Identification of simulants for explosives using pixellated X-ray diffraction
© O’Flynn et al.; licensee Springer. 2013
Received: 11 February 2013
Accepted: 30 June 2013
Published: 6 July 2013
A new method of material identification has been developed utilising pixellated X-ray diffraction (PixD) to probe the molecular structure of hidden items. Since each material has a unique structure, this technique can be used to “fingerprint” items and has significant potential for use in security applications such as airport baggage scanning. The pixellated diffraction technique allows two distinct forms of diffraction, angular-dispersive and energy-dispersive X-ray diffraction, to be combined, exploiting the benefits of both. Thus, fast acquisition times are possible with a small system which contains no moving parts and can be easily implemented. In this work, the capability of the system to identify specific materials within a sample is highlighted. Such an approach would be highly beneficial for detecting explosive materials which are concealed amongst or inside other masking items. The technology could easily be added to existing baggage scanning equipment and would mean that if a suspicious item is seen in a regular X-ray image, the operator of the equipment could analyse the object in detail without opening the bag. The net result would be more accurate analysis of baggage content and faster throughput, as manual searching of suspicious objects would not be required.
where λ is the X-ray wavelength, d is the inter-atomic distance in the material and θ is the angle through which the incident X-rays are scattered. There are two different methods which can be implemented in order to measure XRD. In angular-dispersive XRD (ADXRD), the X-ray source and detector are rotated with respect to the sample surface, and a narrow window of incident X-ray energies is selected (λ is approximately constant). The different d values present within the material produce high intensity diffraction peaks at the incident X-ray angles which satisfy Bragg’s law for the selected value of λ. ADXRD can also be performed with a pixellated detector array, such that monoenergetic photons are collected over a range of angles simulateneously. An alternative method is to keep the scattering angle fixed, and use a polychromatic X-ray beam (a wide range of λ) - this approach is called energy-dispersive XRD (EDXRD). ADXRD can give a very high angular resolution, but the standard approach of rotating the X-ray source and detector about the sample is impractical for most security-based scenarios. EDXRD uses a fixed experimental setup, but requires a strict collimation of the incident and scattered X-ray beams in order to have a well defined θ. This collimation leads to a large drop in the detected X-ray flux, and thus long counting times are required.
A novel technique has been developed in which features of both ADXRD and EDXRD are simultaneously combined (Christodoulou et al. 2011; O’Flynn et al. 2012; O’Flynn et al. 2013). This is achieved by using a pixellated detector which is bonded to a CdTe crystal. The active detector area is 20 ×20 mm, and is composed of 80 ×80, 250 μ m pitch pixels. The CdTe enables the energy of incident X-ray photons to be observed, such that each pixel generates an individual energy spectrum for an acquisition (Jones et al. 2009; Seller 2011). The pixel array gives spatial resolution to the system, and is utilised for measuring angular-dispersive diffraction.
In this work, we present pixellated XRD (PixD) data from simulants for explosives provided by the Home Office Centre for Applied Science and Technology (CAST), UK. The simulants were designed to look similar to a particular plastic explosive when examined using passive millimeter-wave imaging. The results presented demonstrate the ability of pixellated XRD to identify a sample based on the molecular structure of its constituent materials, and therefore the potential to search for specific compounds/substances amongst other masking materials.
where E is the incident X-ray energy (elastic scattering is assumed). The momentum transfer values at which diffraction peaks are measured give us information on the atomic structure of the material under observation. Since values of x for a material are absolute, i.e. they are position and energy invariant, it is possible to sum the momentum transfer plots from all pixels to give an overall spectrum for an acquisition without a loss of information. The resolution of this spectrum is determined by the 250 μ m pixel size, and its counting statistics are governed by the overall detector size. This data processing method therefore enables greater detection efficiency whilst maintaining resolution, and vastly reduces the amount of data to be examined.
Results and discussion
The X-ray diffraction data presented for the three simulant samples demonstrate the ability of XRD to identify the different materials present in a sample based on their individual molecular structures, and therefore the possibility of implementation in a system which can search for specific materials hidden inside packages or baggage. Examples of such materials are the high energy compounds RDX and PETN which are found in many plastic explosives; if the diffraction patterns for these substances are known, they can be compared with the data obtained from unknown items to provide a “red light/green light” system. This approach also applies to any potentially dangerous substances, such as ammonium nitrate. Principal component analysis (PCA) is a data processing technique which groups similar datasets together, and has been previously used to accomplish an explosives identification system for PixD. Although diffraction data are noisier with short acquisition times (due to less X-rays being measured by the detector), PCA has demonstrated accurate material identification for measurements acquired in one second (O’Flynn 2013). With a large library of XRD datasets from explosive and inert materials, PCA enables diffraction patterns of unknown samples to be classified based on their similarity to previously measured data.
