A Proof-Of-Principle Investigation for a Neutron-Gamma Discrimination Technique in a Semiconductor Neutron Detector

A Proof-of-Principle Investigation for a Neutron-Gamma Discrimination Technique in a Semiconductor Neutron Detector

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University

Praneeth Kandlakunta, B.E. (Hons.)

Graduate Program in Nuclear Engineering

The Ohio State University

2012

Thesis Committee:

Dr. Lei Cao, Advisor

Dr. Don Miller

Praneeth Kandlakunta

2012

Abstract

Gadolinium (Gd) is an efficient thermal neutron conversion material due to the superior thermal neutron absorption cross-section predominantly composed of 157Gd, which is also 15.65% abundant in natural Gd. A thermal neutron capture by 157Gd results in an excited 158Gd nucleus. The de-excitation of 158Gd* involves the emission of prompt gamma rays with competing internal conversion (IC) electrons. Following the expulsion of conversion electrons from the atomic shells of 158Gd, the excitation energy of the atom is released through the emission of Auger electrons and characteristic x-rays. The low energy conversion electrons and Auger electrons are considered the principal component of neutron-induced signal in a Gd-based thin film semiconductor. Besides possessing a high thermal neutron absorption cross-section, Gd also has a good interaction probability for high/medium energy gamma rays, owing to its high Z (64) number. A Gd atom activated by an external high energy gamma ray leads to the emission of characteristic x- rays that come primarily from the K-shell. These x-rays have a fairly low energy (43.0 keV, 42.3 keV for Kα1, Kα2 respectively) compared to those of the prompt gamma rays that are emitted following a neutron capture.

Thin film semiconductors, although transparent to high energy gamma rays, are comparatively sensitive to low energy gamma rays and x-rays. Hence, it is supposed that a thin film semiconductor neutron detector using Gd as a neutron convertor receives

ii greater interference from low energy x-rays that are emitted following gamma ray activation in Gd, than that from high energy background gamma rays. Thus, due to the presence of an inherent gamma ray background, separation of the neutron-induced signal from a gamma/x-ray induced signal is central to a semiconductor neutron detector employing Gd as the conversion material. A method of separation of these two signals by means of a current subtraction technique has been proposed. This gamma ray rejection scheme presents two identical semiconductor detectors separated by a thin Gd foil and a polyethylene thin layer. In the presence of a mixed neutron and gamma ray environment, a subtraction of signals resulting from these two detectors generates a ‘neutron only’ induced signal.

Nevertheless, an experimental validation will reinforce the abovementioned supposition and provide substantiation of the same. The objective of this research is thus to validate the principle proposed for gamma ray rejection in a thin film semiconductor neutron detector based on Gd. As the first stage, an experimental setup was designed and constructed to perform the required radiation measurements. In the second phase, preliminary measurements were performed to calibrate the instrumentation system and to gain expertise on using the signal processing electronics. In the final phase, a mixed beta- gamma measurement using two silicon detectors was performed in order to simulate a neutron-gamma discrimination scenario in a Gd based semiconductor detector. The output energy spectra encompassed a mixed beta-gamma spectrum from an unshielded silicon detector and a gamma ray only spectrum from a shielded silicon detector.

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Subtraction of the two spectra generated a beta-only spectrum representing a detector’s response to the IC and Auger electrons from Gd.

Acknowledgments

I sincerely thank my research advisor, Dr. Lei Cao, for having given me the opportunity to work on this research endeavor. I’d also like to thank Dr. Cao for his guidance, support and constant encouragement, without which the investigation wouldn’t have been complete.

I’m thankful to my research colleague James Ralston for sharing his inputs with me and for the several discussions we had on the subject matter.

I would like to express my gratitude to my fellow graduate students Danyal

Turkoglu, Padhraic Mulligan and Jinghui Wang for their assistance and support.

I’m also very thankful to the technical support team from CAEN SpA, for their periodic feedback, support and guidance in using the digital data processing module and the pulse processing software.

Vita

December 2008………………....B.E.(Hons.), Birla Institute of Technology and Science (BITS) – Pilani, India. September 2010 to present……. Graduate Research Associate, Nuclear Engineering

Graduate Program, Department of Mechanical and

Aerospace Engineering, The Ohio State University.

Publications

1. Praneeth Kandlakunta, Lei Cao. "A Neutron Detector with Gamma Discrimination." In: Transactions of the American Nuclear Society. Vol. 105. Washington, D.C., USA. (2011): 335-336.

2. Padhraic L. Mulligan, Danyal J. Turkoglu, Praneeth Kandlakunta, Lei Cao. "Improving Neutron Depth Profiling at The Ohio State University Using Multiple Detectors." In: Transactions of American Nuclear Society. Vol. 104. Hollywood, FL, USA. (June 2011): 227-229.

3. Jinghui Wang, Praneeth Kandlakunta, Thomas F. Kent, John Carlin, Daniel R. Hoy, Roberto C.Myers, Lei Cao. "A Gadolinium Doped Superlattice GaN Schottky Diode for Neutron Detection." In: The Transaction of America Nuclear Society. Vol. 104. Hollywood, FL, USA. (June 2011): 207-209.

4. D. Turkoglua, J. Straha, P. Kandlakuntab, L. Cao. "Development of an External Neutron Beam Facility at The Ohio State University." In: The Transaction of America Nuclear Society. Vol. 102. Las Vegas, NV, U.S.A.

5. Praneeth Kandlakunta, Lei Cao*. "GAMMA RAY REJECTION, OR DETECTION, WITH GADOLINIUMAS A CONVERTER." Radiation Protection Dosimetry. (February 2012) (IF: 0.966) (Formally Accepted).

Fields of Study

Major Field: Nuclear Engineering

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Table of Contents

Abstract ...... ii Acknowledgments...... v Vita ...... vi Table of Contents ...... viii List of Tables ...... x List of Figures ...... xi 1. Introduction ...... 1 2. Background ...... 3 2.1 Neutron Detectors ...... 3 2.2 Solid-state neutron detectors ...... 5 2.3 Neutron converter materials ...... 6 2.4 Interaction of neutrons with gadolinium ...... 10 2.4.1 Intrinsic thermal neutron detection efficiency of a thin Gd foil ...... 16 2.5 Interaction of gamma rays with gadolinium ...... 18 2.6 Gamma ray discrimination techniques in neutron detectors ...... 20 2.6.1 A literature review of some gamma ray discrimination techniques ...... 21 2.6.2 Proposed gamma ray discrimination scheme ...... 25 2.7 Theory of radiation measurement systems and digital pulse processing (DPP) techniques ...... 26 2.7.1 A review of DAQ systems used in radiation measurement ...... 27 2.7.2 Trapezoidal energy filter ...... 32 2.7.3 Operation of a digitizer built by CAEN SpA ...... 34 2.7.4 Digital treatment of the signal – advantages and disadvantages ...... 36 3. Experimental approach ...... 38 3.1 Objective and the Experiment ...... 38 3.2 Radioactive sources for a ‘proof of principle investigation’ ...... 38

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3.3 Instrumentation system for the measurements ...... 40 3.3.1 In-house Al vacuum chamber ...... 41 3.3.2 DAQ System ...... 44 3.3.3 Different acquisition modes with the digitizer...... 47 4. Experimental setup and instrument calibration ...... 50 4.1 β-particle measurements ...... 55 4.2 γ-ray measurements ...... 57 4.3 Mixed β-γ measurement ...... 60 Conclusion and Future Work ...... 64 References ...... 67 APPENDIX A: MCNP5 input – Gadolinium prompt-gamma rays ...... 70 APPENDIX B: MCNP5 input - Gadolinium K-X rays ...... 73 APPENDIX C: Gamma interaction cross-section for gadolinium ...... 75 APPENDIX D: Pulse processing parameters ...... 76

List of Tables

Table 1. A comparison of 0.0253 eV thermal neutron cross-sections of common neutron converter materials (Knoll, 2010)...... 8 Table 2. Characteristic x-rays emitted from an excited Gd atom ...... 15 Table 3. Conversion electron energies and their percentage yields per neutron capture in Gd...... 15 Table 4. A list of the parameters (programmable using the DPP-PHA acquisition software) along with corresponding values, used in the acquisition of 241Am energy histogram data using the digitizer...... 52 Table 5. Values of different parameters used in the acquisition of C-14 beta particle energy histogram...... 56 Table 6. DPP-PHA parameter values used in the measurement and acquisition of 57Co energy histogram data...... 58

List of Figures

Figure 1. Neutron interaction cross-sections for the neutron converter materials of interest (NNDC, Brookhaven National Laboratory, 2011)...... 7 Figure 2. Schematic representation of the major decay paths of 158Gd* ensuing a thermal neutron absorption in 157Gd...... 11 Figure 3. Prompt gamma ray spectrum of an excited Gd atom obtained from MCNP5 simulation of a thermal neutron beam interaction with a Gd foil...... 12 Figure 4. Standard prompt gamma ray spectrum from an excited Gd atom following a thermal neutron absorption in nat. Gd adapted from Revay Z, 2004...... 13 Figure 5: (a) Theoretical Auger electron and (b) characteristic x-ray transition probabilities observed during the relaxation of an excited Gd atom, derived from the atomic relaxation database of the code package PENELOPE...... 14 Figure 6. A visualization of the 72 keV electrons penetration into a 12 m thick Gd foil, using PENELOPE (Salvat, Fernández-Varea, & Sempau, The code 'SHOWER' in PENELOPE-2008: A Code System for Monte Carlo Simulation of Electron and Photon Transport, 2008)...... 17 Figure 7. Geometry used in the MCNP5 simulation that modeled a 500 keV photon beam interaction with a thin (12 m) Gd foil...... 18 Figure 8. K-X rays emitted from a 12 m-thick Gd foil after activation by a 500 keV gamma ray...... 19 Figure 9. Gamma ray rejection scheme with two semiconductor detectors, a Gd layer and a polyethylene layer...... 26 Figure 10. Traditional analog signal processing chain for radiation measurements adapted from Ref. (CAEN S.p.A., 2011)...... 27 Figure 11. A digital DAQ chain comprising the fundamental DPP blocks, adapted from Ref. (CAEN S.p.A., 2011)...... 31 Figure 12. (a) trapezoidal filter parameters and (b) trapezoidal filter output, adapted from Ref. [23] ...... 32 Figure 13. Button-sized 57Co and 14C radioactive sources from CANBERRA...... 40 Figure 14. The instrumentation facility located in the Nuclear Analysis and Radiation Sensors (NARS) laboratory at The Ohio State University...... 41 Figure 15. A 3-D view of the vacuum chamber and pump set up designed using SolidWorks 3-D CAD software (SolidWorks CAD software)...... 42

