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Modeled Martian Subsurface Elemental Composition Measurements with the Probing In situ with Neutrons and Gamma-ray (PING) Instrument

Suzanne F. Nowickia, Larry G. Evansb, Richard D. Starrc, Jeffrey S. Schweitzerd, Suniti Karunatillakee, Timothy P. McClanahanf, Jeffrey E. Moerschg, Ann M. Parsonsf, Christopher G. Tateh

a

Los Alamos National Laboratory, Los Alamos, NM 87544, USA

b

c

Computer Sciences Corporation, Lanham-Seabrook, MD 20706, USA

The Catholic University of America, Washington, DC 20064, USA

d

Department of Physics, University of Connecticut, Storrs, CT 06269, USA

e

Department of Geology & Geophysics, Louisiana State University, Baton Rouge, LA 70803,

USA f

NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA

g

Department of Earth and Planetary Sciences, University of Tennessee, Knoxville, TN 37996,

USA h

Department of Physics and Astronomy, University of Tennessee, Knoxville, TN 37996,

USA

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/2016EA000162 This article is protected by copyright. All rights reserved.

Abstract:

The Probing In situ with Neutrons and Gamma rays (PING) instrument is an innovative application of active neutron-induced gamma-ray technology. The objective of PING is to measure the elemental composition of the Martian regolith. As part 2 of a two-part submission, this manuscript presents PING’s sensitivities as a function of the Martian regolith depth and PING’s uncertainties in the measurements as a function of observation time in passive and active mode. Part 1 of our submission models the associated regolith types. The modeled sensitivities show that in PING’s active mode, where both a Pulsed Neutron Generator (PNG) and a Gamma-Ray Spectrometer (GRS) are used, PING can interrogate the material below the rover to about 20 cm due to the penetrating nature of the high-energy neutrons and the resulting secondary gamma rays observed with the GRS. PING is capable of identifying most major and minor rock-forming elements, including H, O, Na, Mn, Mg, Al, Si, P, S, Cl, Cr, K, Ca, Ti, Fe and Th. The modeled uncertainties show that PING’s use of a PNG reduces the required observation times by an order of magnitude over a passive operating mode where the PNG is turned off. While the active mode allows for more complete elemental inventories with higher sensitivity, the gamma-ray signatures of some elements are strong enough to detect in passive mode. We show that PING can detect changes in key marker elements and make thermal neutron measurements in about 1 minute that are sensitive to H and Cl.

This article is protected by copyright. All rights reserved.

1. Introduction:

The Probing In situ with Neutrons and Gamma rays (PING) instrument is an innovative application of active neutron-induced gamma-ray technology for planetary science. The objective of this technology development program at NASA Goddard Space Flight Center (NASA/GSFC) is to develop the PING instrument to the point where it can operate on a rover on Mars to measure the Martian subsurface bulk elemental composition at different locations. PING consists of a Pulsed Neutron Generator (PNG) and a Gamma-Ray Spectrometer (GRS) to perform geochemical analysis of planets or solid bodies such as asteroids. Many missions have flown gamma-ray spectrometers, however, no landed missions flown by the Unites States have included a GRS (excluding NEAR which did put a GRS on the surface of an asteroid, but this was serendipitous and not part of the mission design (Evans et al., 2011)). Soviet Venera missions (8, 9, and10) did include a GRS, but could only measure natural radioactivity. The only planetary mission to date that has a pulsed neutron generator is the Russian Dynamic Albedo of Neutrons (DAN) experiment on the Mars Curiosity rover, but it has only neutron detectors. The PING experiment described here would be the first planetary instrument to include both PNG and GRS, thus taking full advantage of this innovative technology. By actively generating 14.1 MeV neutrons with a deuterium-tritium PNG, PING can interrogate the regolith directly under a MSL-like rover. The PING GRS can detect the emission of the resulting characteristic gamma rays that are analyzed by ground processing systems to yield bulk elemental composition and layering information. In its active mode (PNG on), PING can make composition measurements at rates that are orders of magnitude faster than by passive detection (PNG off). The Pulsed Neutron Generator-Gamma Ray and Neutron Detectors (PNG-GRAND) experiment, which was an early version of PING, was


