells as with X-rays (Krane, 1988). The protons and
neutrons are also organized in shells and the cross section
Published by Copernicus Publications on behalf of the European Geosciences Union.
1282 A. P. Kaestner et al.: Neutron imaging for porous media
depends on the degree of completion of these shells. This
makes neutrons an isotope-sensitive probe. Neutron imag-
ing (both radiography and tomography) can quantify very
small amounts of fluid, even when the pore space itself can-
not be resolved, as demonstrated in several porous media
studies (Schaap et al., 2008; Carminati et al., 2007; Robin-
son et al., 2008; Rudolph et al., 2012; Zarebanadkouki et al.,
2014; Zhang et al., 2010; Lal et al., 2014). It is particularly
relevant for investigations of water displacement in bulk sam-
ples where the detailed structure of the pore space is known,
is unchanging, or is of lesser importance in understanding the
fluid processes. The isotope sensitivity gives almost an order
of magnitude in contrast between hydrogen (1H) and deu-
terium (2H or D). This allows isotopic tracing of an individ-
ual pulse of water through a preconditioned porous medium,
identifying the spatial and temporal evolution of mixing be-
havior of fluids of similar density and viscosity (Zarebanad-
kouki et al., 2012). Furthermore, most metals are not opaque
to neutrons (in contrast to X-rays), and are less opaque than
the fluids. This means it is possible to observe fluid flow in
situ within metal jacketed pressure and/or high-temperature
vessels.
The flexibility of the instrumentation at neutron imaging
beamlines meets the needs of a wide user community, and
can cater for both large and small samples with a trade-
off between sample size and (spatial and temporal) resolu-
tion. Ongoing instrument development is steadily pushing
the frontiers in capability and making new experiments pos-
sible. Here, we review recent advances in spatial and tempo-
ral performance at NEUTRA (Lehmann et al., 2001), ICON
(Kaestner et al., 2011a), and BOA (Morgano et al., 2014)
neutron imaging instruments at the Swiss spallation Neu-
tron Source (SINQ), Paul Scherrer Institut (PSI). We provide
a suite of examples to demonstrate state-of-the-art neutron
imaging methods and instrument features that can be pro-
vided on demand through the ordinary user program, with a
particular emphasis on those ideal for geological and porous
media experiments.
2 Methods and applications
The individual radiographs collected during neutron imaging
represent the neutrons that were transmitted through the sam-
ple. The mechanism that prevents the neutrons from reaching
the detector is a combination of absorption and scattering.
Scattering is often the dominant component of the neutron at-
tenuation coefficient (Sears, 1992), and some neutrons reach
the detector after multiple scattering events within the sam-
ple and instrument environment. The contribution of scat-
tered neutrons must be considered if the experiment objec-
tive includes quantifying sample structure and fluid distribu-
tion with high accuracy (Hassanein, 2006). The images are
mainly collected on a scintillator-based system with a cooled
precision camera carrying either a CCD (charge-coupled de-
Figure 1. Average number of neutrons per pixel as a function
of exposure time and pixel size calculated for a neutron flux of
107 neutrons cm−2 s−1.
vice) or a sCMOS (scientific complementary metal-oxide
semiconductor) detector chip. The two chip technologies
have different advantages and complement each other. CCD
chips have higher quantum efficiency and larger full well
depth, making them ideal for long time exposures. In con-
trast, the sCMOS has a much shorter readout time, allowing
high frame rates with lower readout noise levels, and making
it the preferred choice for real-time experiments with very
low neutron counts. For some applications an amorphous sil-
icon flat panel detector is also suitable. At PSI the chosen
camera is mounted in a camera box that gives adjustable fo-
cal distances, field of view (FOV) dimensions, and image
pixel resolution. The standard PSI boxes allow an FOV of
15–300 mm and pixel sizes down to 6.5 µm.
When designing an experiment the key consideration
when selecting the camera is its ability to resolve the de-
tails of interest with sufficient spatial and temporal resolu-
tion. The contrast between the phases in the sample also
plays an important role. The contrast between phases occurs
because each phase or component in the sample has a differ-
ent attenuation coefficient. The number of captured neutrons
determines how well this contrast can be resolved, with the
difference between attenuation coefficients and the signal-
to-noise ratio determining detectability. Figure 1 shows the
average number neutrons (N ) that can be detected for dif-
ferent exposure times and pixel sizes for a neutron flux of
107 neutrons cm−2 s−1. The signal-to-noise ratio (SNR) is re-
lated to the neutron count at the detector by
√
N since the
noise has a Poisson distribution. The Poisson nature of the
noise makes the SNR vary across the image with sample di-
mensions and composition. The scaling of the number of cap-
tured neutrons to the grayscale values presented in the im-
ages varies with the configuration of detection system, i.e.,
the scintillator–lens–camera combination used.
Solid Earth, 7, 1281–1292, 2016 www.solid-earth.net/7/1281/2016/
A. P. Kaestner et al.: Neutron imaging for porous media 1283
Figure 2. Comparison of the neutron radiographs of the gadolinium Siemens star test object based on (a) standard high-resolution neutron
instrument (Kaestner et al., 2011a) and (b) the Neutron Microscope prototype (Trtik et al., 2015).
2.1 Neutron imaging with high spatial resolution
Most high-resolution neutron imaging systems today oper-
ate with resolutions on the order of several tens of microns.