Figure 16. In-house constructed Al vacuum chamber in the NARS lab...... 43 Figure 17. NIM crate housing the HVPS and the digitizer...... 45 Figure 18. A block digram representation of the instrumentation system showing the vacuum chamber, the dry vacuum pump and the components of the digital DAQ system...... 47 Figure 19. Buffer occupancy in different modes of acquisition with the digitizer (CAEN SpA, 2011)...... 49 Figure 20. NIM analog DAQ system from ORTEC...... 50 Figure 21. Detector source geometry used for the 241Am alpha particle measurements inside the vacuum chamber (with the Al cap removed)...... 51 Figure 22. A screen-shot showing waveforms of the trigger signal, the preamplifier input signal, the trapezoidal output and the peaking signal generated by the DPP-PHA control software during acquisition...... 53 Figure 23. Screen shot of the energy histogram data of 241Am...... 53 Figure 24. The energy spectrum of 241Am obtained with a NIM analog and a digital spectroscopy system...... 54 Figure 25. The detector source geometry used in beta-particle measurements...... 55 Figure 26. A screenshot of the energy histogram data of 14C...... 56 Figure 27. Energy spectrum of beta particles from 14C observed using the Si charged particle detector...... 57 Figure 28. The detector source geometry used in the gamma ray measurements ...... 58 Figure 29. A screen shot of the 57Co energy histogram data...... 59 Figure 30. Energy spectrum of gamma rays from 57Co observed using the same Si charged particle detector...... 59 Figure 31. The experimental setup of two Si detectors viewing two button-sized radioactive sources...... 61 Figure 32. A visualization of the 156.5 keV fast electrons (14C β particles) penetration in a polyethylene slab of thickness 350 µm obtained using PENELOPE. The range of these electrons in polyethylene is about 302 µm (Salvat, Fernández-Varea, & Sempau, The code 'SHOWER' in PENELOPE-2008: A Code System for Monte Carlo Simulation of Electron and Photon Transport, 2008)...... 62 Figure 33. The spectrum from beta and gamma ray sources, the spectrum from gamma ray source alone and the subtracted spectrum, indicating a detector's response to IC and Auger electrons...... 63

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1. Introduction

Neutron detection is central to the prevention of proliferation and illicit trafficking of the special nuclear materials (SNMs). It is also an integral part of interdiction of radiological threats for homeland security purposes because the SNMs emit neutrons with unique signatures. For example, plutonium, a main component of nuclear weapons, is a significant source of spontaneous fission neutrons. Neutron detection technology thus plays a prominent role in nuclear non-proliferation and interdiction of SNM because neutrons can penetrate through materials that readily absorb gamma rays and also possess unique signatures (Runkle, Bernstein, & Vanier, 2010; Kouzes & Ely, 2010).

Helium-3 (3He), an inert and completely non-hazardous gas, is used in the most commonly deployed neutron detectors. The major application of 3He is in gas proportional counters for neutron detection, although it is also widely used in cryogenic physics studies and as a contrast agent in Magnetic Resonance Imaging (MRI). A hydrocarbon enriched moderator enclosure surrounding these tubes increases the sensitivity of the detection systems to neutrons emitted by SNM. Advantages such as stability, high sensitivity to neutrons and low sensitivity to gamma rays are offered by

3He tube, the dominant neutron detector used in homeland security practices, and are not on par with any other currently available detection technologies whose size is similar to that of a 3He tube. Because of the shortage of 3He, a replacement technology for

1 neutron detection is urgently sought. While a false negative is intolerable in homeland security detection scenarios, a false positive from a neutron detector can also have a significant negative societal impact. This requires any neutron detection technology to avoid generating, or at last to minimize, false neutron signals in the presence of a large gamma ray background (Kouzes & Ely, 2010). Hence, any potential neutron detection technology employing a neutron sensitive material should be able to address the two requirements of high neutron detection efficiency as well as good gamma ray rejection efficiency.

Semiconductor neutron detectors provide a solution to the need for compact portable neutron detectors. As the direct detection of neutrons through magnetic field is still beyond the reach of current detection technology, a material with high neutron absorption efficiency is normally required as the neutron conversion material. Gadolinium, with an extremely large thermal neutron cross-section, has been a good candidate for neutron converter material. However, the fundamental requirements outlined earlier in addition to other design challenges involved in the use of Gd as a neutron-sensitive material are to be investigated and addressed for a successful deployment of a Gd-based semiconductor detector.

2. Background

2.1 Neutron Detectors

Neutrons are electrically neutral particles just like gamma ray photons. Photons have no mass and interact directly with the electrons in matter whereas neutrons possess mass and do not interact directly with the electrons. Hence, existing methods for detecting neutrons in materials utilize exclusively indirect means. The sequence of events involved in the chain of a neutron detection include the interaction of incoming neutrons with various nuclei in matter, a release of one or more charged particles as a consequence of these interactions and generation of electric charge when the charged particles penetrate through the detection medium. The collected charge is then transduced into a voltage signal that is further processed by detector electronics (Crane & P.Baker, 1991).

Two basic types of neutron interactions with matter can be discussed. In the first interaction type, an incoming neutron is scattered by a nucleus, in which some of its energy is transferred to the nucleus. If enough energy is transferred, the recoiling nucleus ionizes the material surrounding the interaction site. This mechanism is only efficient for fast neutrons interacting with light nuclei. Thus, only hydrogen and helium nuclei are considered for practical detection applications based on neutron scattering mechanism. In the second reaction type, neutrons can induce a nuclear reaction. The products from these

3 nuclear reactions, such as protons, alpha, triton, lithium particles, gamma rays, and fission fragments, can trigger the detection process. Some reactions require a threshold on the neutron energy, but most reactions take place at thermal energies. Detectors based on thermal neutron reactions can be surrounded by a moderating material to increase the efficiency of fast or epithermal neutron detection. Detectors employing either of the interaction mechanisms may be in a solid, liquid or gas-filled detection media. The choice of a variety of detection media makes available many detector designs although the choice of conversion materials is indeed limited. Some of these are gas-filled proportional counters, boron-10 (10B) lined counters, scintillation detectors, fission chambers and semiconductor detectors commonly known as solid-state detectors (Crane

& P.Baker, 1991).

The thermal neutron detection systems provide no energy information due to the low energy and momentum of neutron compared to the large reaction Q-value. Even for fast neutron detection such as recoil-type counters, it measures only the first interaction event.

The complete neutron energy is usually not deposited in the detector, and the only energy information derived is roughly grouped as thermal and fast neutron. The detection systems that work on the principle of neutron-induced reactions may increase reaction probability (equivalently reaction cross-section of the involved nuclei) by moderating the incoming neutrons. Nevertheless, information about the initial neutron energy prior to moderation is lost and the energy recorded by the detector only indicates the reaction energy (Q-value). Thus, the neutron detectors in general provide information only on the number of neutrons detected and not on their energy. The rough range of detected

4 neutron energies can usually be estimated from the type of detector and the surrounding materials. Information on the neutron energy spectrum can sometimes be obtained indirectly by techniques such as proton recoil spectrometers, neutron time-of-flight measurements and helium (He) based spectrometers (Crane & P.Baker, 1991).

2.2 Solid-state neutron detectors

A solid-state detection medium provides great advantage in many radiation detection applications. In applications where the measurement of high-energy electrons or gamma rays is intended, the detector may have much smaller sizes compared to an equivalent gas-filled detector due to the fact that solid medium densities are much higher than those of gas. Scintillation detectors may offer a solid detection medium, but they are significantly limited by relatively poor energy resolution. The succession of events that take place in the transduction of incident radiation to optical photons and the ensuing generation of an electrical signal engrosses many inefficient steps. Consequently, the energy needed for the generation of a single information carrier is high (on the order of

100 eV) and thus the number of carriers produced in such an interaction event is not more than a few thousand. In addition, the statistical fluctuations in such a small number of generated information carriers place an inherent limitation on the attainable energy resolution. Hence, in order to reduce the statistical limit on energy resolution, the only solution is to increase the number of information carriers per radiation induced pulse

(Knoll, 2010).

The ionization induced by an ionizing radiation event in a semiconductor material gives rise to a relatively large number of charge carriers in the form of electron-hole pairs, compared to gas-filled and scintillation detectors. Semiconductor detectors thus offer high-energy resolution to ionizing radiations. Apart from this, semiconductor detectors can also provide desirable features such as compact size, relatively fast timing characteristics and an effective depth of radiation sensitive region that can be varied according to the requirements of a detection application. However, the main drawbacks of solid state detectors include the limitation to small sizes and high susceptibility to radiation-induced damage (Knoll, 2010).

Hence, in order to develop an efficient solid-state neutron detector, it is essential to select a semiconductor material that is highly resistant to radiation-induced damage and coupled with an efficient neutron conversion material.

2.3 Neutron converter materials

The most commonly used neutron converter materials are 3He, lithium-6 (6Li) and

10B. The increased demand for efficient neutron conversion materials for deployment in a variety of homeland security applications, triggered by a shortage of 3He, has stimulated a continued investigation for better neutron conversion materials. Gadolinium has an extremely high capture cross-section for thermal neutrons of about 49,000 barns (b).

Natural gadolinium (nat. Gd) has 15.65 % of 157Gd that has the highest thermal neutron cross-section (254,000 b) known for any radionuclide (Chadwick & al, 2006). Also,

155Gd has a significant thermal neutron capture cross-section of 61000 b, with an isotopic abundance of 14.8 % in nat. Gd. A plot of the neutron interaction cross-sections as a function of incident neutron energy for the different neutron conversion materials discussed is presented in Figure 1.

Figure 1. Neutron interaction cross-sections for the neutron converter materials of interest (NNDC, Brookhaven National Laboratory, 2011).

The various characteristic nuclear reactions and the corresponding thermal neutron cross-sections are summarized in the following table.

Material Type of nuclear reaction Cross section, σth (barns) 3He (n,p) 5330

6Li (n,α) 940 10B (n,α) 3840 155Gd (n,γ) 60890

157Gd (n,γ) 254,200

Table 1. A comparison of 0.0253 eV thermal neutron cross-sections of common neutron converter materials (Knoll, 2010).

Thus the superior thermal neutron cross-section of Gd makes it a potentially efficient neutron converter and forms a basis for the investigation of the neutron capture mechanism in Gd. Before studying the thermal neutron capture mechanics, it is important to revisit these neutron converter materials for their reaction energies and reaction products (Knoll, 2010) of corresponding nuclear reactions.

1. 10B(n,α) reaction:

Ninety-four percent of all the reactions lead to the excited state of Li atom

whereas only 6% lead to the ground state. Nevertheless, in either state the Q-value

of the reaction is high and thus the energy imparted to the reaction products is

high.

2. 6Li(n,α) reaction:

The triton and the alpha particle are emitted in opposite directions with

energies 2.73 MeV and 2.05 MeV respectively, for negligible incoming neutron

energy. Though the cross-section is lower compared to that of 10B, a higher Q-

value and thus high reaction products’ energy is still at advantage.

3. 3He(n,p) reaction:

Again, for the reaction induced by a slow (thermal) neutron, the reaction

products triton and proton are emitted in opposite directions with energies 0.191

MeV and 0.573 MeV respectively. The small reaction Q-value is offset to some

extent by a higher neutron cross-section than that for 10B.

4. 157Gd(n,γ) reaction:

The reaction products in this case include prompt-gamma rays and internal

conversion (IC) electrons. The mechanics of Gd neutron capture reaction are

discussed in some detail in the subsequent sections. In addition to the superior

thermal neutron cross-section of 157Gd, the reaction energy is higher compared to

the other nuclear reactions, but most of the reaction energy is contained by the

high energy prompt gamma rays emitted during the de-excitation of the 158Gd*

nucleus. These high energy gamma rays easily pass through a thin film

semiconductor material. Only about one percent of the reaction energy associated

with the low energy IC electrons contributes to a neutron signal, which is

apparently weak in a small volume semiconductor detector.

