Detection of explosives, narcotics and
nuclear materials using neutrons
Amar Sinha
Neutron and X-ray Physics Facilities
Bhabha Atomic Research Centre,
Trombay, Mumbai
About this talk

This talk is about role of nuclear
sciences in meeting challenges of
counter terrorism

This talk is about how the nuclear
techniques which have been developed
for basic research can be adapted for
detection of explosives, narcotics or
nuclear materials

We will talk on efforts required for
developing a system from lab scale to
commercial scale

This talk will also focus on main
constraints in developing such systems
–speed, ease of operation, footprint,
cost etc
Collaborators
Mayank Shukla
 P.S. Sarkar
 Yogesh Kashyap
 Tarun Patel
 Tushar Roy
 Ashish Agrawal
 Saroj Bishnoi
 Ram Kumar Pal

Our activities at BARC

Neutrons Reactors (CIRUS) -Tomography and
Neutron Phase imaging
 Neutron Generator, D-D and D-T
 Photoneutron sources
 Isotopic sources
 Detector development
 Applications of neutrons

X-ray Imaging Beamline at Indus-II, RRCAT
 Phase imaging
 Tomography (Emission and transmission)
 Medical Imaging
Topics

Brief description of existing methods

Why neutrons?

Various Neutron based methods



Purnima neutron generator- testing of concept



TNA- FNA – PFNA- PFTNA- APINeutrons for nuclear material detection
Experiments with Purnima generator on
prompt gamma, tagged neutron,
backscattering
Plan for portable systems
What are the various steps in technology development?












(a) Mathematical modeling,
(b) Modeling of detector responses
© Spectrum analysis and deconvolution algorithm
(d) Laboratory Testing and their optimization
(e) control and data acquisition systems
(f) Assembling and testing
(g) Development of decision making algorithms
(h) Field trials
(i) method to make portable systems for smaller vehicle –truck & car
(j) method to detect dirty bomb inside cargo
(k) method for IED
( l) Indigenous effort to develop API based portable neutron source

Work at BARC

Limitations of neutron based method

Conclusion
Conventional methods
Transmission

X-ray - Generator for
passenger baggage to

Electron Linac based 9
MeV sources for cargo



Single energy
dual energy (gross low
and high density
discrimination)
Backscatter –

Gamma

3D CT
Neutron based
techniques

Why neutron based?

The key to distinguishing
explosives from benign material is
the use of elemental analysis.

X-ray Technique- insufficient
Problems with X-ray
Conventional technique -X-rays based
methods for the detection of explosive
materials are chemically blind.
They can only determine shapes and
densities of objects, leading to false
recognition of material that may be
physically similar to explosive
compounds.
A piece of Semtex plastic explosive can be
molded to look like a block of cheese or
chocolate.
Some other technologies can detect only
surface of objects or based on close
examination of vapour near objects or too
cumbersome for mass screening
Neutron based techniques

It is due to the limitations of conventional
techniques to meet such a challenge that
other more definitive technique such as
neutron based techniques are currently under
active development for detecting such
contraband materials inside vehicles, marine
and air cargo containers

They can penetrate the shielding of cargo and
to identify the composition of materials- Of
particular interest in the detection of
conventional explosives are nitrogen, oxygen,
carbon, and hydrogen

Neutron interrogation offers the possibility of
measuring the elemental density of most
elements in materials

Though not as fast as x-ray screening – but
due to their capability to identify the chemical
composition lead to lower false alarm rate

They are being developed as second line of
confirmatory sensor
Nuclear Physics behind the technique

The physical basis of these techniques is
well known to nuclear physicist.