This applies to camera-scintillator-based systems (Kaestner
et al., 2011a; Williams et al., 2012) as well as pixel detectors
(Jakubek et al., 2005; Tremsin et al., 2012). Higher resolution
can be achieved using an arrangement were the scintillator is
tilted to a shallow angle to the beam, and combined with a
mirror (Boillat et al., 2008). This approach has the ability
to increase the spatial resolution in one direction while the
resolution in the other direction remains unchanged, produc-
ing images with rectangular pixels and thus anisotropic res-
olution. More recently, sub-ten micron resolution has been
achieved using a pixel detector in combination with a cen-
troiding technique to estimate the impact position of each de-
tected neutron (Vavrik et al., 2014). In contrast, achromatic
neutron microscope based on axisymmetric focussing mir-
rors for neutrons (so-called Wolter optics) have the potential
to yield significant improvements in neutron flux and spa-
tial resolution (Liu et al., 2013), but the current resolution of
cold neutron Wolter optics is still limited to several tens of
microns.
A first prototype of a microscope that magnifies the ra-
diograph by a factor of 4.3 on a gadolinium oxysulfide 4 µm
thick (Gd2O2S:Tb) scintillator screen has been developed at
PSI within the Neutron Microscope Project. This system is
based on a magnifying lens for light and a low-noise cam-
era of either CCD or sCMOS type. Using this configuration,
pixel sizes down to 1.5 µm can be obtained at a resolution
of 7.6 µm (Trtik et al., 2015). Radiographs of a Siemens star
test object obtained using the so-called regular “micro-setup”
and the new Neutron Microscope clearly demonstrate the im-
provement in spatial resolution (Fig. 2), with the increased
exposure times being the natural consequence of the smaller
pixels of the Neutron Microscope images. The Neutron Mi-
croscope image required a 25 min exposure time, while the
micro-setup image was acquired in 90 s.
To shorten the acquisition times, and therefore allow fur-
ther practical improvement of the spatial resolution, scin-
tillator screens based on isotopically enriched gadolin-
ium oxysulfide (157Gd2O2S:Tb) have been developed (Tr-
tik and Lehmann, 2015). When linked to tailor-made high-
numerical-aperture magnifying optics, these scintillators can
provide images with a spatial resolution of about 5 µm (Tr-
tik and Lehmann, 2016). A more advanced version of the
Neutron Microscope is currently being designed and imple-
mented at PSI as a self-contained instrument that can, with a
moderate effort, be used at different beamlines.
2.1.1 High-resolution neutron imaging of drying in a
porous medium
Despite the relatively long acquisition times needed for
imaging with the prototype Neutron Microscope, the instru-
ment already allows observation of even slower processes in
radiographic mode.
A sample of a model porous medium was used to demon-
strate the spatiotemporal capabilities of the Neutron Micro-
scope at the BOA beamline. The sample consists of a SiO2
capillary (of 1.25 and 1.0 mm inner and outer diameter re-
spectively) filled with stainless steel spheres of about 1.0 mm
in diameter. The sample was initially saturated with H2O and
the water left evaporating freely under ambient conditions.
The field of view was equal to approximately 3× 3 mm2, and
the pixel size of the images was equal to 6 µm pixel size. This
www.solid-earth.net/7/1281/2016/ Solid Earth, 7, 1281–1292, 2016
1284 A. P. Kaestner et al.: Neutron imaging for porous media
Figure 3. Time series of the evaporation of water from a model
porous medium sample. The field of view is approximately
3× 3 mm2. The images were acquired with 6 µm pixel size (4×
binning) using 90 s acquisition time. Only every 10th image is pre-
sented; therefore the time gap between the individual presented im-
age is about 15 min. The slightly darker trapezoidal object in the
bottom right FOV is hydrogenous material within adhesive alu-
minum tape used for the sample fixation.
series was not acquired at highest possible spatial resolution.
A 4× 4 binning was used to increase the neutron dose per
pixel. Individual projections’ acquisition times were 90 s.
Visualization of the time series (Fig. 3) demonstrates that
processes occurring in porous media can be investigated with
high spatial resolution in 2-D. The data revealed the hetero-
geneous removal of water (darkest gray/black) from the pore
space between the capillary (near transparent) and the beads
(mid-gray). It also shows that the water forms menisci at the
solid–solid boundaries when air enters the system over the
time span of more than 6 h. The images are of sufficiently
sharpness to allow quantitative measurements of the interfa-
cial curvatures. The changes are clearly observable, even if
the subsequent images are compared (every tenth image is
presented in Fig. 3 for convenience reasons only).
Although the data presented are from a 2-D study, the
quality of the images indicates that 3-D high-resolution neu-
tron imaging of even slow processes could be performed
when coupled to advanced reconstruction techniques (de-
scribed later in Sect. 2.3).
2.2 Time-lapse neutron CT
The distribution of fluids in porous media can be consid-
ered as static under steady-state flow of a single fluid, or
as dynamic under variable flow or composition. For the dy-
namic case, when capturing the effects of diffusion or flow
processes over time is the objective of the experiment, time-
lapse or 4-D imaging is required. With neutron imaging, ex-
perimental approaches vary with the required contrast, spa-
tial resolution, and the temporal development of the observed
process. The main challenge during a dynamic CT experi-
ment is to avoid artifacts caused by changes within the sam-
ple during imaging and the performance of the acquisition
system. Reconstruction methods generally assume that the
sample is invariant during the acquisition of all the projec-
tion data used for the reconstruction.
Changes to a sample during the acquisition of the data for
a single 3-D image can be induced by vibrations and centrifu-
gal forces imposed by the sample environment. However, in
many experiments these effects can be neglected, and most
artifacts relate to the acquisition rate. Motion artifacts can
appear if the acquisition rate is low relative to the observed
process. Sub-pixel displacement rates within the sample are
sufficient to cause motion artifacts in the reconstructed data.
The motion artifacts appear as tangential streaks emerging
from the changing region, and poorly defined phase bound-
aries.
Increasing acquisition speeds would reduce motion ar-
tifacts, but can be counterproductive, as faster acquisition
means lower SNR, and image quality will be substantially re-
duced leading to possibly coarser resolution. Hence, the chal-
lenge with 4-D CT experiments is to minimize the impact of
motion artifacts while providing sufficient image contrast to
allow observations of the process of interest in a sample that
is unaffected by the acquisition procedure.