2.4 Interaction of neutrons with gadolinium

As discussed earlier, after a thermal neutron capture, the excited 158mGd atom returns to the ground state by a release of about 7937 keV energy in the form of prompt gamma- rays with competing internal conversion (IC) electrons, x-rays and Auger electrons.

Schultz D. et al (Schultz, et al., 2010) summarized the major decay paths involved in the de-excitation cascade of an excited 158Gd atom in the form of a schematic representation which is adapted and presented in Figure 2.

Figure 2. Schematic representation of the major decay paths of 158Gd* ensuing a thermal neutron absorption in 157Gd.

A simulation is performed using MCNP5 code package (Brown et al, 2002), in order to study the prompt gamma ray spectrum resulting from a thermal neutron capture in natural Gd. In this model, a neutron beam comprising 0.025 eV thermal neutrons is incident on a 12 µm thick Gd foil. The following plot (Figure 3) illustrates the output obtained for prompt gamma ray spectrum from the simulation.

Figure 3. Prompt gamma ray spectrum of an excited Gd atom obtained from MCNP5 simulation of a thermal neutron beam interaction with a Gd foil.

Although the simulation result is only an inexplicit illustration of the standard prompt-gamma ray spectrum (Figure 4), it still reveals few prompt gamma ray peaks and the baseline of other gamma rays, elucidating the theory on prompt gamma ray emission after a thermal neutron capture in nat. Gd.

Figure 4. Standard prompt gamma ray spectrum from an excited Gd atom following a thermal neutron absorption in nat. Gd adapted from Revay Z, 2004.

Although the common mechanism of de-excitation of an excited nuclear state is through the emission of gamma rays, some de-excitations involve the product of internal conversion (IC) that becomes significant and competes with the process of gamma ray emission. During IC, the nuclear excitation energy is transferred to an orbital electron of the atom and the electron is ejected from its original shell with energy equal to the difference between the excitation energy and the binding energy of the electron shell.

Depending on whether the IC is on the K, L, M or N shell, the emitted electrons from Gd will have energy in the range 29-182 keV. Following IC, a vacancy is created in the otherwise full electron shell, which results in an excited state of the atom. Subsequently the atom relaxes through the emission of Auger electrons and characteristic x-rays. Auger electrons and characteristic x-ray emission are another two competing mechanisms; the

13 transition probabilities of the radiative (x-rays) and the non-radiative (Auger electrons) transitions from an excited Gd atom are shown in Figure 5. The atomic relaxation database pdrelax.08 from the Monte-Carlo code package PENELOPE (Salvat,

Fernández-Varea, & Sempau, PENELOPE-2008: A Code System for Monte Carlo

Simulation of Electron and Photon Transport, 2008) has been used for this purpose.

(a) (b) Figure 5: (a) Theoretical Auger electron and (b) characteristic x-ray transition probabilities observed during the relaxation of an excited Gd atom, derived from the atomic relaxation database of the code package PENELOPE.

The following table summarizes the energies and relative intensities of the characteristic x-rays emitted during the relaxation of an excited Gd atom (Center for X-

Ray Optics and Advanced Light Source, 2009).

X-ray Energy (keV) Relative Intensity (%) K 43.00 100 α1 Kα2 42.31 56

Kβ1 48.70 20 K 49.96 7 β2 Kβ3 48.56 10

Lα1 6.057 100

Lβ1 6.713 62

Lβ2,15 7.103 21

Lγ1 7.786 11

Table 2. Characteristic x-rays emitted from an excited Gd atom

Since the high energy prompt gamma rays are almost transparent to a thin film semiconductor material, only the low energy IC and Auger electrons form the principal contributor of a neutron induced signal. These electrons contribute ~79 keV of energy which can be used for the generation of an electrical signal in a detector. Although the energy available for measurement in the form of IC and Auger electrons is only about 1% of the reaction Q-value, the superior thermal neutron cross section of 157Gd makes an energy deposition that is still 2.26 times higher than that of B-10. The three prominent conversion electron energies 71.2 keV, 29.3 keV and 78.2 keV, and their emission intensities per neutron absorption (Masaoka et al, 2003) are listed in the table below.

Conversion electron Abundance (%) energy (keV) 71.2 39.6 29.3 23.8

78.2 9.7 Table 3. Conversion electron energies and their percentage yields per neutron capture in Gd.

2.4.1 Intrinsic thermal neutron detection efficiency of a thin Gd foil

In this study, a Gd foil of 12 µm is considered for its intrinsic detection efficiency for

0.0253 eV thermal neutrons. The neutron absorption efficiency of a Gd foil of an arbitrary thickness ‘x’ is given by

Here, is the macroscopic cross-section of Gd, calculated using, .

where, is the thermal neutron absorption cross-section of Gd,

and is the atom density of Gd.

22 -3 -24 It is also known that = 3.025  10 cm , and = 49000 barns (49000 x 10 cm2) for natural Gd. Hence, it follows that the macroscopic cross-section of Gd for thermal neutrons is about 1482 cm-1. Thus, for a 12 µm thick Gd foil, the neutron absorption efficiency can be theoretically determined as

= 0.8312 (~83 %).

Assuming the 72 keV conversion electron as the principal neutron signal carrier with an emission probability of 39% per neutron absorption, the intrinsic thermal neutron detection efficiency associated with a 12 µm thick Gd foil can be calculated as

= 0.3242 (~32 %).

It is also of interest here to mention that an MCNP5 simulation modeling a 0.0253 eV thermal neutron beam interaction with a 12 µm thick Gd foil provided a neutron absorption rate of 1.73  102 cm-3 (source particle)-1. This implied an absorption reaction rate (RRabs) = 0.8297 per source particle. Thus, the thermal neutron detection efficiency for the foil is found as

= 0.3236 (~32 %),

As demonstrated, the simulation reproduced the theoretical result.

The range of a 72 keV fast electron in nat. Gd is computed using PENELOPE and found to be ~20.6 µm. Hence, the 72 keV fast electrons can easily pass through a Gd foil of thickness 12 µm (Figure 6), inducing the neutron signal into a semiconductor detector.

Figure 6. A visualization of the 72 keV electrons penetration into a 12 m thick Gd foil, using PENELOPE (Salvat, Fernández-Varea, & Sempau, The code 'SHOWER' in PENELOPE-2008: A Code System for Monte Carlo Simulation of Electron and Photon Transport, 2008).

2.5 Interaction of gamma rays with gadolinium

In section 2.4, it was discussed that the energy available for neutron detection following a thermal neutron capture in Gd is quite low compared to that of the reaction products from the nuclear reactions 10B(n,α) and 6Li(n,3H). In addition, Gd (Z=64) has a very high probability of interaction with gamma rays. Because of the high stopping power of Gd, detectors that incorporate Gd as the neutron conversion material are associated with an inherent gamma ray background. A typical interaction in which a high-energy gamma ray interacts with Gd, one of its atomic shells is ionized. As a result, an orbital electron is knocked out, leaving the atom in an excited state. Subsequently, the atom is relaxed to the ground state, during which the characteristic x-rays prominently from the K-shell are emitted.

An MCNP5 simulation modeling a 500 keV photon beam interaction with a 12 µm thick Gd foil inclined at 45° angle (Figure 7) demonstrated the emission of K-X rays as shown in Figure 8.

500 keV photon Detector disk source

Gd foil

Figure 7. Geometry used in the MCNP5 simulation that modeled a 500 keV photon beam interaction with a thin (12 m) Gd foil.

0.05

0.045

0.04

0.035

) -2 0.03

0.025

0.02

Fluence Fluence (cm 0.015

0.01

0.005

0 0 5 10 15 20 25 30 35 40 45 50 55 60 Energy (keV)

Figure 8. K-X rays emitted from a 12 m-thick Gd foil after activation by a 500 keV gamma ray.

Unlike the x-ray yield shown in Figure 5(b), the x-ray spectrum shown in Figure 8 does not show any L-shell x-rays (6-8 keV) but contains lines corresponding only to the

K-shell x-rays (Kα1 43.0 keV – the strongest line, Kα2 42.3 keV, Kβ1 48.7 keV, Kβ2 50.0 keV, Kβ1 48.6 keV (Center for X-Ray Optics and Advanced Light Source, 2009)). This is because the L-shell photo-ionization cross-section of Gd at 500 keV photon energy is only 1.15 barns compared to that of the K-shell at 8.18 barns. In fact, the K-shell photo- ionization cross-section of Gd at photon energy as low as 60 keV is about 2437.5 barns

(Scofield, 1973). The K-X ray production cross section is about 1828 barns at this energy.

Therefore, the production of this K-X ray is quite significant and the simulation result from MCNP5 code confirms the emission of K-X rays from Gd after gamma ray activation.

It is to be noted that the K-X ray interference in a Gd foil of thickness as low as 12

µm is significant, as demonstrated by the simulation result. It then follows that, although a thin film semiconductor detector with Gd as the neutron sensitive material is almost transparent to a high energy gamma ray, such a semiconductor may still receive a significant amount of interference from the low energy K-X rays. Hence, it is supposed that the low energy K-X rays emitted after activation of Gd by an external gamma ray interfere with the weak neutron signal. A gamma ray discrimination method is thus essential for a solid-state neutron detector employing Gd as the neutron converter. Thus, a suitable gamma ray rejection technique has to be formulated for such a neutron detector.

It is also observed that the study of Gd interaction with gamma rays in fact gives insight into gamma ray detection using Gd as a converter. Since Gd acts as a transducer in converting the high/medium energy gamma rays into low energy K-X rays, the detection of gamma rays is made possible in a thin film semiconductor detector.

However, the energy information of the incoming gamma rays is unachievable, which is inherent in this approach; nevertheless, the method is sufficient for many application scenarios where only the intensity of gamma rays is of interest.

2.6 Gamma ray discrimination techniques in neutron detectors

This section presents a review of some gamma ray rejection techniques available from the literature, followed by the proposition of a gamma ray discrimination method for a semiconductor neutron detector based on Gd.

2.6.1 A literature review of some gamma ray discrimination techniques

A 3He semiconductor sandwich spectrometer was investigated by Blum H. (Bluhm,

1974), in which a pair of two Si-surface barrier detectors was used along with 3He as the

3 gaseous conversion element. The gap (comprised of He and CH4) between the semiconductor detectors was used as a proportional counter. Secondary electrons generated from gamma rays caused lesser ionization when crossing this space, compared to that of protons and tritons from neutron absorption of 3He. The gamma rays and neutrons therefore were separated by analyzing the proportional counter pulses. The readout electronics comprised a signal processing circuit for the proportional counter and a different signal processing circuit for the Si detector pair. A two parameter analysis was considered, of which one parameter was the proportional counter pulse and another parameter was the sum of the three (proportional counter’s and the two semiconductor detectors’) pulses. A multiplication of the proportional counter pulses by the triple sum and subsequent analysis of the product signal with a single channel analyzer was considered. The 3He spectrometer accepted only those events that produced pulses in both, the semiconductor detectors and the proportional counter. The amplitude of these pulses exceeded the intrinsic noise of the electronic system. At first, the pulses originating from the semiconductors were considered separately. Following amplification, they were added up in a summing amplifier and gated by a fast coincidence circuit. After stretching this pulse to several microseconds, it was added to the proportional counter pulse in coincidence. The sum of these three detector pulses was connected independently to a multi-channel analyzer (MCA) and also to one of the inputs of an analog pulse height module (a computer). The second input of this computer was

21 fed with the proportional counter pulse alone and the product of the two inputs was considered. Thus, the module became active only if a coincident event was recorded in the spectrometer. It was generally observed that this product was much larger for the proton-triton pairs than for the electrons. The gamma ray background was simulated by a weak (5 mCi) radium gamma ray source near the spectrometer and pulse height distribution of the proportional counter was measured in coincidence with the semiconductor pulses for both the thermal and Am-Be source neutrons. An agreeable separation between the gamma ray background and the Am-Be neutrons was achieved.