What has changed is adoption of such
concepts in terms of reconfiguration of
neutron sources and detector and
methodology for the purpose of explosive
detection
Physical basis of detection
(n, n’)
(n,)
Emitted gammas are Finger print of element
Elemental composition of common substances
narcotics, explosives, and chemical weapons
Substance
Density
(g/cm3)
%H
%C
%N
%O
%C
l
% Other
elements
C/
O
N/
O
Cl/
C
Cl/
H
Benigns
Salt
0.77
0
0
0
0
60
40
0
0
0
0
Sugar
1.2
7
42
0
51
0
0
0.8
0
0
0
Sand
2.3
0
0
0
53
0
47
0
0
0
0
Water
1
11
0
0
89
0
0
0
0
0
0
Wood
0.62
6
47
0
44
0
3
1.1
0
0
0
Petroleum
0.87
14
86
0
0
0
0
0
0
0
0
Cement
2.3
0
0
0
35
0
65
0
0
0
0
PVC
1.32
5
38
0
0
57
0
0
0
1.5
11.5
Polyethylene
0.94
14
86
0
0
0
0
0
0
0
0
Fiberglass
1.7
3
46
0
35
0
16
3
1.3
0
0
Sea water
1.02
10
0
0
88
1.2
0.8
0
0
0
0.03
PETN
1.76
2.4
19
17.7
60.8
0
0
0.3
0.3
0
0
TNT
1.63
2.2
37
18.5
42.3
0
0
0.9
0.4
0
0
Dynamite
1.18
4.2
14.8
18.5
62.4
0
0
0.2
0.3
0
0
C4
1.65
3.6
21.9
34.4
40.1
0
0
0.6
0.9
0
0
Heroin
hydrochloride
0.87
6
62.1
3.5
19.7
8.7
0
3.2
0.2
0.1
1.5
Cocaine
hydrochloride
0.87
6.5
60.1
4.1
18.8
10.4
0
3.2
0.2
0.2
1.6
Heroin
0.87
6.3
68.2
3.8
21.7
0
0
3.2
0.2
0
0
Cocaine
0.87
6.9
67.3
4.6
21.1
0
0
3.2
0.2
0
0
Explosives
Narcotics
Substance
Density (g/cm3)
%
H
%C
%N
%O
%Cl
% Other elements
C/O
N/O
Cl/C
Cl/H
Chemical_weapons
Hydrogen cyanide
3.7
44.5
51.
8
0
0
0
0
0
0
0
Mustard gas
5
30.2
0
0
44.6
20.2
0
0
1.5
8.9
Sarin
7.1
34.3
0
22.9
0
35.7
1.5
0
0
0
Characteristic gamma
Signature
The technique one chooses is
dependent on what you want to
detect
Incident Neutron energy is important
for some inelastic reaction
Different detection schemes have been
Worked out –
(a) based on only capture
(b) use Inelastic or both
© use imaging to spatially localize the signal
(d)other use time of flight
Which neutron
technique
TNA
 FNA
 PFTNA
 NRA
 ……….
 PFNA
 API
 ……….

We focus on a few Methods

(a) Thermal Neutron Analysis (TNA):
Basic principle of TNA
TNA spectrum for Bag with and
without small explosive
Isotopic source – 252Cf or even Am-Be
In fact this technique using 252Cf has been
used extensively for interrogating parcels
Limitations –mostly qualitative–small parcels –
where other background is minimal
(b)
The main signatures used are derived from
detecting the
- 4.43 MeV γ-ray from 12C
-1.64, 2.31 and 5.11 MeV γ-rays from 14N
-6.130 MeV γ-ray from 16O
© Pulsed Fast-Thermal
Neutron Analysis (PFTNA)
Being used for vehicle borne explosive detection
UXO characterization
landmine detection
(d)
ELECTRON LINAC BASED NEUTRON SOURCE
electron-photon- neutron
n

e
Tantalum
Be
high energy electrons to produce photons
- Photons then produce neutrons through photo-neutron
reaction-
We have helped Mangalore university design
such a source based on microtron
(e)
Combined Neutron and
Gamma-Ray Interrogation
Ratio of neutron attenuation to gamma
attenuation
Ratio of neutron to gamma attenuation
Device based on this concept is operational
At Brisbane airport for air cargo scanning
(f)
NEUTRON RESONANCE
RADIOGRAPHY

Uses energy
selective radiography
unlike the previous
technique which uses
white neutron source
and requires a
variable energy
neutron source to
extract information.

specific mapping of
elements based on
their resonance
properties of their
total interaction crosssection
Variable energy is produced using
d(d,n)3He reaction and energy selection is
made by varying production angle
Imaging Techniques?

The ability to measure precisely elemental
concentrations in an inspected object is necessary but
not sufficient condition for a successful inspection
system.

Simple detection of nuclear signature is not enough if the
object being inspected has large volume. For large object
the information from contraband may be smeared due to
signal from surrounding constituents of the cargo

If somehow the measurement can be localized inside the
volume of cargo, the determined elemental densities will
represent the material composition at that very volume
element (voxel) and not an average over a larger volume.

