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Journal of Science and Technology in the Tropics (2010) 6: 59-65
Prompt gamma neutron activation analysis (PGNAA) of hydrocarbons:
A Monte Carlo study with GEANT4
Lam YiHua1 , Wong Chiow San1 * and Kurunathan Ratnavelu2 1Plasma Research Laboratory, Department of Physics, Faculty of Science, University of Malaya,
50603 Kuala Lumpur, Malaysia
2Institute of Mathematical Sciences, University of Malaya, 50603 Kuala Lumpur, Malaysia
*Corresponding author
Abstract In the present work, the results of prompt gamma (γ) neutron activation analysis (PGNAA)
calculated by the open source GEANT4 Monte Carlo toolkit were compared with the commercial simulation
package MCNP. Both the Monte Carlo simulation packages utilize the phenomenological nuclear reactions
to yield γ rays which are coupled with incident neutrons after these reactions. A virtual experimental setup
with a 4π solid-angle γ detection was instantiated in the simulations to collect all prompt γ rays from the
tested hydrocarbon phantoms. The comparative results present good agreement in getting the characteristic
γ energy spectra of hydrocarbon materials.
Keywords GEANT4 – MCNP – Monte Carlo simulations – prompt gamma neutron activation
INTRODUCTION
A material with its specific chemical composition and
density can be detected or differentiated from among
other types of materials, which have nearly the same
chemical composition but have not complied with the
same densities, by using prompt gamma (γ) neutron
activation analysis (PGNAA) method. It has been
used in detecting explosive hydrocarbon material [1].
In addition, certain element in a bulk material or in a
biological tissue can be determined via PGNAA, e.g.
biomedical protein detection [2].
PGNAA method relies on neutron-nuclear
interactions, that is, inelastic scattering (n, n′γ), (n, pγ)
and radiative capture (n,γ), to yield γ rays. Although
1/v law [3] (v is the incident neutron velocity) is not
applicable to every element, isotope and energy range
[4], it is still acceptable to be applied in low Z element
and in thermal energy range [5]. This law infers that
the probability of neutron radiative capture depends
on how long the period of time a neutron spends in
the region surrounding the nucleus. The longer period
of time it spends, the higher probability of neutron
radiative capture will occur. Hence, when a low
kinetic energy incident neutron, e.g. thermal neutron
(~0.025eV) or epithermal neutron (0.1-1eV), enters the
narrow separation virtual energy levels in compound
nucleus or interacts with compound nucleus [6], the
neutron radiative capture cross sections will increase.
These low energy interactions raise the possibility of
producing stable isotopes and the coupled γ ray, e.g.
1 H(n, γ) 2 H in which 2 H is a stable isotope and γ ray will
be radiated. Besides, different materials composed by
different chemical compositions (including different
isotopes) and densities will have different radiative
capture cross sections. By radiating low energy
neutrons with certain range of energy distribution on
different materials, the produced γ ray energy spectra
will be different. Hence, the prompt γ ray energy
spectra become an identifying characteristic of the
material.
Other than experimental measurements, PGNAA
can be simulated by using various types of Monte
Carlo computational simulation packages, such as
GEANT4 [7,8], MCNP [9] and FLUKA [10,11].
Most of these packages are written in structural
programming language (C and FORTRAN). GEANT
4 has been written in object-oriented programming
(OOP) architecture (C++), developed and maintained
by many laboratories [7,8]. Conceptually, OOP has
its distinctive feature in treating particle as a single
object which may have encapsulated its own data
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