The previously mentioned coincidence technique of multiplication of a sum of the signals from three detectors with the proportional counter signal alone was implemented when the spectrometer was exposed both to thermal neutrons and fission neutrons from Cf-252.

It was observed that separation of the gamma ray background was sufficient in both the scenarios. Additionally, a fast reactor neutron spectrum was measured using this spectrometer. From the pulse height distribution it was observed that the neutron spectrum was totally covered by a gamma ray background up to 1.5 MeV fast neutron energy when the gamma ray discrimination was not implemented. A fine separation of the neutron pulse heights from the gamma ray background was indeed seen when the gamma ray discrimination method was applied.

A neutron detector designed using silicon (Si) PIN photodiodes achieved gamma ray discrimination by the technique of signal subtraction (Aoyama et al, 1992). The detector consisted of two Si PIN photodiodes with a 25 μm-thick Gd foil placed outside the sensitive surface of one of the diodes. The PIN diodes using Gd as the neutron converter

22 cannot detect neutrons separately from γ-rays. Hence, in order to achieve gamma ray discrimination, a second photodiode with a tin (Sn) foil instead of Gd, was employed.

Since Sn has a negligibly small neutron-capture cross section, but an atomic number (Z =

50) close to that of Gd (Z = 64), a Sn foil having roughly the same mass thickness as the

Gd foil was used to cancel out the generation and absorption of Compton electrons in the

Gd foil. A Sn foil was attached to the sensitive surface of the second diode in the same manner as the Gd foil was coupled to the first diode. A thick Lucite board was inserted between the photo diodes to prevent the conversion electrons emitted after Gd neutron capture from entering the second photodiode and thus achieve γ-compensation. The detector response was examined using a Cf-252 neutron source. Energy spectrum of the electrons generated from neutron absorptions and gamma ray interactions in each foil and photodiode was observed. The energy spectrum obtained from the photodiode with Gd foil had humps corresponding to the energies of internal-conversion electrons whereas the spectrum obtained from the photodiode with Sn foil had no humps because of

Compton electrons generated by relatively high energy of gamma rays from the Cf-252 source. The lower and upper level energy thresholds were appropriately selected in order to attain a decent gamma ray separation. The best gamma ray separation depends not only on the n-γ count ratio but also on the detection efficiency for neutrons and was attained with the maximum upper-level threshold, using the integral mode of the single channel analyzer (SCA). The net neutron counts were estimated from the difference of the counts obtained from each photodiode with different lower-level threshold.

Fernandez F. et al investigated the separation of neutron signal from the gamma ray component in mixed n-γ fields using differential pulse analysis techniques with a double silicon diode (Fernandez et al, 1997). A double diode consisting of two Si diodes positioned on either side of a single silicon bulk following a 40 µm-thick polyethylene converter was used as a dosimeter detector for real time neutron dosimetry. The depletion thickness of the diodes was roughly 30 μm, with a thickness of 222 μm for the Si bulk separating the two depletion zones. The characteristics of the detector ensured that no differences between the electrical properties of the diodes emerge. When irradiated in a neutron field, the polyethylene converter resulted in protons emerging with a fluence rate roughly proportional to the neutron dose rate in the energy range 100 keV to 5 MeV. An energy calibration was performed using two types of radiation, which included photons from a 60Co source for low energy loss rates, and alpha particles from an Americium-241

(241Am), 239Pu and 244Cm combined source for high energy loss rates. After calibration, the dosimeter was irradiated with different mono-energetic neutron beams of 73 keV, 144 keV, 250 keV, 570 keV, 1.2 keV and 2.5 MeV with corresponding dose equivalent rates.

The neutrons were incident normally onto the detector. A net energy spectrum was calculated by subtracting the integrated spectrum obtained in the back diode from that obtained in the front one. This resultant spectrum was associated mainly with protons originated in the polyethylene converter. From the spectra obtained for each diode and also the net spectra for incident neutron energies of 0.250 MeV and 0.570 MeV, it was concluded that the energy cut-off for neutron detection should be on the order of 250 keV, and the exponential behavior of the net spectrum confirmed that these spectra originate from the contribution of electromagnetic radiation. Deviations from this

24 exponential behavior were observed in cases of neutron energies of 1.2 MeV and 2.5

MeV due to the presence of recoil protons with maximum energy equal to the incident neutron energy. It was concluded that, in its actual configuration, the dosimeter displayed a low response value for low energy neutrons and a high response value for photons.

Thus an energy threshold of the order of 250 keV was required in practice.

It is seen that the technique of differential pulse analysis was commonly employed for gamma ray discrimination in neutron dosimeters. Gamma ray interference on an electronic dosimeter (Barelaud et al, 1992) response in a neutron field was investigated by Paul D. et al (Paul et al, 1992), whose study demonstrated that several dosimeter parameters such as depletion depth of the diodes, threshold voltage, constitution of the sensor (structure, materials used for its composition) must be optimized in order to effect the discrimination of the greatest number of gamma ray pulses.

2.6.2 Proposed gamma ray discrimination scheme

A gamma ray discrimination technique based on signal subtraction has been proposed for a semiconductor detector based on Gd. This technique requires two semiconductor detectors, one of which is sensitive to neutrons while the other is completely insensitive to neutrons. This discrimination can be achieved by introducing a layer of the neutron converter material Gd and another layer of an electron separator

(polyethylene) into the composite detector scheme. The proposed gamma ray rejection scheme is illustrated in Figure 9, in which two semiconductor detectors are separated

25 from each other by a thin Gd foil and a polyethylene separator. A polyethylene layer of appropriate thickness stops all the IC and Auger electrons originating from neutron absorption in the Gd layer. Hence, it follows that the detector on the Gd layer end generates a combined neutron and gamma ray induced signal whereas the detector on the separator end produces a signal induced only by gamma rays. Thus, subtraction of these two signals yields an output signal induced solely by neutrons.

Figure 9. Gamma ray rejection scheme with two semiconductor detectors, a Gd layer and a polyethylene layer.

2.7 Theory of radiation measurement systems and digital pulse processing (DPP)

techniques

A detector responds to the incident ionizing radiation by generating a weak electrical signal, which can be easily lost in the absence of an appropriate signal conditioning. The detector signal also needs to be processed in the subsequent stages in order to be made suitable for measurement and thus extract relevant information about the incident radiation. A radiation measurement system is a data acquisition (DAQ) system that

26 features necessary electronics and signal processing modules, which enable the detection of incident radiation and determination of certain quantities of interest like energy, time of arrival etc., of the incident radiation.

2.7.1 A review of DAQ systems used in radiation measurement

The basic components in a typical radiation induced signal processing chain are shown in Figure 10.

CHARGE SENSITIVE ENERGY PREAMPLIFIER PEAK SENSING DETECTOR ADC PC

− SHAPING Trigger, coincidence + AMPLIFIER Shaping time POSITION constant, LOGIC INFORMATION Gain DISCRIMINATOR UNIT

TIMING TIME TO INFORMATION DIGITAL CONVERTER (TDC) THRESHOLDS COUNTS SCALER/ COUNTER

Figure 10. Traditional analog signal processing chain for radiation measurements adapted from Ref. (CAEN S.p.A., 2011).

An incident radiation quantum interacts in the detector and deposits energy. The fundamental output of all pulse type radiation detectors is a burst of charge Q liberated by a single radiation quantum in the detector as an outcome of energy deposition. The liberated charge is typically proportional to the energy deposited and is converted into a

27 current pulse. The net charge collected at the detector output is usually too small to be detected directly. Hence, this current is first sent to a preamplifier that acts as an interface between the detector and the subsequent signal processing electronics. The preamplifier typically has a charge sensitive configuration, and thus integrates the transient current pulse to generate a voltage step ΔV that is proportional to the charge present at its input.

The preamplifier also comprises a resistor in its feedback loop, called a feedback resistor, which restores the input to ground with a very long time constant (given by the product of the resistor and capacitor values in the feedback loop) usually on the order of hundreds of microseconds. By restoring the preamplifier input to ground, it is effectively prepared to sense another charge burst from the next radiation quantum interacting in the detector.

The next circuit block in the signal chain is a shaping amplifier that transforms the preamplifier output signal into a form suitable for measurements. The output from the shaping amplifier is a voltage pulse with pulse amplitude (more commonly called pulse height) Vpeak proportional to the generated charge Q. Since the magnitude of Q reveals the energy deposited by the incident radiation quantum in the detector, recording the pulse height distribution is a powerful tool to obtain information about the energy distribution of the incident radiation (Knoll, 2010).

The shaping amplifier filters high and low frequency noise by means of a high pass filter and a low pass filter in its first and last stages respectively. Thus, a shaping amplifier improves the signal-to-noise ratio. Also, the output from the shaping amplifier must rapidly return to the baseline in order to avoid overlapping of pulses and subsequent

28 distortion in the measurement. The output should return to true zero between pulses so that the pulse peak is referenced to the correct baseline. The name shaping amplifier is thus attributed due to the noise filtering and baseline restoration characteristics of the amplifier that modify the pulse shape (Knoll, 2010).

The shaped pulse is sent to circuits that select pulses for further processing. This selection may be very simple – for example, an integral discriminator selects all pulses with pulse height above a certain threshold. A differential discriminator, also known as a single channel analyzer, selects pulses with peak amplitude between an upper threshold and a lower threshold. More complex logic, if available, may perform functions like pile- up rejection, i.e. rejection of radiation events that pile up or exhibit distorted pulse shapes. Many systems (for example those used for coincidence measurements or other timing applications) involve the detector signals to be triggered within a narrow time bin as part of the selection logic (Knoll, 2010).

These selected pulses (and thus the radiation events) are subsequently processed by simple circuits like counters and more complex circuits like an MCA (or a peak sensing

Analog to Digital Converter). The MCA measures the pulse height for each of a series of selected events and allocates the height to one of several pulse height channels, incrementing a counter corresponding to that channel each time the selected event is allocated to that channel. The result is a histogram, called a pulse height spectrum, that displays the distribution of pulses and thereby an energy distribution of the incident radiation (Knoll, 2010).

The DAQ system discussed thus far is almost analog in that the analog-to-digital

(A/D) conversion is performed only at the end of the acquisition chain. But in recent years, the availability of very fast and high precision flash Analog-to-Digital Converters

(ADCs) permits the design of DAQ systems in which the A/D conversion takes place as close as possible to the source of signal (i.e., the output of the detector or the preamplifier). After the A/D conversion, specific algorithms can be applied for extracting certain quantities of interest like pulse height, time of arrival, etc. by means of digital filters and other pulse processing blocks, that mostly are analogous to the analog circuit blocks, such as a timing filter, shaping amplifier, constant fraction discriminator (CFD) etc., at least from a functional perspective (CAEN [n] Electronic Instrumentation, 2011).