Improved S/N ratio
Two schemes –PFNA and API
(g) Pulsed Fast Neutron analysis (PFNA)

PFNA –use of
pulsed
nanosec beam
directional
monoenergetic
beam
Producing pulsed
Nanosec beam
Directional beam
-requires large
Accelerator
-expensive
(h)
Tagged Neutron
(Associated particle Imaging)
• It can provide 3D information about any volume by detecting
gamma in coincidence with alpha in the DT reaction
• It can be used to detect explosives, narcotics etc in cargo
• It can be used to detect SNM in CARGO by detecting the
fission gamma induced by burst of external neutron
• It can be used to detect SNM by use of
correlation/coincidence techniques
This method has been extensively tested at a
Port in Europe under a project named
“EURITRAC”
EURITRACK –consotorium of
16 European Agencies

Explosive detection
technique using neutrons
We feel API method also called tagged Neutron Method
has potential to be used in large cargo/container scanning
which is of interest to us.
We are coordinating with several agencies in evaluation
of such system and for this reason we are evaluating
several technologies including API system
Fissile material
Detection
Passive – coincidence -gamma
 Active interrogation- A variety
of signature


Neutron in- fission neutron out
and delayed – both carry
signature
 Prompt

Neutron in – fission gamma out

Differential Die away

Tagged neutron coincidence
Residual fissile material in waste stream
Differential Die Away
This technique is also used in Hull Monitoring
In reprocessing plant to monitor plutonium
Dirty Bomb
Directional fast neutron Imaging
for special Nuclear material (SNM)
Delft University of Technology -
harbor of Rotterdam
The background flux below 10 MeV to be ≈0.01 n/s.cm2 . One kilogram
of weapon grade plutonium (WGP) emits 6.104 n/s following a Watt
energy spectrum . Simple algebra shows neutron flux from the
plutonium becomes over shadowed by the background beyond a
distance of about 7 m. Standard scanning methods will not be able to
detect such an amount of WGP in a sea container since 7 m is of the
order of the dimension of the container.
Substantial reduction of the background will
be possible by using a fast neutron detector
with imaging properties. The background rate
within an opening angle corresponding to an
angular resolution of 10o for example is
reduced by a factor:
under the assumption of isotropy of the
background. With such a direction sensitive
detector the WGP can be detected above the
natural background up to a distance of about
70 m.


4

1
2
8
2
t
a
n
1
0

Fast neutrons lose energy when penetrating hydrocarbon scintillator materials by interactions with protons
and carbon nuclei. The recoil proton energy is released
as scintillator light and the collision kinematics uniquely
defines the scattering angle of the neutron. The proton
track itself is too short to be observed. When the
scattered neutron experiences a second collision with a
proton inside the scintillator the direction of the original
incoming track can be determined see figure 1
Directional fast neutron Imaging
for special Nuclear material (SNM)


Two successive n-p elastic
scattering
Determine:





 n
interaction positions
energy scattered neutron En’
direction scattered neutron
energy of the first recoil proton
p1
p
En  E p11 En'
n'
p2
Determine the incident neutron
energy
E
p
s
i
n


E

E

E
n
p
n
'
E
n
2



Calculate scatter angle 
Construct cone
Common direction on several
cones points to the source
Double elastic n-p
scattering showing the
basic kinematics of event
reconstruction. If the full
neutron energy is
measured, the incident
neutron direction is
restricted to the mantle of a
cone and an “event circle”
can be drawn
: Schematic of the source-imaging fast-neutron
detector. Reactions of two incoming neutrons are
shown (tracks in green and blue). The small arrows
show recoiling protons (in red). For simplicity only one
light sensor (PMT) is indicated.
Working on Various steps in technology
development?











(a) Simulation -optimize parameter
(b) Laboratory Testing and their
optimization
(c) Modeling of detector responses
(d) Spectrum analysis and deconvolution
algorithm
(e) control and data acquisition systems
(f) Assembling and testing
(g) Development of decision making
algorithms _neural network, Fuzzy Logic
(h) Field trials
(i) method to make portable systems for
smaller vehicle –truck & car
(j) method to detect nuclear material in cargo
( k) Indigenous effort to develop portable
neutron source
Neutron Generator at Purnima, Ion
BARC
Source
Faraday
Cup
Tritium
Target
Dome
Beam
Steerer
400 kV DC
Power Supply
BPM
Accelera
ting
Column
Farad
Tritiu ay
m
Cup
Target
F
Beam
Steer
BPMer
Ion source
Dome High
Accelerat
Ting Tube
M
P
Voltage
Power
Supply
Turbo
Molecul
ar
Pump
Photograph of the Purnima neutron generator
•Cockcroft-Walton voltage multiplier
Schematic of the Purnima Neutron Generator
Basic facility for testing before field application
Status

This generator is running in
both D-D and D-T mode

Safety committee has
permitted us to operate it at
107 n/s in D-T and 3x 107 n/s in
D-D mode