2.2.1 High dynamic range and spatial resolution
Detecting small changes in the fluid distribution with high
spatial resolution requires longer exposure times to capture
a sufficient neutron dose (number of detected neutrons per
pixel) to resolve the attenuation contrast between phases. Ex-
posure times on the order of several tens of seconds or even
minutes per projection are not uncommon with neutron imag-
ing. Thus, a typical duration for a neutron CT scan is sev-
eral hours. Increasing the number of neutrons improves con-
trast and the signal-to-noise ratio, thereby improving post-
processing segmentation performance and reducing the er-
rors in qualitative and quantitative analysis of the fluid distri-
bution in the sample.
For most aqueous processes, the long exposure times mean
that significant changes in the fluid distribution are likely
over a single exposure, and that strong motion artifacts will
appear in the reconstructed data. Two methods to reduce the
impact of these artifacts use alternative acquisition sequences
that have a time-averaging effect in the reconstructed data.
The motion’s artifact streaks are replaced by a smooth gradi-
ent across the extent of the dynamic region, which appears as
edge unsharpness in the reconstructed data set, but does not
affect static regions.
The first approach uses the repetition of several scans with
equiangular increments each with a slight angular offset upon
start. The second uses angular increments determined by the
golden ratio (Köhler, 2004; Kaestner et al., 2011b). The lat-
Solid Earth, 7, 1281–1292, 2016 www.solid-earth.net/7/1281/2016/
A. P. Kaestner et al.: Neutron imaging for porous media 1285
ter method is more flexible since the golden ratio generates
an infinite series of angles that always spans the full angu-
lar range. Therefore, the acquisition can be stopped at any
time, and reconstruction can be performed on any number of
sequential projections from the data set. Scans that are too
short do not satisfy the sampling theorem which can intro-
duce sampling artifacts. The major advantage of these alter-
native acquisition sequences is that they can be decomposed
into shorter sub-scans (i.e., each scan uses a subset of the to-
tal projections collected), therefore producing a time series
of CT data from a single acquisition session. The time inter-
val of each 3-D image (i.e., the number of projections used
to reconstruct a single 3-D image) can be selected after the
experiment. This means the exact start point and timescale of
the phenomena in a specific sample do not have to be known
ahead of the experiment. The timescale of the reconstructed
data can be tuned during reconstruction by selecting an ad-
equate subset of projections. Techniques for reconstructing
this kind of data and an example with experiment data are
described in Sect. 2.3 below.
2.2.2 Fast acquisition
When the process of interest is fast compared to the projec-
tion acquisition rate, the alternative acquisition schemes do
not prevent motion artifacts. Under these conditions the pro-
jection (frame) acquisition rate must be increased at the cost
of neutron dose. As a consequence, the dynamic range of the
gray levels and SNR will be inferior in the reconstructed data.
sCMOS cameras allow frame rates greater than 25 frames
per second (making it possible to acquire an entire set of
CT projection data in about 10 s). Under such acquisition
conditions, the sample table is continuously turning, while
the camera acquires projections at a specified frame rate to
avoid unnecessary time delay caused by discrete stepping.
This so-called on-the-fly tomography was demonstrated by
Zarebanadkouki et al. (2015), who acquired projections for
tomogram in about 3 min. However, turntable speed and the
neutron dose are the limiting factors for on-the-fly experi-
ments, especially at high spatial resolution.
The neutron dose per pixel can be improved by increas-
ing the pixel size (Fig. 1), either by binning on the camera
side or by increasing the focal distance of the lens; but this
reduces the spatial resolution of the images. A low SNR in
the experiment projection data increases the importance of
high-quality reference images. Lower average neutron counts
per pixel mean more reference images are needed to avoid
contamination of the data by noise from both the open beam
(flat/bright) and dark current (dark) images.
2.2.3 Using on-the-fly tomography to study water
uptake
Rate and location of root water uptake by plants growing in
soil is poorly understood due to the dynamic behavior of soil
Figure 4. (a) Neutron radiography of a 2-week old lupine in a cylin-
drical container of sandy soil, 27 mm in diameter. (b, c, d) Horizon-
tal slices of the reconstructed data at different depths indicated by
the colored lines in the radiography. (e) 3-D rendering of the root
system reconstructed using 181 projections
and roots of transpiring plants. In 2-D, high spatiotemporal
resolution coupled to high sensitivity to the contrast between
normal (H2O) and deuterated water (D2O) has allowed neu-
tron radiography to successfully resolve average water up-
take mechanism in a small Lupine plant (Zarebanadkouki
et al., 2012, 2014). However, providing experimental data to
validate the refine model and determining the relative contri-
butions of the competing water transport pathways requires
experimental quantification of the 3-D spatial distribution of
D2O across the root tissue through time.
Performing these neutron tomography experiments was
challenging because of the spatial and temporal resolution
required; the process has been proven to take place within
the course of several minutes depending on root thickness.
Frame rates of 6 fps were needed to remove motion artifacts
(to keep the water displacements below one pixel over the
entire 3-D data set) during on-the-fly tomography.