In theory, a digital acquisition system is information lossless, provided that the

Nyquist criterion (Kester, 2009) is met. But in practical applications, the acquisition is affected by errors arising from quantization noise and other sources of electronic noise. In general, the applications that require precise timing measurements are more disposed to the use of digital data processing modules (hereafter called “digitizer”) with high sampling frequencies (e.g., 500 mega samples per second (MS/s) or greater), whereas the applications where high energy resolution is a requirement for the acquisition favor digitizers with 12-14 bits for the A/D conversion (CAEN SpA, 2011). A fully digital approach also offers advantages such as high stability, reusability and ability to reprogram the pulse processing algorithms that enable customization. The most common functional blocks in the DPP chain are shown in Figure 11.

DIGITIZING MODULE

DETECTOR SIGNAL ENERGY INPUT DIGITAL SAMPLES COUNTS HARDWARE PC ADC DPP TIMING INTERFACE

LOW SHAPE PASS FILTER A very high data throughput

Figure 11. A digital DAQ chain comprising the fundamental DPP blocks, adapted from Ref. (CAEN S.p.A., 2011).

But a major problem of the digital approach is the extremely high amount of data to be read. Hence, it becomes impossible to maintain a continuous acquisition, transfer raw data to a computer and perform the analysis off-line. Consequently, it is critical to implement certain on-line digital data processing operations (for e.g., zero suppression and/or DPP) for reducing the amount of data and extract from the sequence of raw samples only specific parameters that are necessary in the acquisition and which preserve the information required by the physics. This procedure thus minimizes the data size pertaining to each single event (CAEN SpA, 2011).

The following section will discuss an example of a digital pulse processing block similar in operation to an analog signal processing module, a trapezoidal digital filter that is also the central component of DPP-based pulse height analysis (DPP-PHA).

2.7.2 Trapezoidal energy filter

The trapezoidal filter is the digital equivalent of a shaping amplifier in the analog signal processing chain and is the most commonly used digital filter in DPP. The filter operates on the digitized form of the preamplifier output signal. The principle of operation of a trapezoidal filter is described in Ref. (Byun, 2009-10) and is summarized below.

It is understood that the preamplifier output signal is digitized into discrete samples

th and let the i input data point (sample) be denoted by Vin[i]. The following steps illustrate the operations involved.

1. The average value for the next L data points is computed as (Figure 12a).

The quantity ΔtL is the time interval corresponding to the length of the data samples L.

Figure 12. (a) trapezoidal filter parameters and (b) trapezoidal filter output, adapted from Ref. [23]

2. A separation gap of G number of data points is considered and another average

for the data length L is computed as follows,

The quantity ΔtG is the time interval corresponding to the length of the data samples G.

3. The trapezoidal filter output Vout[i] corresponding to the input data point Vin[i] is

computed below:

When these operations are performed on all data points in the input, the output pulse transforms into a trapezoidal shape as suggested by its name (Figure 12b). The output pulse has a peaking time equal to ΔtL, referred to as the trapezoidal rise time and a ‘flat top duration’ of ΔtG. The fall time of the pulse is the same as rise time, given by ΔtL.

Thus, the total width of the output pulse is ΔtG + 2ΔtL. Both ΔtL (rise time) and ΔtG (flat top duration) are employed as freely adjustable parameters in order to shape the output pulse, analogous to the shaping time constant (τ) of the spectroscopy (shaping) amplifier.

The flat top duration of the trapezoidal signal enables improvement of the detector charge collection when the rise time is shorter than the charge collection time of a fraction of carriers. It is to be noted that in analog pulse processing, another step after the semi-Gaussian shaping of the input pulse is required for pulse height analysis (i.e. A/D conversion), whereas in the case of a trapezoidal filter, the digitized pulse height is already available. Accordingly, the processing speed in DPP is faster (Byun, 2009-10).

2.7.3 Operation of a digitizer built by CAEN SpA

The basic operating mode of a digitizer is essentially the same as a digital oscilloscope. The input signal stage conditions the analog signal primarily to settle into the dynamic range of the ADC. A flash ADC in the subsequent stage samples the analog signal into a stream of digital samples. This sample stream is continuously read by an

FPGA and stored in a circular memory buffer of a programmable size. At the onset of a trigger, the buffer is frozen and made accessible for readout while the acquisition continues in a new buffer (CAEN SpA, 2011).

The functions of a digitizer that distinguish it from a commercial digital oscilloscope are featured in Ref. (CAEN SpA, 2011) and outlined below.

 The digitizers allow for dead‐timeless acquisition. Different from most

oscilloscopes, the digitizer can accept consecutive triggers that are closely spaced

in time due to the utility of multi-buffer memory management. Hence, there is no

dead time between an acquisition window and the next one. It is also possible to

accept two triggers for which the acquisition windows overlap. The dead‐timeless

acquisition is a very important feature, particularly in the case of events that are

randomly distributed in time, so that even at low rate, two such events when occur

in a very short interval can be captured.

 In the digitizer, all the channels can generate a trigger at any point of time. A

channel generating a trigger can either use it locally (independent triggering) or

contribute the trigger to the assertion of a global trigger for all the channels in the

board.

 The digitizers allow for multi-board synchronization and system scalability. It is

possible to synchronize several boards to make an acquisition system with a

theoretically unlimited number of channels. Board synchronization enables to

have events with correlated time stamps and implementation of coincidences by

distributing the channel auto‐triggers and the global triggers according to

programmable trigger logic.

 The digitizers can provide data transfer rates at high bandwidth to a computer or

an external processing unit.

 The acquisition in the digitizers is performed by means of field programmable

gate arrays (FPGAs) that are programmable devices. They feature the

functionality of managing the stream of ADC samples and implement online

digital algorithms for signal processing. This feature is essential to the

implementation of systems that are based not only on the acquisition, storage and

readout of waveforms but also on the extraction of certain quantities of interest

like pulse height, the arrival time, the baseline, charge corresponding to a pulse

and other parameters. This offers a clear advantage in terms of readout bandwidth

when the storage and readout of only the final results are required.

2.7.4 Digital treatment of the signal – advantages and disadvantages

Some of the advantages of pulse processing in digital domain are described in Ref.

(CAEN SpA, 2011) and are summarized below.

 Energy, timing and pulse shape analysis measurements can all be incorporated

into a single board, thus minimizing cost and improving reliability.

 DPP offers good linearity, stability and reproducibility.

 The issues of pulse pile-up, ballistic deficit and baseline fluctuation can be

corrected by digital techniques in a better fashion.

 A dead-timeless acquisition gives a high counting rate and the pulse information

is preserved along the entire signal chain.

 Pulse processing in the digital domain offers wider dynamic range for analog

inputs and the system performance is maintained uniform over the range.

 Flexibility in programming and reprogramming the algorithms is made possible

by means of the FPGAs. Thus, adaptability to different application scenarios can

be achieved.

 In terms of tuning and calibration, the register programming instead of manual

regulations makes the process faster and automatic.

A deep understanding of the digital algorithms and other relevant parameters is essential for setting up the system. In addition, significant technical support is needed for

36 customization in applications, and it may also stipulate knowledge of a hardware description language for programming the FPGAs (CAEN SpA, 2011).

3. Experimental approach

3.1 Objective and the Experiment

The purpose of the experiment is to corroborate the proposed gamma ray discrimination technique by means of a ‘proof-of-principle’ investigation. An experiment involving two commercially available semiconductor detectors and two radioactive sources has been designed with the objective of confirming the concept of the gamma ray discrimination technique. In this experiment, a pure beta source (emitting only beta particles) is chosen to model the IC and Auger electrons from thermal neutron absorption in Gd and a pure gamma ray source (emits only gamma ray photons) is chosen to surrogate the characteristic x-rays that cause main interference to the weak electron signal. These two sources are used in combination with two identical semiconductor detectors. During the experiment, one of the detectors is shielded from beta particles while the other detector is left unshielded, in order to reproduce the neutron-gamma discrimination scenario.

3.2 Radioactive sources for a ‘proof of principle investigation’

As mentioned earlier, the objective of this experiment is to be able to reproduce the scenario that will arise when a compound Gd-coated thin film semiconductor neutron

38 detector is exposed to a mixed n-γ environment. It was also discussed earlier that the principal component of neutron signal from Gd is the energy associated with the IC and

Auger electrons, whereas the prominent interference to these low energy electrons is posed by the characteristic x-rays. Hence, it is crucial to select two separate radioactive sources that are a pure beta emitter and a pure gamma ray emitter, respectively. After some investigation, it was concluded that 14C, a pure beta emitter, is an adequate substitute for the source of electrons. The maximum energy of the beta particles emitted from 14C is about 156.5 keV with average energy of the beta spectrum about 49.5 keV.

Since the most prominent electron energies resulting from a neutron absorption in Gd are

71.2 keV, 29.3 keV and 78.1 keV, the selection of 14C as a conversion and Auger electron source is justified. Similarly, 57Co was chosen as a pure gamma ray emitter. 57Co decays to 57Fe by the mode of electron capture and in the de-excitation process emits gamma rays with energies 122 keV, 136.5 keV and 14.4 keV. The photon with energy of 122 keV is emitted predominantly with a relative intensity of about 85.6 % and plays the role of a surrogate to the characteristic x-rays. Although the photon energy involved (122 keV) is not quite close to that of the characteristic x-rays, it is still deemed an appropriate choice as the most important requirement is that the source is a pure gamma ray emitter.

Another factor to be considered in this measurement is the strength (activity) of the gamma ray source; a strong gamma ray background will provide a strong interference to the desired signal, under which conditions the proposed discrimination scheme is to be substantiated.

Two button-sized radioactive disk sources of 14C and 57Co (Figure 13) from

CANBERRA are used in this experiment. At the time of purchase, the activity of the 57Co source was 100 µCi, with a half-life of only about 272 days, whereas the activity of the

14C source was 10 µCi, with a much longer half-life (~5730 years).

Figure 13. Button-sized 57Co and 14C radioactive sources from CANBERRA.

3.3 Instrumentation system for the measurements

The instrumentation facility built for the requirements of this research is shown in

Figure 14. The system comprises an in-house constructed aluminum (Al) vacuum chamber, a dry vacuum pump and a digitizer (digitizing module) based DAQ system.

Figure 14. The instrumentation facility located in the Nuclear Analysis and Radiation Sensors (NARS) laboratory at The Ohio State University.

3.3.1 In-house Al vacuum chamber

In order to perform the measurements required in the experiment, it was essential to build a vacuum chamber that provides a moderate-to-high vacuum environment. A vacuum chamber is also essential to perform measurements that entail negligible loss in particles’ energy preceding energy deposition in a detector; for e.g. measurements requiring high energy resolution, alpha particle measurements for evaluating the charge collection efficiency of novel semiconductor detectors etc.

The SolidWorks software for three dimensional (3-D) drawing was used to design a

3-D model of the vacuum chamber assembly and produce corresponding technical drawings needed for the making of the chamber. A 3-D model of the vacuum system

41 setup is shown in Figure 15. The figure shows the vacuum chamber connected to a vacuum pump by means of a flexible stainless steel hose.

Figure 15. A 3-D view of the vacuum chamber and pump set up designed using SolidWorks 3-D CAD software (SolidWorks CAD software).