A challenge for the pixellated diffraction system is to be able to identify materials in thick samples, as described in the ‘Methods’ section and demonstrated in ‘Results and discussion’ section. This issue could be overcome with the use of secondary collimators (positioned between the sample and detector) to more accurately select the scattering angles of photons which reach the detector. One drawback of this approach is the potentially large reduction of photon flux due to the extra collimation, which would lead to longer counting times. Another possible solution is to produce a simulated spectrum for each suspicious material based on the sample thickness, such that more direct comparisons with data from an unknown item can be made. This method would require the thickness of the object under observation to be defined. Attenuation of the incident and scattered X-ray beams due to other materials in front of/behind the object under study would also be a factor to consider in the production of a diffraction based scanning system. Increasing the incident beam peak energy would give greater penetration through the sample, but would have knock-on effects on the resultant diffraction pattern. Further research is required in order to optimise a system for specific material identification in more realistic baggage scenarios.
In conclusion, the pixellated X-ray diffraction technique enables simultaneous measurement of angular and energy dispersive XRD, and utilises the benefits of both methods. The experimental setup is useful for practical situations, since it is compact and contains no moving parts. The pixellated detector enables the counting statistics of a 20 ×20 mm2 detector with the angular resolution afforded by the 250 μ m pixel pitch. It is envisaged that pixellated diffraction would be used alongside conventional baggage imaging methods; due to the small beam size used for diffraction, it would be more efficient to scan suspicious regions within a bag which were initially identified with an image. Radiation protection required for the diffraction setup would be similar to that used for present airport-based scanners.
This project was funded under the Innovative Research Call in Explosives and Weapons Detection (2010) initiative, a cross-government programme sponsored by a number of departments and agencies under the U.K. Government’s CONTEST strategy, in partnership with US Department of Homeland Security.
- Cook E, Fong R, Horrocks J, Wilkinson D, Speller R: Energy dispersive X-ray diffraction as a means to identify illicit materials: A preliminary optimisation study. Applied Radiation and Isotopes 2007, 65(8):959. 10.1016/j.apradiso.2007.02.010View ArticleGoogle Scholar
- Cook E, Pani S, George L, Hardwick S, Horrocks J, Speller R: Multivariate data analysis for drug identification using energy-dispersive X-ray diffraction. IEEE Transactions on Nuclear Science 2009, 56(3):1459.View ArticleGoogle Scholar
- Christodoulou C, Reid CB, O’Flynn D, Wilson M, Veale M, Cernik RJ, Seller P, Speller RD: Multivariate analysis of pixelated diffraction data. Journal of Instrumentation 2011, 6(12):C12027. 10.1088/1748-0221/6/12/C12027View ArticleGoogle Scholar
- Farquharson M, Luggar R, Speller R: Multivariate calibration for quantitative analysis of EDXRD spectra from a bone phantom. Applied Radiation and Isotopes 1997, 48(8):1075. 10.1016/S0969-8043(96)00328-4View ArticleGoogle Scholar
- Jones L, Seller P, Wilson M, Hardie A: HEXITEC ASIC - a pixellated readout chip for CZT detectors. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 2009, 604(1–2):34. 10.1016/j.nima.2009.01.046View ArticleGoogle Scholar
- Kämpfe B, Luczak F, Michel B: Energy dispersive X-ray diffraction. Particle & Particle Systems Characterization 2005, 22(6):391. 10.1002/ppsc.200501007View ArticleGoogle Scholar
- Luggar RD, Farquharson MJ, Horrocks JA, Lacey RJ: Multivariate analysis of statistically poor EDXRD spectra for the detection of concealed explosives. X-Ray Spectrometry 1998, 27(2):87. 10.1002/(SICI)1097-4539(199803/04)27:2<87::AID-XRS256>3.0.CO;2-0View ArticleGoogle Scholar
- Malden CH, Speller RD: A CdZnTe array for the detection of explosives in baggage by energy-dispersive X-ray diffraction signatures at multiple scatter angles. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 2000, 449(1–2):408. 10.1016/S0168-9002(99)01418-7View ArticleGoogle Scholar
- O’Flynn D, Reid C, Christodoulou C, Wilson M, Veale MC, Seller P, Speller R: Pixelated diffraction signatures for explosive detection. Proc. SPIE 2012, 8357: 83570X.View ArticleGoogle Scholar
- O’Flynn D, Reid C, Christodoulou C, Wilson M, Veale M, Seller P, Hills D, Desai H, Wong B, Speller R: Explosive detection using pixellated X-ray diffraction (PixD). Journal of Instrumentation 2013, 8: P03007. 10.1088/1748-0221/8/03/P03007Google Scholar
- Phadnis NV, Cavatur RK, Suryanarayanan R: Identification of drugs in pharmaceutical dosage forms by X-ray powder diffractometry. Journal of Pharmaceutical and Biomedical Analysis 1997, 15(7):929. 10.1016/S0731-7085(96)01939-5View ArticleGoogle Scholar
- Seller P, Bell S, Cernik RJ, Christodoulou C, Egan CK, Gaskin JA, Jacques S, Pani S, Ramsey BD, Reid C, Sellin PJ, Scuffham JW, Speller RD, Wilson MD, Veale MC: Pixellated Cd(Zn)Te high-energy X-ray instrument. Journal of Instrumentation 2011, 6(12):C12009. 10.1088/1748-0221/6/12/C12009View ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.