The cylindrical samples of sandy soil were 27 mm in di-
ameter and 100 mm in length. D2O transport was imaged
with a pixel size of 45 µm using the Andor NEO sCMOS
camera with an FOV of 55× 116 mm (corresponding to
1200× 2560 pixels). The exposure time per projection was
167 ms (scan time of 30 s). The 3-D volumes were recon-
structed from 181 projections uniformly distributed over 180
degrees. This represents a 6× increase in temporal resolu-
tion compared to Zarebanadkouki et al. (2015) and with no
reduction in spatial resolution. A part of this speed increase is
contributed to the higher neutron flux at ICON. The neutron
dose here was about 100 neutrons pixel−1, which results in a
lower SNR, but image quality is still acceptable for the in-
vestigation thanks to the high contrast between the different
www.solid-earth.net/7/1281/2016/ Solid Earth, 7, 1281–1292, 2016
1286 A. P. Kaestner et al.: Neutron imaging for porous media
Figure 5. Time series neutron tomography of D2O transport into the root of a 2-week old lupine (nighttime). These images show the change
in neutron attenuation across the root tissue at different times after D2O injection (time is indicated in minutes). As D2O enters the root tissue,
D2O : H2O increases and neutron attenuation decreases. D2O : H2O is indicated by low attenuation (blue); low D2O : H2O is indicated by
high attenuation (yellow). The images show a 5× 5 mm region of one horizontal slice through the 3-D data at a depth of 50 mm from soil
surface.
phases. The first 3-D data set represents the steady-state con-
ditions before D2O was injected into the soil near the roots
and its transport was simultaneously monitored using a time
series neutron radiography (Figs. 4, 5).
The reconstructed data from the steady-state experiment
(Fig. 4a) show that the image acquisition parameters provide
sufficient contrast to enable segmentation of the roots from
the soil.
Working at a single depth (50 mm from the soil surface)
and tracking the D2O concentrations as a function of time
(Fig. 5) shows the radial transport into the root. As D2O
moves into the root, the neutron attenuation decreases with
a sharp contrast between roots and their sounding soil. There
is a distinct transition from H2O (yellow) to D2O) (blue) over
the first 5 min after D2O injection. This study proves that 4-D
neutron (on-the-fly) tomography can capture the flow of wa-
ter across the root tissue in 3-D with sufficiently high spatial
and temporal resolution to verify root water uptake models.
To this end, the transport of D2O across root tissue during
day and night should be modeled by the diffusion–convection
equation proposed in Zarebanadkouki et al. (2014). Note that
for the case of dominant cell-to-cell transport, a sharp gradi-
ent in concentration of D2O across the root tissue can be ex-
pected, while the gradient can be expected to be more grad-
ual for the case of a dominant apoplastic pathway since D2O
can quickly bypass the root tissue and reach the xylem. Data
from 4-D imaging experiments showing the water distribu-
tion over time are urgently needed to verify models and to
increase the understanding of the physical mechanisms con-
trolling water, solute, and hormone transport in the roots.
2.3 Towards new reconstruction methods
Experimental projection data are usually reconstructed using
the analytical filtered back projection (FBP) reconstruction
algorithm (Buzug, 2008), which requires a large number of
projections to perform well (i.e., to fulfill the sampling theo-
rem). FBP is also sensitive to nonuniform angular sampling
of the projection data. This can be a major problem when
increasing acquisition speed for higher temporal resolution.
Undersampled projection data are best treated using itera-
tive reconstruction techniques, as these can account for var-
ious inaccuracies required by the experimental method such
as nonuniform sampling steps, low-intensity dynamics, and
Solid Earth, 7, 1281–1292, 2016 www.solid-earth.net/7/1281/2016/
A. P. Kaestner et al.: Neutron imaging for porous media 1287
Figure 6. Reconstruction from 60 projections to show the difference
iterative methods can make to resolving key spatial information in
fluid flow studies. The images show an axial slice (1000×1000 pix-
els) from one time frame of a 4-D experiment performed at ICON.
The darkest areas depict the different times showing the progress of
water entering the sample. The mid-gray regions are gravel particles
which have approx. 10 % internal porosity.
SNR in the measurements. These reconstruction techniques
also allow the imposition of some regularity (e.g., smooth-
ness) or data consistency (e.g., rejection of nonzero values)
into the process to find the solution. The benefit hereby is
to improve image quality, particularly for undersampled and
under-exposed projection data.
Commonly, a priori information assumes some expected
local intensity correlations, i.e., regions that remain un-
changed throughout the experiment. In the fluid-flow prob-
lems of interest here, the initial stationary “dry” stage is
an ideal “prior” reference for iterative reconstruction. Si-
multaneous iterative reconstruction (SIRT) and the conju-
gate gradient least square (CGLS) methods employed are
now available (Van Eyndhoven et al., 2015; Kazantsev et al.,
2015a). Here we summarize the findings that are of spe-
cific interest to porous media experiments. Figure 6 shows
a 1000× 1000 pixel slice reconstructed using the different
methods to demonstrate the difference in performance using
undersampled projection data (60 projections acquired using
golden ratio protocols, see Sect. 2.2.1). This is 4 % of the
data needed to fulfill the Nyquist theorem; i.e., severely un-
dersampled and strong streak artifacts are to be expected. The
Figure 7. Rendered volume of the stationary “dry” sample (sand-
stone) prior to water ingress. Reconstruction from 150 projections
using a CGLS–TV algorithm.
slices were reconstructed using FBP and three different iter-
ative methods.
It can be seen that the CGLS–NLST (non-local spa-
tiotemporal) method (Kazantsev et al., 2015a) gives signifi-
cantly better resolution (sharper transitions between different
phases) and better contrast separation between the phases.
Sampling artifacts are much weaker and the SNR is higher
in these data since the regularization is driven by the a priori
information provided by a pre-reconstructed ”dry” station-
ary initial image (Fig. 7) reconstructed from 150 projections
using a CGLS–TV algorithm.
It is possible to reconstruct a time-lapse series showing
the condition of the sample, using smaller subsets of projec-
tion data from one long sequence of time-evolving projec-
tion data, provided the data are acquired using the golden
ratio method. The improved feature resolution provided by
the CGLS–NLST reconstruction (Kazantsev et al., 2015a) al-
lows us to quantify the liquid volumes in the sample through
time at a minimum of 3× higher temporal resolution than
possible with FBP, and at lower image noise (Fig. 8).