The vacuum chamber has a bell-shaped structure comprising an Al cap that rests on an Al base-plate. The top surface of the base plate is equipped with a circular groove that houses a viton O-ring. During vacuum operation, the cap is mated with the base plate by means of the O-ring, with the force of gravity establishing the mate. When air is pumped out from the chamber, gravity enables the cap to mate with the base plate and a tight seal is established between the mating components by means of the O-ring. Thus, vacuum leakage is avoided and the vacuum level in the chamber is retained after the pump is isolated from the chamber.

The base-plate of the chamber has four ports for electrical inputs/outputs and one inlet vacuum port for evacuating the chamber, on its bottom surface. The Al cap of the

42 chamber has a port on its top surface, to which a thermocouple vacuum gauge is connected for measuring the pressure inside the chamber. The chamber pressure and thus the level of vacuum is indicated in mtorr/mbar on an LCD display connected to the thermocouple pressure sensor. A stainless steel flexible hose is connected on one end to the vacuum inlet of the base plate and on the other end to a dry vacuum pump, by means of Al cast clamps. A ball valve is connected at the chamber end of the hose to enable isolation of the chamber from the pump and to retain vacuum inside the chamber. An air vent valve is also included in the chamber assembly to let the chamber down to atmospheric pressure, without manipulating the chamber-pump assembly (Figure 16).

Figure 16. In-house constructed Al vacuum chamber in the NARS lab.

The dry vacuum pump from OSAKA Vacuum Inc. is an advanced, remotely operable pump that features RS-232 communication interface. The pump produces a minimal amount of mechanical vibrations while in operation, thus mitigating the issue of microphonic noise in electrical signals. Such a provision is very critical in low energy radiation measurements which involve the detection of a weak electrical signal.

3.3.2 DAQ System

A multi-channel DAQ system from CAEN SpA, comprising a charge sensitive preamplifier, a high voltage power supply (HVPS) and a digitizer, is used for the measurements. The HVPS and the digitizer are both housed in a standard Nuclear

Instrumentation Module (NIM) crate. Each module in the system has four independent channels that enable simultaneous data acquisition from four detectors. A brief description of each module in the DAQ system follows.

1) Charge sensitive preamplifier (version A1422B090F3): The preamplifier uses a

single signal cable to supply a bias voltage input to the detector and also receive

the detector output. The preamplifier receives high voltage input from the HVPS

module. Input charge bursts from the detector are converted into sharp voltage

pulses with very small rise time and long decay period. The output channels on

the preamplifier feed these voltage pulses to corresponding input channels on the

digitizer for subsequent signal processing.

2) NIM crate (NIM8305 – 2 Slot switching 450 W mini crate): A two slot NIM crate

with switching power supplies. The crate houses the HVPS and the digitizer

modules (Figure 17) and is equipped with three ventilation fans which lower the

heat dissipated when the modules are in operation. This crate is connected to an

external AC voltage supply and provides power to the modules using two high-

quality NIM connectors located on the back plane of the crate. Also, the pre-

amplifier is supplied voltage for its operation by means of a RS-232 connection to

the crate; the crate has a corresponding connector on its rear side.

Figure 17. NIM crate housing the HVPS and the digitizer.

3) HVPS (N1471): The HVPS provides a maximum voltage of 5.5 kV with a very

low voltage ripple. The power supply is programmable and remotely operable

from a terminal on the host computer.

4) Digitizer (N6724): The digitizer is central to the DAQ system. Single-ended

analog inputs in the range 0-2.25 Vpeak-to-peak are allowed. The resolution of the

ADCs is 14 bits, with a sampling rate of 100 MS/s, ideal for applications that

demand a high energy resolution. The digitizer consists of FPGAs in each

channel. These are loaded with a DPP trapezoidal filter based firmware (DPP-

PHA) [26] that performs the required pulse processing operations. For each

individual channel, the trigger signal is generated using a trigger and timing filter

(RC-CR2; equivalent of a constant fraction discriminator). Also, each detection

event is associated with a trigger time stamp corresponding to the arrival time of

the pulse. The preamplifier output signal is processed by a trapezoidal digital

filter algorithm into a trapezoidal output pulse. The height of this pulse is

proportional to the energy deposited in a detector. The firmware also features

other functionalities which include pulse height analysis (energy histogram),

timing analysis (time histogram), pileup rejection, baseline restoration etc. All

required operations like start/stop acquisition, tune different parameters,

read/write etc., are performed online by means of a java graphical user interface

(GUI) for the associated DPP-PHA control software on the host PC (CAEN -

Electronic Instrumentation, 2012).

A block diagram illustration of the instrumentation system discussed is presented in

Figure 18. The figure shows the vacuum chamber connected to the dry vacuum pump, four independent detector channels of the digital DAQ system, components in the DAQ system which include the charge sensitive preamplifier, the HVPS and the digitizer interfaced to a host PC.

High USB link for Vacuum voltage remote operation chamber power supply (HVPS) High voltage supply cables Host PC

Preamplifier Digitizer

Data Preamplifier transfer link Detector output (USB) input Dry vacuum pulses pulses pump

Figure 18. A block digram representation of the instrumentation system showing the vacuum chamber, the dry vacuum pump and the components of the digital DAQ system.

3.3.3 Different acquisition modes with the digitizer

By virtue of the DPP capabilities, the digitizer can be operated in different modes of acquisition like oscilloscope mode, list mode, mixed mode and histogram mode (CAEN

SpA, 2011). A brief discussion of each mode is presented below.

1. Oscilloscope mode: This is the standard acquisition mode of the digitizer and works only when the digitizer does not feature any DPP firmware. The sequence of waveform samples from the acquisition window associated with each trigger is saved into one local memory buffer. This mode is useful for monitoring the signals at different stages, to tune

47 the parameters and observe the effect on filters’ response and more generally, for tuning and debugging an acquisition.

2. List Mode: In this mode, the DPP algorithms are applied dynamically in runtime on a continuous data stream by means of the FPGAs. Whenever a pulse is detected, the required quantities of interest are computed and written to the memory buffers, thereby creating a list of those quantities. Once the list reaches a certain size, this data buffer is presented for readout while the acquisition continues on a different buffer with no dead- time. Even when the pulse rates are very high, continuous acquisition is sustainable in this mode, due to a great reduction in the amount of data to store and transfer.

3. Mixed Mode: This mode of acquisition stores both the waveform samples and the relevant quantities that are the result of DPP algorithms, into the memory buffers. Only the signal component pertaining to an acquisition window defined by the trigger is saved.

Accordingly, only the quantities resulting from those samples within that acquisition window are saved. This mode enables an acquisition which requires both the waveform samples and the relevant DPP output quantities at the same time. The mixed mode is indeed fundamental to observe the effect of DPP algorithms on a specific waveform.

4. Histogram mode: This mode is essentially the same as the list mode, except that the memory buffer accumulates the DPP output quantities (like energy, time etc.) in a histogram which increases in size continuously until an external interrupt is provided or the maximum counting range is reached (232).

The difference in occupancy of the memory buffer when running in oscilloscope mode (all the samples are saved), in energy list mode (saving only the energy value in the memory buffer) and in mixed mode is shown in Figure 19.

Figure 19. Buffer occupancy in different modes of acquisition with the digitizer (CAEN SpA, 2011).

4. Experimental setup and instrument calibration

An experimental setup comprising the in-house constructed aluminum vacuum chamber, mounting structures for the detectors and sources, and the digitizer-based multichannel DAQ system from CAEN SpA, is built. For comparison, an analog NIM system from ORTEC (Figure 20) was also used along with the digitizer-based DAQ system for system calibration.

Figure 20. NIM analog DAQ system from ORTEC.

Before the mixed beta-gamma (β-γ) measurement, system calibration is carried out using a 241Am radioactive source, which emits 5.486 MeV α-particles, and a Si charged particle detector (ion-implanted) to evaluate the functionality of the instrumentation system. These energetic α-particles have a range of about 4.2 cm in air. If the particles suffer an energy loss before reaching the surface of the detector, the 5.486 MeV energy will not be deposited in the detector entirely. This leads to some energy smearing and broadening of the energy peaks in the output spectrum of the particles. By maintaining an

50 ideal level of vacuum inside the chamber in these measurements, energy loss of the particles can be fully restrained. This means that a loss in energy resolution or degradation of the output spectrum should only arise from the characteristics of the detector or the acquisition system. Thus, a measurement of alpha particles of known energy serves as a calibration tool and ensures the desired functionality of the detectors in combination with the readout electronics, supported by an optimized energy spectrum.

The conventional analog spectroscopy system was employed to supply a reference to the digitizer response. The analog NIM system from ORTEC offered specific shaping time constants for the pulse-shaping amplifier whereas the digitizer required the pulse processing parameters to be adjusted via firmware.

Figure 21. Detector source geometry used for the 241Am alpha particle measurements inside the vacuum chamber (with the Al cap removed).

Inside the vacuum chamber, the alpha source and the detector were mounted facing each other with a separation span of just above 3 cm (Figure 21). The dry vacuum pump produced a moderate to high vacuum inside the chamber. The thermocouple pressure gauge connected to the vacuum chamber indicated a 10 mTorr pressure inside the chamber at which point negligible particle energy loss was ensured. The NIM measurement setup consisting of a charge sensitive pre-amplifier and a shaping amplifier

51 with a shaping time constant of 1 μs were connected to a multichannel analyzer. The digitizer-based DAQ system consisting of the charge sensitive pre-amplifier and the multichannel digitizer were connected with a USB interface to the host computer. The required digital pulse processing algorithms were loaded by manufacturer-supplied firmware onto the FPGA boards. The trapezoidal digital filter was set up with a rise time of 1.2 μs and a flat top duration of 2.8 μs. The values of all parameters used in the acquisition are summarized in Table 4.

TRAPEZOIDAL FILTER TRIGGER GENERATION Parameter Value Parameter Value Decay time 200 µs Trigger threshold 35 LSB* Rise time 1.2 µs Smoothing factor 32 Flat top duration 2.8 µs Delay or rise time 0.8 µs Baseline mean 16384 Hold off 1 µs Trapezoid gain 1 Peaking delay 1 µs Peak mean 64 Baseline hold off 0.1 µs Peak hold-off 1.4 µs *Note: The value of LSB is determined by the input dynamic range of the ADC and the number of ADC bits for digitization. For the current digitizer LSB = 2250 mV/214 = 0.137 mV. A description of the different parameters for acquisition using the DPP-PHA control software is provided in APPENDIX D.

Table 4. A list of the parameters (programmable using the DPP-PHA acquisition software) along with corresponding values, used in the acquisition of 241Am energy histogram data using the digitizer.

Some screen-shots obtained during the experiment using a plotter tool embedded in the software are shown in the following figures. Figure 22 shows the trigger signal (magenta), the input preamplifier signal (green), the trapezoidal digital filter output (red) and the peaking signal (blue). Figure 23 shows a screenshot of the 241Am energy histogram.

Figure 22. A screen-shot showing waveforms of the trigger signal, the preamplifier input signal, the trapezoidal output and the peaking signal generated by the DPP-PHA control software during acquisition.

Figure 23. Screen shot of the energy histogram data of 241Am.