However shortly we are going
to take a trial run in D-T mode
upto 1010 n/s
Experiments on PGNA
Spectrum of Urea showing H and N capture lines
-Top curve with urea
-bottom without urea
Graph of the Signal and background data in terms of channel
versus counts. The Hydrogen peak at 2.22 MeV and the nitrogen
photopeak at 10.829MeV are very clearly visible. Nitrogen single
escape peak is also distinguishable. The data collection time was
1800 seconds. Urea (CO(NH2)2) : Molecular weight: 60.06 gm,
Density: 1.33gm /cc: Composition: H—6.71%, C – 20%, N –
46.65% and O – 26.64%
Sample: Salt (NaCl)

The main aim to carry out the detection chlorine (Cl)
capture lines in salt is due to fact that chlorine based
compounds form part of narcotics. Since Cl has more
neutron capture cross-section (43b) than Na the
capture gammas of Cl are much more detectable than
Na. In a data collection time of 1200 seconds we
could detect 4 Chlorine photo-peaks and one of their
escape peaks.
Left graph shows the Chlorine peaks (labeled
in MeV energy): Cl-6.619MeV and Cl – 6.11
MeV along with its single escape peak Cl’ –
5.599MeV and double escape peak Cl’’ –
5.08MeV. The right hand side graph shows the
other Cl lines, 1.16MeV and 1.95MeV.
Prompt inelastic gamma
D-T neutron
Graphite (6-8kg)sample was irradiated
for the detection of theprompt gamma
4.439MeV from carbon element.
We have observed the 4.439 as well as
its first escape peak
Aquisition Time=20 min
...Background
...Graphite
5
10
Counts
C(3928-SE) C-4439
4
10
100
200
300
400
Channel Number
Similarly experiments with urea and water for nitrogen and
oxygen detection have been done.
Developing Tagged Neutron
(Associated particle Imaging)
API method diagram
In the d + t
reaction a neutron with energy of 14 MeV and an
alpha particle with energy of 3.5 MeV are emitted “back-to-back”
DT (En=14 МeV)
Eα = 3.5 MeV
Time-of-flight
for
14 МeV neutron:
1 ns => 5.2 cm
Ability for 3Dimaging: elemental
analysis +
direction and
depth
Sufficient
improvement
for ratio
effect/background
Experiments on
developing neutron
tagging method

D+T – n+

It is a challenge to discriminate

D+D – n+He-3

D+D –t+p
Experiments on tagging in collaboration with
Italian Researchers


Simulated experiment on illicit material detection using tagged
neutron technique
Fig. 4 Gamma spectrum and time domain counting for tagged neutron analysis
Detectors

We are conducting
experiments with NaI (3”, 5”).
BGO, LaBr to optimize the
detector configuration for a
workable detection system for
cargo, vehicle.

We are also developing
suitable electronics and data
acquisition system for this
work.
Development of simulation tools
Simulation Model
50 X 50 X50 cm3
VARYING DENSITY OF ORGANIC / METALLIC MATRIX
Cargo 250 (W), 250 (H), 100 (L)
TOP DETECTOR RESPONSE AS A
FUNCTION OF TIME
Tagging Interval
signal to noise ratio increases in 30-50ns
time interval indicating presence of an
anomaly
FRONT DETCTOR
RESPONSE AS A
FUNCTION OF TIME
Tagging interval
Case study
Varying explosive quantity
 Varying explosive location
 Varying density of embedded
matrix
 Different types of material such
as Nylon, Cocaine etc

200kg explosive in
0.2gm/cc
N14
C12
sum of counts of all top detector
in 27-45ns
N14
O16
Front Detector
C12
O16
50kg explosive in
0.2gm/cc
25kg explosive in
0.2gm/cc matrix
200kg in 0.5gm/cc
matrix
50Kg in 0.5gm/cc
matrix
25 kg explosive in
0.5gm/cc matrix located
near to top detectors
Location of detectors with
respect to explosive plays a
important role.
 Double sided scanning may
help to improve the possibility
of detection of explosives

Cocaine in a organic
matrix of 0.5gm/cc
Organic matrix has self
background which may be
sufficient to shield these
materials if put in high density
matrix
 Need additional tool or
information to distinguish these
from organic materials