Another successful approach (Van Eyndhoven et al., 2015)
for the reconstruction of undersampled time-lapse projection
data uses the reconstructed stationary stage (i.e., extracting
the rock phase) to define the stationary regions, and then it-
eratively refines the other phases (in this case air and water)
by applying known intensity constraints (Kazantsev et al.,
2015a, b; Van Eyndhoven et al., 2015).
The stationary region is redefined as the experiment pro-
gresses, so the reconstruction focusses on the dynamic re-
gions only. This approach gives much better spatiotempo-
ral resolution (data comparable to that of the CGLS–NLST
method with fewer than 20 projections) than has been previ-
www.solid-earth.net/7/1281/2016/ Solid Earth, 7, 1281–1292, 2016
1288 A. P. Kaestner et al.: Neutron imaging for porous media
Figure 8. The fluid phase in the rock sample at three different times of the water ingress. Each volume is reconstructed from 60 projections
using the CGLS–NLST method.
Figure 9. Cropped part (22.1× 60.0 mm2) of the vertical cross sections through the 3-D X-ray (a) and neutron data sets (b–c) of the intact soil
sample taken into a cylinder (a diameter of 34 mm, height of 87 mm) during various stages of the recurrent ponded infiltration experiment:
(a) and (b) before experiment when the macropore in the center of the image is filled with air, (c) during the infiltration when the macropore
is entirely filled with water, (d) during continuing infiltration (e) after draining the sample, and (f) during second infiltration episode when
the entrapped air formed in the macropore.
ously achieved (Kazantsev et al., 2014b, 2015a); however it
is more parametrized and data-dependent. Current tests show
that reconstructions from as few as 18 projections can be seg-
mented.
2.4 Bimodal imaging – combining neutron and X-ray
imaging
Every imaging modality has it strengths and weaknesses, and
one method is rarely capable of providing all the information
needed. Integrating data from a second imaging modality can
provide important complementary information and reduce
ambiguity. Combining neutron and X-ray CT is one example
of bimodal imaging particularly relevant for investigations of
flow in porous media. The attenuation coefficients of a par-
ticular phase will be significantly different in the two data
sets, and therefore multivariate methods will provide better
results than those using single data sources. In some cases
the contrast is even reversed between the modalities, e.g., wa-
ter which is low contrast for X-rays while it provides a high
contrast for neutrons.
There are two typical uses for bimodal imaging: (1) the
sample is static but it is difficult to identify relevant features
due to small differences in contrast between the present ma-
terials and (2) samples with a dynamic component. In the lat-
ter case, one modality can be used to identify the static struc-
tures, while the other is used to capture the displacements
caused by the observed process. For experiments with com-
plex sample compositions, combining the two approaches to
increase performance and data quality may be required.
Bimodal imaging using neutrons and X-rays is available
to users at NEUTRA (Mannes et al., 2015; Vontobel et al.,
2016) and will soon be operational at ICON (Kaestner et al.,
2015). These neutron beamlines are also equipped with X-
ray sources so both neutron and X-ray images can be per-
formed in situ without moving the sample. X-ray and neutron
images can be collected either simultaneously or interleaved
(one modality after the other), removing the delays between
scans that often occur when ex situ X-ray sources are used.
Solid Earth, 7, 1281–1292, 2016 www.solid-earth.net/7/1281/2016/
A. P. Kaestner et al.: Neutron imaging for porous media 1289
Figure 10. Bivariate histograms of cropped part of the X-ray and corresponding neutron tomograms, representing a soil sample with large
macropores during various stages of recurrent ponding infiltration experiment. Histograms show (a) empty macropore before the infiltration
was started, (b) filling of the macropores during the first infiltration, and (c) partial filling of the macropores during the second infiltration.
Figure 11. Macropore system that represents 1.97 % of the sample volume segmented from X-ray tomogram (left). Time sequence of water
contents in the macropore system derived from series of 22 tomograms (right). The blue columns indicate the time of two ponding infiltration
episodes.
One key advantage of using the same sample manipula-
tion environment is the reduced registration required to align
the image data from the modalities onto a common coordi-
nate system. This is in particular true for the installation at
NEUTRA where the X-ray and neutron beams have a very
similar geometry, and makes pixel-wise comparison possi-
ble. At ICON, an alternative approach has been taken, and
the divergent X-ray source and beamline mounted perpen-
dicular to the neutron beam direction. This installation fur-
ther reduces the time between imaging using each modality,
and makes simultaneous imaging using both modalities pos-
sible. The only need to drive ex situ X-ray imaging in this
case is the potential for higher spatial resolutions that can be
achieved elsewhere.
There are several strategies to analyze bivariate data. The
work flow usually starts with a registration step to align the
data sets onto a common coordinate system. This guaran-
tees that pixel-/voxel-wise analysis of the two data sets is
possible. Approaches that start data fusion during the recon-
struction stage first register the projection data Kazantsev
et al. (2014a). Other approaches reconstruct the data inde-
pendently and then fuse at a later point in time. Development
of these strategies is ongoing and the choice of data fusion
strategy will depend both on the sample type and the infor-
mation to be extracted from the experiment.
2.4.1 Bimodal imaging to study preferential water flow
in soil
As an example of combined X-ray and neutron tomogra-
phy imaging, we present a study of water and air behav-
ior in soil. The infiltration of water and air trapping was
studied on intact samples of coarse sandy loam soil from a
mountainous site (Cambisol series, Korkusova Hut, Sumava
Mountains, Czech Republic) from a depth of 40 cm below
the surface. Preferential and localized water flow often oc-
curs in this soil (Dohnal et al., 2012), with the majority of
the water utilizing the small fraction of the soil volume char-
acterized by soil macropores, fractures, and high-porosity
regions, which results in uneven weathering. The preferen-
tial flow can be numerically simulated by dual-continuum
models (e.g., Gerke et al., 2007). However, current models
www.solid-earth.net/7/1281/2016/ Solid Earth, 7, 1281–1292, 2016
1290 A. P. Kaestner et al.: Neutron imaging for porous media
do not account for trapped air that can efficiently obstruct
the macropores and significantly reduce soil permeability for
water (Snehota et al., 2015); thus these model predictions
fail.