The detector to be calibrated has a manufacturer-claimed best energy resolution of

16.0 keV at 5.486 MeV from 241Am if the experimental conditions follow the ORTEC standard NIM electronics and procedures. The acquired histogram data indicated an

53 energy resolution of 16.0 keV for the 5.486 MeV peak in the spectrum, with no difference observed between an analog and a digital spectroscopy. As shown in Figure

24, the output spectra from the analog and digital systems clearly differentiate the 5.486

MeV, 5.443MeV and 5.388 MeV peaks from a 241Am alpha source.

Figure 24. The energy spectrum of 241Am obtained with a NIM analog and a digital spectroscopy system.

The digitizer based DAQ system enables multichannel acquisition and is used in the simultaneous measurement of β and γ responses in the Si detectors. In order to gain some insight into the mixed β-γ measurement scenario, at first, separate β and γ-ray measurements were performed using the digitizer. The measurements helped observe the detector response separately to beta particles and gamma rays.

4.1 β-particle measurements

The experimental conditions followed were the same as in the case of alpha measurements. The detector-source geometry used in this measurement is shown in

Figure 25.

Figure 25. The detector source geometry used in beta-particle measurements.

The values of the trigger generation and trapezoidal filter parameters used for DPP in the data acquisition are summarized in Table 5.

TRAPEZOIDAL FILTER TRIGGER GENERATION Parameter Value Parameter Value Decay time 200 µs Trigger threshold 23 LSB Rise time 1.2 µs Smoothing factor 32 Flat top duration 2.5 µs Delay or rise time 0.8 µs Baseline mean 16384 Hold off 1 µs Trapezoid gain 1 Peaking delay 1 µs Peak mean 64 Baseline hold off 0.1 µs Peak hold-off 1.4 µs

Table 5. Values of different parameters used in the acquisition of 14C beta particle energy histogram.

Figure 26. A screenshot of the energy histogram data of 14C.

The response of the Si detector to 14C β-particles can be seen in the screen-shot

(Figure 26) from the acquisition. The data is analyzed offline to present the energy spectrum of the β-particles as shown in Figure 27.

Figure 27. Energy spectrum of beta particles from 14C observed using the Si charged particle detector.

The beta particles from 14C are emitted with a maximum energy of 156.5 keV and an average energy of 49.5 keV, also seen from the energy spectrum. The range of a 156.5 keV beta particle in Si is about 164 µm and the minimum depletion depth of the Si detector used in the measurement is the same. Hence, it follows that the particles deposited their full energy into the Si depletion region and a complete charge collection yielded a spectrum with good energy resolution.

4.2 γ-ray measurements

Similar procedures are followed for the gamma ray measurements, with the 14C beta source now replaced with a 57Co gamma ray source. The detector-source geometry is essentially the same, as shown in Figure 28.

Figure 28. The detector source geometry used in the gamma ray measurements

The DPP parameters were adjusted again to enable a loss-less and smooth acquisition of the gamma ray spectrum and are listed in Table 6.

TRAPEZOIDAL FILTER TRIGGER GENERATION Parameter Value Parameter Value Decay time 200 µs Trigger threshold 35 LSB Rise time 1.2 µs Smoothing factor 32 Flat top duration 2.5 µs Delay or rise time 0.8 µs Baseline mean 16384 Hold off 1 µs Trapezoid gain 1 Peaking delay 1 µs Peak mean 64 Baseline hold off 0.1 µs Peak hold-off 1.4 µs

Table 6. DPP-PHA parameter values used in the measurement and acquisition of 57Co energy histogram data.

Figure 29. A screen shot of the 57Co energy histogram data.

The response of the Si detector to photons from 57Co is shown in the screenshot

(Figure 29) of the acquisition. The gamma ray energy spectrum is analyzed off-line to elaborate the details and is presented in Figure 30.

Figure 30. Energy spectrum of gamma rays from 57Co observed using the same Si charged particle detector.

The spectrum shows a full energy peak corresponding to the 122 keV photons emitted with the highest intensity. Additionally, a less resolved second energy peak

59 around 83 keV is observed. It is interesting to notice that this peak originates from the photons that are back-scattered from aluminum mounting structures inside the vacuum chamber. A simple calculation reveals this information.

It is known from Compton scattering that the energy of the scattered photon is given by,

2 E0mec 2 where the energy of the scattered photon mec 2E0

E0 is the energy of the incident photon

and meis the mass of the electron Compton electron

2 Using the values of 122 keV and 511 keV for E0 and mec respectively, the above equation yields a value of about 82.6 keV for the energy of the back-scattered photon.

A very low background is observed in the output spectrum resulting from a higher value on the trigger threshold, which is set at 35 LSB.

4.3 Mixed β-γ measurement

As discussed earlier, a 10 µCi 14C source was chosen to produce a low energy electron signal in the Si charged particle detector. Two such identical charged particle detectors from ORTEC were employed in this measurement. The photons of energy 122 keV from the 100 µCi 57Co source surrogated the characteristic x-rays. The two sources and the two detectors were placed inside the in-house made vacuum chamber on an

60 aluminum mounting structure. The detector-source geometry is shown in Figure 31, where the vacuum cover was removed to present the instrument.

Figure 31. The experimental setup of two Si detectors viewing two button-sized radioactive sources.

The discrimination scheme of Section 2.6.2 is reproduced by shielding one of the detectors with a polyethylene cap of thickness 350 μm, which fully stops the beta particles from the 14C source (Figure 32).

Figure 32. A visualization of the 156.5 keV fast electrons (14C β particles) penetration in a polyethylene slab of thickness 350 µm obtained using PENELOPE. The range of these electrons in polyethylene is about 302 µm (Salvat, Fernández-Varea, & Sempau, The code 'SHOWER' in PENELOPE-2008: A Code System for Monte Carlo Simulation of Electron and Photon Transport, 2008).

The second detector was left unshielded and was thus responsive to both the beta particles and the photons from the 57Co source. The multichannel digitizer based DAQ system was used for a simultaneous signal acquisition from two independent channels.

The DPP parameters used in this acquisition are the same as those for the beta particle measurements.

A mixed β-γ spectrum was observed from the unshielded detector. A gamma ray- only spectrum was seen from the shielded detector (Figure 33). Distinct from the gamma ray spectrum discussed earlier, the γ-only spectrum shown in Figure 33 included a higher level of noise in the lower energy channels. This can be attributed to the trigger threshold

62 which is set at a relatively lower value. The γ-only spectrum included the energy peak

(~83 keV) from the back-scattered photons, as observed earlier. Furthermore, spectrum subtraction yielded a pure beta-only response, corresponding to the neutron signal from

IC and Auger electrons without the interference from K-X ray.

Figure 33. The spectrum from beta and gamma ray sources, the spectrum from gamma ray source alone and the subtracted spectrum, indicating a detector's response to IC and Auger electrons.

Conclusion and Future Work

The superior thermal neutron cross-section of Gd makes it a capable neutron converter material. A major shortcoming of greater interaction with gamma rays due to the high Z number of Gd, while producing a weak neutron-induced signal in the form of

IC and Auger electrons, is observed. This highlights the need for a gamma ray discrimination capability for the detector with Gd as a converter.

A gamma ray rejection technique for a semiconductor with Gd as the neutron converter is proposed. Two commercial Si-charged particle detectors and a beta particle source and a gamma ray source are chosen to reproduce the scenario when a Gd based semiconductor neutron detector is used in a mixed n-γ field. The measurement results proved the hypothesis of the gamma ray rejection scheme.

The study also provides insight into gamma ray detection with Gd as a converter to transduce high/medium energy gamma rays to low energy K-X rays. Subsequently, the detection of a gamma ray is made possible using a thin-film charged particle semiconductor detector. Although the energy information of gamma rays is unattainable with such a detection scheme, it is sufficient for many application scenarios in which only the intensity of the gamma rays is concerned.

For further research, a capillary plate (an assembly of fine glass tubes) design using

Gd is proposed for neutron detection. As a precursor to this research, a commercial micro-channel plate (MCP) detector is considered; investigation of the response of the

MCP detector to neutrons, gamma rays and the K-X rays from Gd may offer insight into capillary plate (CP) neutron detection. Also, a potential n-γ discrimination technique for the capillary plate neutron detector can be formulated based on this study.

Some of the advantages of using MCP detectors include that they provide high gain, low noise, and good spatial and temporal resolution.

 It was previously discussed that the external gamma rays can activate Gd to emit

K-shell x-rays that cause interference to the weak neutron signal. Hence, it would

be interesting to observe the response of a MCP detector to the K-X rays from Gd.

In this study, a thin Gd foil and a gamma ray source can be used in combination

with the MCP detector. Photons from the gamma ray source ionize Gd atoms,

causing the emission of K-X rays.

 This study also furthers understanding of the magnitude of interference posed by

the K-X rays to the neutron-induced signal when a MCP detector is used in

combination with a Gd foil. This should support research in using a CP detector.

 In order to detect the neutron signal from Gd, a MCP detector can be used in

combination with a thin Gd foil and a thermal neutron source. Although the

primary component of the neutron signal from IC and Auger electrons is only

about 1% of the total reaction energy, high gain (104 – 107) of the channel

multipliers in the detector amplify the neutron induced charge before it is

collected at the output electrode, securing the detection of a weak neutron signal.

This study principally is intended to offer insight into capillary plate neutron detection. By means of a preliminary investigation using an off-the-shelf MCP detector, some foresights into the response of a CP neutron detector to the K-X rays and the conversion electrons can be garnered.

Two different kinds of MCP detectors are considered for the study.

 A single MCP detector with a metal anode read out device; the net charge

generated from electron avalanche inside a channel across the MCP structure is

collected from a single output electrode. This type of readout is suitable for

applications in which only particle detection and counting are of interest.

 A phosphor screen readout is actually needed in image intensifying applications.

However, in the present case, it may complement the experimental scheme with

another signal output in the form of blue light emission. A visible blue light

serves as a direct indicator of detection of a neutron or a gamma ray signal. The

emitted light can be detected by a photomultiplier tube and converted to an

electric current, which can be further processed by readout electronics.