Detection of explosive with
Tagged Neutron method will be
dependent of several factors
 Quantity
of explosive
 Matrix density
 Type of matrix
 Location of explosive in the cargo
 Nature of surrounding matrix
 Nature of background etc
Study of neutron
backscattering method
for landmine detection
What are its potentials and limitations
What kind of system will work in specific condition
Such studies have been carried out by other
researchers for specific experimental system
and different source and experimental condition
Simulation geometry
Neutron
detector+
shielding
(2.5x2.5x15
cm3)
Standoff
distance
(2cm)
TNT
(C7H5N3O6)
Soil
DD/DT
neutron
source
Mine
depth
(5cm 20cm)
PMA2-mine at the
depth 5cm
Simulation for SNM
Polythene
graphite
Schematic of SNM monitoring device
Plot of reaction rates as a function of Time with and
without fissile material (A drum containing 0.5% of
fissile material in 13.3 kg of actinide content)
Further data analysis consists in
decomposition of energy spectra of γ-rays
collected for every “voxel” of the inspected
volume, into contributions from various
chemical elements.
Response function of individual elements
Multivariate calibration
• Often want to estimate a property based on a multivariate
response
• Typical cases
• Estimate analytic concentrations (y) from spectra (X)
• Finding Elemental composition (y) from fluorescence
spectrum (X)
• Want solution of form Xb = y + e
• Problem: how to estimate b?
Partial least Square
regression
PLS is related to PCR ( Principle component Regresion) and
MLR (Multi Linear Regression)
PCR captures maximum variance in X
MLR achieves maximum correlation between X and Y
PLS tries to do both by maximizing covariance between X
and Y






X is a matrix containing spectrum of several
samples with known compositions
Y is the matrix of concentrations of various
elements present in the modeled samples then
their relation can be written
Let Y = XB + F (Where F is the matrix of
residual) (1)
The PLSR model can be considered as consisting
of three relations
X = TP’ + E, Y = UQ’ + F, and U = BT
Where P,Q are loading matrixes of X,Y. T,U are
score matrix of X,Y and E,F are matrix of
residuals. B is matrix relating X block scores to Y
block scores. When all the scores are calculated
the concentration of unknown sample can be
obtained from the following relation
Y = BTQ’ + F
Calibration and crossvalidation
Sample
( wt % )H
( wt % ) C
( wt % ) N
( wt % ) O
S1
5
25
30
40
S2
6
18
35
41
S3
5
20
28
47
S4
8
28
20
44
S5
2
30
18
50
S6
3
25
22
50
S7
4
18
25
53
S8
6
21
30
43
S9
4
15
24
57
S10
3
23
33
41
Application of PLS technique in
quantitative determination of explosive
elements
S7
S8
S9
S10
4
6
4
3
Predicted
3.99
5.992
4.47
2.61
Actual
18
21
15
23
Predicted
17.49
20.90
14.28
23.08
Actual
25
30
24
23
Predicted
25.75
30.16
25.09
32.50
53
43
57
41
52.53
43.46
55.99
41.51
H Actual
C
N
O Actual
Predicted
Artificial Neural
Network
(ANN) for Explosive
Detection
Neural network
architecture
Neuron
Model
Transfer
functions
ANN model for
explosive detection





Feed-forward network with backpropagation
algorithm
Two stage network
10 element vector input (C, H, N, O, Cl, C/N,
C/O, N/O, Cl/C, Cl/H)
29 patterns (explosives/narcotics)
35 neurons in the hidden layer
Tan-sigmoid transfer
function
Tan-sigmoid transfer
function
Feed-Forward
Network
Training data
Input
Vector
Element
Paramet
er
1
C
2
H
3
N
4
O
5
Cl
6
C/O
7
C/N
8
N/O
9
Cl/C
10
Cl/H
Training Performance
Recall test values
Input: Original input values used in training
Simulated Input for:
RDX: [16.22 2.72 37.84 43.22 0 0.42865 0.87552
0.37529 0 0 ]
Cocaine: [67.3 6.9 4.6 21.1 0 14.63 0.2 3.2 0 0 ]
Recall test values with
5% error
Input: 5% random error added to original input
values used in training
Simulated Input for:
RDX: [15.855 2.6772 37.75 44.995 0 0.44322
0.91611 0.37401 0 0 ]
Cocaine: [70.514 6.8679 4.5525 21.77 0 15.223
0.19993 3.12 0 0 ]
Limitations

The method is slower
compared to X-ray (seconds vs
minutes)

Can be used as confirmatory
sensor

Still much work remains to be
done to make it commercial
Conclusions

We have reviewed various methods
of explosive detection

The necessary steps in developing
such systems have been highlighted
We have described our work at
BARC for this development
We have brought out
multidisciplinary nature of this work



We have also pointed out the
limitations of the technique