The experiment performed at the NEUTRA beamline con-
sisted of two infiltration episodes during which a layer of
D2O : H2O mixture (in the approx. mass ratio of 95 : 5) was
maintained on the sample surface (a condition known as
ponding), while water was left to drain the sample freely
through the bottom by gravity. Flooding of the sample sur-
face and maintaining the water level was controlled remotely.
One X-ray and two neutron 3-D tomography data sets (tomo-
grams) were acquired in the initial state before the first infil-
tration was begun. Another 20 neutron tomograms were ac-
quired during the following 25 h of the experiment (see sub-
set of the data in Fig. 9).
The neutron and X-ray tomograms were reconstructed by
the MuhRec3 code (Kaestner, 2011) using 201 projections
over 180◦. The detector used for neutron imaging was a
LiF/ZnS scintillator screen, 100 µm thick, photographed by
a CCD camera (Andor iKON L BW936). The exposure time
for each projection was 8 s and the acquisition time for one
tomogram was approx. 50 min. The nominal pixel size was
0.10× 0.10 mm2.
Fine co-registration of the X-ray and neutron tomograms
was done by searching for the minimum of sum of differ-
ences while rotating and translating the X-ray tomogram as
a rigid body. Bivariate histograms shown in Fig. 10 helped
identify a threshold of 14 500 a.u. for subsequent segmenta-
tion of the macropores from the X-ray data.
The segmented X-ray tomogram was then used as a binary
mask (see Fig. 11, left) before the evolving water volume
in the macropores was determined from the neutron tomo-
grams. The volume of water and average water content in
the macropore system was calculated by subtracting the data
from the dry sample and dividing the grayscale values by
the attenuation coefficient of water (Fig. 11, right). The data
show a reduction in the water content prior to and during the
second infiltration, which results from air trapping in some
of the pores. The data are being used to further develop the
follow-up model by Fucik et al. (2010) that is based on the
two-phase flow approach.
3 Conclusions
We have shown, using state-of-the-art approaches, that neu-
tron imaging beamlines are a vital tool for observing pro-
cesses in porous media. Routine methods are now approach-
ing, or exceeding the spatial and temporal scales that can
be achieved with lab-based X-ray sources. However, it is
this capability coupled to the high sensitivity to hydrogen
that makes neutron imaging such an ideal probe for high-
resolution experiments (2-D or 3-D over time) into the spa-
tiotemporal distribution of fluids in porous media. PSI in-
strument options achieve spatial resolutions on the order
of a 1–50 µm and 3-D image acquisition rates 1–7 CT vol-
umes min−1; yet, often this was achieved at the cost of poorer
image quality (consequence of lower signal-to-noise ratio).
The combination of experiment equipment and numerical
methods summarized here marks a major step forwards in
this regard.
While it is important that the data can be acquired, the
techniques shown here aim to increase the information that
can be extracted from the data as well as increase the data ac-
quisition rate. The neutron imaging community is currently
focussed on developing improved methods for multidimen-
sional and multimodal data analysis under low SNR condi-
tions through close collaboration between the user commu-
nity, instrument scientists, and algorithm developers. For ex-
periments that produce data with intrinsic time structure, it
is often beneficial to perform the analysis in 4-D instead of
processing the data as a sequence of individual 3-D images.
Ideally, the subsequent post-processing quantitative analyses
will also involve the time structure to yield more accurate
analyses.
Already, thanks to recent technological improvements,
neutron imaging is a good choice to observe and quantify
transport processes in porous media at different scales in time
and space, regardless of whether the pore space can be re-
solved or not.
Acknowledgements. For the experiments performed at NEUTRA,
we kindly acknowledge the instrument support by Jan Hovind,
Martina Sobotkova, and Vladka Jelinkova. We would also like to
acknowledge the support and funding from COST action MP1207,
the Czech Science Foundation (project no. 14-03691S), as well
as the European Union’s Seventh Framework Programme for
Research and Technological Development under the NMI3-II grant
no. 283883, SINQ 20110581.
Edited by: H. Steeb
Reviewed by: F. Fusseis and R. Jänicke
References
Anderson, I., McGreavy, R., and Bilheux, H. (Eds.): Neutron Imag-
ing and Applications, Springer Verlag, 2009.
Boillat, P., Kramer, D., Seyfang, B., Frei, G., Lehmann, E., Scherer,
G., Wokaun, A., Ichikawa, Y., Tasaki, Y., and Shinohara, K.: In
situ observation of the water distribution across a PEFC using
high resolution neutron radiography, Electrochem. Commun.,
10, 546–550, 2008.
Buzug, T.: Introduction to Computed Tomography: From photon
statistics to modern cone-beam CT, Springer, 2008.
Carminati, A., Kaestner, A., Ippisch, O., Koliji, A., Lehmann, P.,
Hassanein, R., Vontobel, P., Lehmann, E., Laloui, L., Vulliet, L.,
and Flühler, H.: Water flow between soil aggregates, Transport
Porous Med., 68, 219–236, 2007.
Solid Earth, 7, 1281–1292, 2016 www.solid-earth.net/7/1281/2016/
A. P. Kaestner et al.: Neutron imaging for porous media 1291
Cnudde, V. and Boone, M.: High-resolution X-ray computed to-
mography in geosciences: A review of the current technology
and applications, Earth-Sci. Rev., 123, 1–17, 2013.