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APPENDIX A: MCNP5 input – Gadolinium prompt-gamma rays

Project - Modeling neutron interaction with Gd and prompt gamma-ray emission c c 0.025 eV thermal neutrons beam is incident onto c a 12 um thin foil made of nat. Gd c c Cell Cards c 500 1 -7.9004 61 -62 66 -65 64 -63 imp:n,p,e = 1 $ Gd thin film 640 2 -2.33 -70 imp:n,p,e = 1 $ Silicon detector1 680 2 -2.33 -75 imp:n,p,e = 1 $ Silicon detector2 700 0 -99 #500 #640 #680 imp:n,p,e = 1 $ void medium c c kill the particles outside region of interest c 999 0 99 imp:n,p,e = 0 $ outside world c c end of cell cards c c c Surface Cards c c Gd foil surfaces c 61 px 5.0000 $ Gd foil x plane 62 px 5.0012 $ Gd foil x plane 63 pz 1 $ Gd foil upper z plane 64 pz -1 $ Gd foil lower z plane 65 py 1.0 $ Gd foil upper-y plane 66 py -1.0 $ Gd foil lower-y plane c c silicon detector surfaces c 70 1 RCC 0 -0.5 0 0 0.05 0 1 $ Si detector1 75 RCC 6 0 0 0.05 0 0 1 $ Si detector2 c c outside world

70 c 99 so 70 $ Outside world c c end of surface cards c c c Data cards c mode n p e $ neutrons, photons and electrons ctme 15 $ limit run time phys:p 100 0 0 0 0 $ photon physics phys:e 100 0 0 0 0 1 1 1 1 0 $ electron physics *TR1 2.5 3.5 0 45 45 90 135 45 90 $ coords transformation c c source definition and description c sdef erg=0.025e-6 par=1 pos=0 0 0 axs=1 0 0 ara=3.14159 ext=0 dir=1 rad=d1 vec= 1 0 0 $ disk source si1 0 1 $ radius sampling limits sp1 -21 1 $ sampling weights for radius c sc1 Maxwellian energy distribution c sp1 -2 0.5 $ continous thermal spectrum c si1 h 1.00E-12 1.00E-11 5.00E-11 1.00E-10 2.00E-10 c 5.00E-10 1.00E-9 2.00E-9 5.00E-9 1.00E-8 c 2.50E-8 5.00E-8 1.00E-7 1.50E-7 2.00E-7 c 2.50E-7 5.00E-7 c sp1 d 0 1.520E-01 4.518E+00 2.819E+01 1.124E+02 c 6.072E+02 2.744E+03 1.065E+04 5.353E+04 2.095E+05 c 7.644E+05 1.577E+06 1.408E+06 5.292E+05 1.404E+05 c 3.140E+04 2.162E+02 c c Material Definitions c m1 64152.70c 0.0020 $ natural Gd 64154.70c 0.0218 64155.70c 0.1480 64156.70c 0.2047 64157.70c 0.1565 64158.70c 0.2484 64160.70c 0.2186 m2 14000 1.0000 $ Silicon c c tallies for photons c c photons escaping from Gd surfaces

71 c f2:p 61 62 63 64 65 66 T $ Gd foil surfaces e2 1e-5 1e-3 7999i 8.0 c c photon fluences in Si detectors c f4:p 640 680 $ Si detector volume e4 1e-5 1e-3 7999i 8.0 c

APPENDIX B: MCNP5 input - Gadolinium K-X rays

Project - Interaction of Photons with Gadolinium, Gd (Z=64) c Si detector active area - 300 mm2 (radius = 0.977 cm) c Si detector minimum depletion depth is 164 um c c Cell Cards c 100 1 -7.9004 -100 $ Gd thin film 200 2 -2.33 -200 $ Si Detector1 165 um 300 2 -2.33 -300 $ Si Detector2 200 um c the vacuum chamber 400 3 -2.7 -420 400 $ the Al cylinder 420 0 -400 #100 #200 #300 $ vacuum inside c air(ambience) outside the chamber 500 4 -1.205e-3 -900 420 $ air outside c defining problem boundary 900 0 900 $ outside world c c end of cell cards c c c Surface Cards c 100 1 RPP -1 1 -0.0006 0.0006 -1 1 $ Gd target thin film 12 um c detectors 200 RCC 10 15 0 0 0.0165 0 0.977 $ fluence in Si Detector - 165 um 300 RCC 10 5 0 0 0.02 0 0.977 $ pulse-height Si Detector - 200 um c vacuum chamber 400 RCC 5 0 0 0 30.48 0 15.24 $ inner cylinder 420 RCC 5 -0.5 0 0 31.48 0 16.1925 $ outer cylinder c problem boundary 900 SO 100 $ air outside the vacuum chamber c c end of surface cards c c c Data Cards

73 c mode p e $ photons and electrons ctme 120 $ limiting the run time phys:p 100 0 0 0 0 $ energy cutoff photon physics phys:e 100 0 1 1 0 1 1 1 1 0 $ full electron physics *TR1 10 10 0 45 45 90 135 45 90 $ coordinate transformation c c source definition and description c A photon disk source emitting 500 keV photons sdef pos=0 10 0 axs=1 0 0 ext=0 rad=d1 par=2 erg=0.5 vec=1 0 0 dir=1 c si1 0 1 $ radial sampling range: 0 to Rmax (=1cm) sp1 -21 1 $ radial sampling weighting: r^1 for disk imp:p,e 1 1 1 1 1 1 0 $ coupled photon and electron transport c c Material Definitions c m1 64000 1.0 $ Gadolinium m2 14000 1.0 $ Silicon m3 13000 1.0 $ Aluminum m4 07014 -0.7552 $ Air 08016 -0.2319 18000 -0.0129 c c tallies for photons f4:p 200 300 $ photon flux spectrum in silicon detectors e4 0.00 509i 0.51 $ energy bin structure c c pulse height tally - detector response c f8:p 200 300 $ pulse height distribution in silicon detectors e8 0.00 1e-5 508i 0.51 $ energy bin structure c c energy deposition tally to model only the energy deposition in a material c *f18:p 200 300 $ energy deposition in Si detectors e18 0.00 1e-5 508i 0.51 $ energy bin structure c c print c

APPENDIX C: Gamma interaction cross-section for gadolinium

1. K-X ray fluorescence yields and the cross-section of photons for interaction with Gd.

• The cross-section of photon interaction for x-ray fluorescence yields were

calculated using

σKα= σK(E).ωK.fKα

σKβ= σK(E).ωK.fKβ

where σK(E) is the K-shell photo-ionization cross-section for the given element at

the photon excitation energy E, ωK is the K-shell fluorescence yield.

• fKα and fKβ are fractional x-ray emission rates for Kα and Kβ x-rays, defined as

below:

-1 fKα = (1+Ikβ/Ikα)

-1 fKβ = (1+ Ikα/Ikβ)

Ikβ/Ikα is the ratio of Kβ to Kα x-ray emission rates.

• Using the values of 0.932, 8.1836 barns per atom and 0.2426 for ωK , σK(E) and

Ikβ/Ikα respectively, yielded the predicted cross-section for Gd, for K-X ray

production after a 500 keV photon absorption, as below.

APPENDIX D: Pulse processing parameters

SpA – 2011) provides a description of some general parameters, parameters corresponding to the trigger and timing filter and the trapezoidal energy filter used in data acquisition with DPP-PHA Control Software.

General Settings: The following general parameters can be set to each individual acquisition channel.

 DC Offset: sets the value of the DC Offset applied to the channel, expressed as

the percentage of the Full Scale Range. Allowed values are: -50% (Full negative)

to 50% (Full Positive).

 Pulse Polarity: selects the polarity of the input signal to be processed by the

DPP-PHA algorithm. As the digital pulse height analyzer (DPHA) works properly

with positive input pulses, a polarity inversion (by setting NEGATIVE) is needed

to turn a negative input signal into positive.

 Input Digital Gain: multiplies the value of the samples coming out from the

ADC channel by a constant value. If used in combination with the Decimation

parameter, the Input Digital Gain provides an improvement in resolution. The

allowed values for the input digital gain parameter are: 1, 2, 4 and 8.

 Decimation: selects the value of parameter D to be used, i.e. the number of

samples to be averaged before the sampled signal is analyzed by the algorithm.

An important effect of decimation is to extend the range of permitted values for

the time parameters (e.g. the trapezoid rise time). The allowed values are: 1, 2, 4

and 8.

Trigger and Timing Filter: The parameters corresponding to the trigger and timing filter (RC- CR2) are:

 Threshold (basic configuration): sets the parameter thr which is the threshold

for the board self-triggering. The value is expressed in LSB. The value in

millivolts (mV) for 1 LSB can be calculated according to the board input signal

range (0.5 V, 2.25 V or 10V). For a board with 14-bit resolution and an input

range of 2.25 Volts, the value of LSB is 2.25 / 2 = 0.137 mV.

 Smoothing Factor (advanced configuration): sets the number of samples

(parameter a) to be used in the moving window of a low pass filter which is the

integrative component (RC) contained in the trigger-and-timing filter and filtering

the input signal in order to reduce the high frequency noise. Allowed values for

the parameter a are 1, 2, 4, 8, 16 and 32.

 Delay (advanced configuration): sets the parameter b used in the derivative

component of the trigger-and-timing filter (CR2) in order to maximize its

amplitude with respect to the input signal. The best way to find the optimum

setting is to start from a value equal to the rise time of the input signal and then,

looking at the RC-CR2 signal on the plot, increase b until the signal reaches the

maximum amplitude.

 Hold off (advanced configuration): sets the minimum time interval that must

exist between two consecutive triggers. Triggers that occur within this Holdoff

window are rejected. The value of this parameter (trgho) is expressed in μs.

Trapezoidal energy filter: The parameters corresponding to the trapezoidal energy filter, used in the software are as follows

 Decay Time (basic configuration): sets the exponential decay time constant M

of the input pulses. Setting M parameter is like to calibrate the pole-zero

cancellation in a traditional Shaping Amplifier. The value of M is expressed in μs.

 Rise Time (basic configuration): sets the parameter k, being the rise and fall

time of the trapezoid, expressed in μs. Setting this parameter is like to change the

shaping time constant of the traditional spectroscopy Amplifier. Higher values of

k give a better signal to noise ratio, but increase the probability of pile-up. The

user should find the best compromise between the overall resolution of the energy

calculation and the dead time (ratio between number of pulses converted to the

total number of input pulses).

 Flat Top (basic configuration): sets the parameter m, i.e. the width of the

trapezoid signal flat top, expressed in μs. Like the parameter k, m has an influence

on the signal to noise ratio and on the efficiency. Moreover, its value should be

set long enough in order to contain the ballistic deficit.

 Baseline Mean (basic configuration): sets the nsbl parameter which is the

number of samples in the moving average filter window to calculate the baseline.

The output signal of the trapezoidal filter has a baseline depending on the DC

offset and on the trapezoid parameters. This baseline is also affected by low

frequency fluctuations usually due to the ground loops (50 or 60 Hz noise),

temperature variation and other slow components such as the microphonic noise.

In order to obtain a reliable baseline value as reference for the trapezoid peak

calculation, a moving average filter is applied to the baseline signal. the nsbl

allowed values are 0, 16, 64, 256, 1024, 4096, 16384.

 Peaking Delay (advanced configuration): defines the point on the flat top of the

trapezoid signal and is referred to the start of the flat top, where the peak

calculation is started and the value is expressed in μs. Due to the ballistic deficit

typical of particle detectors, the trapezoid flat top doesn’t start exactly after its rise

time, according to the theory, but shows a round shaped knee. Therefore, it is

necessary to delay the peaking window and bring it into the flat part of the top.

 Peak Mean (advanced configuration): sets the parameter Nspk which is the

number of samples to be averaged for the calculation of the trapezoidal height.

Allowed values are 1, 4, 16 and 64.

 Baseline Hold off (advanced configuration): sets the baseline hold off extension

parameter (blhoe) and so the time interval of the baseline calculation which is

otherwise inhibited from the start to the end of the trapezoid. The value of this

time interval (i.e. the baseline holdoff) which is by default around the flat top

duration plus twice the rise time (with blhoe = 0), can be extended by means of

the blhoe parameter. The value is expressed in μs.

 Peak Hold off (advanced configuration): sets the peak hold off extension

parameter (pkhoe), so that the time interval between two trapezoids for the peak

measurement can be calculated correctly. Theoretically the minimum interval of

time is rise time + flat Top (with pkhoe = 0). This GUI parameter allows the user

to extend this interval. Two consecutive peaking within this time interval causes

the second to be rejected.