Dobson, K. J., Coban, S. B., McDonald, S. A., Walsh, J. N., At-
wood, R. C., and Withers, P. J.: 4-D imaging of sub-second dy-
namics in pore-scale processes using real-time synchrotron X-
ray tomography, Solid Earth, 7, 1059–1073, doi:10.5194/se-7-
1059-2016, 2016.
Dohnal, M., Vogel, T., Sanda, M., and Jelinkova, V.: Uncertainty
analysis of a dual-continuum model used to simulate subsurface
hillslope runoff involving oxygen-18 as natural tracer, J. Hydrol.
Hydromech., 60, 194–205, 2012.
Fucik, R., Sakaki, J. M. T., Benes, M., and Illangasekare, T.: Sig-
nificance of dynamic effect in capillarity during drainage exper-
iments in layered porous media, Vadose Zone J., 9, 697–708,
2010.
Gerke, H., Dusek, J., Vogel, T., and Kohne, J.: Two-dimensional
dual-permeability analyses of a bromide tracer experiment on a
tile-drained field, Vadose Zone J., 6, 651–667, 2007.
Hassanein, R.: Correction methods for the quantitative evaluation
of thermal neutron tomography, Phd. thesis eth no. 16809, Swiss
Federal Institute of Technology, doi:10.3929/ethz-a-005273682,
2006.
Jakubek, J., Holy, T., Lehmann, E., Pospisil, S., Uher, J., Vacikc, J.,
and Vavrika, D.: Spatial resolution of Medipixnext term-2 device
as neutron pixel detector, Nucl. Instrum. Meth. A, 546, 164–169,
2005.
Kaestner, A.: MuhRec – a new tomography reconstructor, Nucl. In-
strum. Meth. A, 651, 156–160, 2011.
Kaestner, A., Hartmann, S., Kuehne, G., Frei, G., Gruenzweig, C.,
Josic, L., Schmid, F., and Lehmann, E.: The ICON beamline – A
facility for cold neutron imaging at SINQ, Nucl. Instrum. Meth.
A, 659, 387–393, 2011.
Kaestner, A. P., Münch, B., Trtik, P., and Butler, L. G.: Spatio-
temporal computed tomography of dynamic processes, Opt.
Eng., 50, 123201, doi:10.1117/1.3660298, 2011.
Kaestner, A., Morgano, M., Hovind, J., and Lehmann, E.: Bimodal
Imaging Using Neutrons and X-rays, in: Proceedings of the Inter-
national Symposium on Digital Industrial Radiology and Com-
puted Tomography, http://www.ndt.net/events/DIR2015/Paper/
58_Kaestner.pdf (last access: 19 August 2016), 2015.
Kardjilov, N., Manke, I., Hilger, A., Strobl, M., and Banhart, J.:
Neutron imaging in materials science, Mater. Today, 14, 248–
256, 2011.
Kazantsev, D., Ourselin, S., Hutton, B. F., Dobson, K. J., Kaestner,
A. P., Lionheart, W. R. B., Withers, P. J., Lee, P. D., and Ar-
ridge, S. R.: A novel technique to incorporate structural prior in-
formation into multi-modal tomographic reconstruction, Inverse
Probl., 30, 065004, doi:10.1088/0266-5611/30/6/065004, 2014a.
Kazantsev, D., Thompson, W., Dobson, K. J., Kaestner, A., Lion-
heart, W., Withers, P., and Lee, P.: Simultaneous 4D-CT recon-
struction using higher order spatial regularization and edge en-
hancement based on global information in temporal domain, In-
verse Probl. Imag., 2014b.
Kazantsev, D., Eyndhoven, G. V., Lionheart, W., Withers, P., Dob-
son, K., McDonald, S., Atwood, R., and Lee, P.: Employing tem-
poral self-similarity across the entire time domain in computed
tomography reconstruction, P. T. R. Soc. London A, 373, 1–14,
2015a.
Kazantsev, D., Thompson, W. M., Lionheart, W. R. B., Eynd-
hoven, G. V., Kaestner, A. P., Dobson, K. J., Withers, P. J., and
Lee, P. D.: 4D-CT reconstruction with unified spatial-temporal
patch-based regularization, Inverse Probl. Imag., 9, 447–467,
doi:10.3934/ipi.2015.9.447, 2015b.
Köhler, T.: A Projection Access Scheme for Iterative Reconstruc-
tion Based on the Golden Section, in: Nuclear Science Sympo-
sium Conference Record, IEEE, vol. 6, 3961–3965, 2004.
Krane, K.: Introductory nuclear physics, John Wiley & Sons, 845
pp., 1988.
Lal, S., Poulikakos, L., Gilani, M. S., Jerjen, I., Vontobel, P., Partl,
M., Carmeliet, J., and Derome, D.: Investigation of Water Uptake
in Porous Asphalt Concrete Using Neutron Radiography, Trans-
port Porous Med., 105, 431–450, 2014.
Lehmann, E. and Kaestner, A.: 3D neutron imag-
ing, Encyclopedia of Analytical Chemistry, a9123,
doi:10.1002/9780470027318.a9123, 2009.
Lehmann, E. H., Vontobel, P., and Wiezel, L.: Properties of the ra-
diography facility NEUTRA at SINQ and it’s potential for use
as European reference facility, Nondestruct. Test. Eva., 16, 191–
202, 2001.
Liu, D., Hussey, D., Gubarev, M. V., Ramsey, B. D., Jacobson,
D., Arif, M., Moncton, D. E., and Khaykovich, B.: Demon-
stration of achromatic cold-neutron microscope utilizing ax-
isymmetric focusing mirrors, Appl. Phys. Lett., 102, 183508,
doi:10.1063/1.4804178, 2013.
Mannes, D., Schmid, F., Frey, J., Schmidt-Ott, K., and Lehmann,
E.: Combined Neutron and X-ray imaging for non-invasive in-
vestigations of cultural heritage objects, Physics Procedia, 69,
653–660, 2015.
Morgano, M., Peetermans, S., Lehmann, E., Panzner, T., and Filges,
U.: Neutron imaging options at the BOA beamline at Paul Scher-
rer Institut, Nucl. Instrum. Meth. A, 754, 46–56, 2014.
Robinson, B., Moradi, A., Schulin, R., Lehmann, E., and Kaest-
ner, A.: Neutron Radiography for the Analysis of Plant-Soil In-
teractions, Encyclo, a9023, doi:10.1002/9780470027318.a9023,
2008.
Rudolph, N., Esser, H. G., Carminati, A., Moradi, A. B., Hilger,
A., Kardjilov, N., Nagl, S., and Oswald, S. E.: Dynamic oxygen
mapping in the root zone by fluorescence dye imaging combined
with neutron radiography, J. Soil. Sediment., 12, 63–74, 2012.
Schaap, J., Lehmannn, P., Kaestner, A., Vontobel, P., Hassanein, R.,
Frei, G., de Rooij, G., Lehmann, E., and Flühler, H.: Measur-
ing the effect of structural connectivity on the water dynamics in
heterogeneous porous media using speedy neutron tomography,
Adv. Water Resour., 31, 1233–1241, 2008.
Sears, V.: Neutron scattering lengths and cross sections, Neutron
News, 3, 26–37, doi:10.1080/10448639208218770, 1992.
Snehota, M., Jelinkova, V., Sobotkova, M., Sacha, J., Vontobel, P.,
and Hovind, J.: Water and entrapped air redistribution in hetero-
geneous sand sample: Quantitative neutron imaging of the pro-
cess, Water Resour. Res., 51, 1359–1371, 2015.
Tremsin, A., McPhate, J., Vallerga, J., Siegmund, O., Feller, W.,
Lehmann, E., Kaestner, A., Boillat, P., Panzner, T., and Filges,
U.: Neutron radiography with sub-15 µm resolution through
event centroiding, Nucl. Instrum. Meth. A, 688, 32–40, 2012.
Trtik, P. and Lehmann, E.: Isotopically-enriched gadolinium-157
oxysulfide scintillator screens for the high-resolution neutron
imaging, Nucl. Instrum. Meth. A, 788, 67–70, 2015.
www.solid-earth.net/7/1281/2016/ Solid Earth, 7, 1281–1292, 2016
1292 A. P. Kaestner et al.: Neutron imaging for porous media
Trtik, P. and Lehmann, E.: Progress in High-resolution Neutron
Imaging at the Paul Scherrer Institut – The Neutron Microscope
Project, J. Phys. Conf. Ser., in press, 2016.
Trtik, P., Hovind, J., Grünzweig, C., Bollhalder, A., Thominet, V.,
David, C., Kaestner, A., and Lehmann, E. H.: Improving the
spatial resolution of neutron imaging at Paul Scherrer Institut
– The Neutron Microscope Project, Physics Procedia, 69, 169–
176, 2015.
Van Eyndhoven, G., Batenburg, K., Kazantsev, D., Van Nieuwen-
hove, V., Lee, P., Dobson, K., and Sijbers, J.: An Iterative CT
Reconstruction Algorithm for Fast Fluid Flow Imaging, IEEE T.
Image Process., 24, 4446–4458, 2015.
Vavrik, D., Jakubek, J., Kaestner, A., Krejci, F., Turecek, D., and
Zemlicka, J.: Modular pixelated detector system for neutron
imaging with micrometric resolution, in: 10th World conference
for neutron radiography – Book of abstracts, 2014.
Vontobel, P., Mannes, D., Kaestner, A., Schmid, F., and Lehmann,
E. H.: The X-ray option at the NEUTRA imaging beamline of the
spallation neutron source SINQ, Nuclear Instruments & Meth-
ods in Physics Research, Section A: Accelerators, Spectrometers,
Detectors, and Associated Equipment, in review, 2016.
Wildenschild, D. and Sheppard, A. P.: X-ray imaging and analy-
sis techniques for quantifying pore-scale structure and processes
in subsurface porous medium systems, Adv. Water Resour., 51,
217–246, 2013.
Williams, S., Hilger, A., Kardjilov, N., Manke, I., Strobl, M., Douis-
sard, P., Martin, T., Riesemeier, H., and Banhart, J.: Detection
system for microimaging with neutrons, J. Instrum., 7, P02014,
doi:10.1088/1748-0221/7/02/P02014, 2012.
Zarebanadkouki, M., Kim, Y. X., Moradi, A. B., Vogel, H. J., Kaest-
ner, A., and Carminati, A.: Quantification and Modeling of Local
Root Water Uptake Using Neutron Radiography and Deuterated
Water, Vadose Zone J., 11, 3, doi:10.2136/vzj2011.0196, 2012.
Zarebanadkouki, M., Kroener, E., Kaestner, A., and Carminati, A.:
Visualization of root water uptake: quantification of deuterated
water transport in roots using neutron radiography and numerical
modeling, Plant Physiol., 166, 487–499, 2014.
Zarebanadkouki, M., Carminati, A., Kaestner, A., Mannes, D.,
Morgano, M., Peetermans, S., Lehmann, E., and Trtik, P.: On-
the-fly neutron tomography of water transport into lupine roots,
Physics Procedia, 69, 292–298, 2015.
Zhang, P., Wittmann, F., Zhao, T., and Lehmann, E.: Neutron imag-
ing of water penetration into cracked steel reinforced concrete,
Physica B, 405, 1866–1871, 2010.
Solid Earth, 7, 1281–1292, 2016 www.solid-earth.net/7/1281/2016/