conducted at NASA Goddard’s Geophysical and Astronomical Observatory (GGAO) (Parsons et al., 2011). A 14.1 MeV Pulsed Neutron Generator (PNG) and a LaBr3 gamma-ray detector, which are the components modeled in this paper however with different dimensions, were placed on top of a large granite monument and showed that this technology has the capability to detect the presence of materials beneath the surface of the material the instrument was resting on (Parsons et al., 2011). By probing below the Martian surface, PING can: 1) identify the locations that are most promising for follow-up measurements and possible collection of samples into a returnable cache for future return to Earth, 2) characterize the processes that formed and modified the geologic record by observing the preserved geochemical signatures of these processes and environments, and 3) provide insight into the possible habitability of ancient Martian environments. PING is capable of uniquely identifying and assessing the abundance of most major and minor rock-forming elements, including H, C, O, Na, Mg, Al, Si, P, S, Cl, K, Ca, Ti, Fe, Th, and U. While DAN also has a PNG, it is primarily sensitive to the presence of hydrogen, and the confounding effects of high absorption cross section elements (notably Cl and Fe) must be taken into account in model-based analyses. By contrast, PING takes advantage of the fact that every element has a unique gamma ray signature, consisting of one or more emission lines at specific energies. PING has the ability to measure context-scale bulk elemental composition, including key elements such as C, H, O, P, and S that are considered essential to Earth-analog life and aqueous processes. PING’s sensitivity to buried compositions has high scientific value because dust and mantling material may conceal key small scale outcrops or buried lithic fragments indicative of habitable environments, such as buried deposits or veins of aqueous minerals.


Consequently, PING provides detailed insight into the nature of the Martian near subsurface, particularly in understanding the bulk geochemical context for cored and cached samples. Techniques employed for geochemical analysis of the regolith using remote sensing gamma-ray measurements can be found in Evans et al., (2007) and Boynton et al., (2007). This paper presents the modeled in situ sensitivities and uncertainties of the PING instrument in passive and active mode for the Martian surface. This paper presents the sensitivity of the instrument as a function of depth and the improvement of the measurement uncertainties as a function of time. Part 1 by Karunatillake et al., entitled “Models and Analysis of the Regolith for Gamma-Ray and Neutron Measurements on Mars: Part 1,” develops the underlying regolith models, which we refer to henceforth as Karunatillake et al., 2015, submitted.

2. Description of PING

2.1 Physics processes

As illustrated in Figure 1, when the surface of Mars is bombarded with 14.1 MeV neutrons from the PING PNG, reactions with the nuclei in the soil such as inelastic scattering and neutron capture produce gamma rays that are detected with the PING GRS. Other processes such as delayed neutron activation and natural radioactive decay also cause the material to emit gamma rays that are detected by the GRS. The energy of these gamma rays is characteristic of both the process and the isotope with which the neutrons have interacted. The intensity of the gamma rays produced by these nuclear reactions is proportional to both the concentration of the elements and the incident flux of neutrons that caused the nuclear reactions. Therefore, the GRS measurement of the gamma-ray energies indicates which elements are present and their spectral line intensities provide the abundances of the specific


elements. These nuclear gamma rays are sufficiently energetic to be highly penetrating, setting the PING probing depth to about 20 cm below the surface.

The likelihood of a thermal neutron capture event increases with decreasing neutron energy. The time at which a neutron capture gamma ray is emitted depends on the time it takes the neutron to undergo enough collisions to reach a sufficiently low energy to be captured. In contrast, since inelastic neutron scattering requires the neutron to have higher energy than the reaction threshold in the nucleus (1–6 MeV), inelastic scattering events occur before the incident 14.1 MeV neutrons lose most of their energy. Thus the emitted gammaray lines from inelastic scattering are produced early in the PNG pulse period, on average a few picoseconds after the emission of the 14.1 MeV neutron from the PNG. Characteristic gamma-ray lines resulting from thermal or epithermal neutron capture appear at a later time, mostly between PNG pulses. The naturally occurring radioactive elements K, Th, and U emit characteristic gamma-ray lines from radioactive decay without PNG neutron stimulation. Thus the gamma ray emission rate from these naturally radioactive elements is constant and independent of the PNG pulse period. The control of the pulsing of the PNG and the acquisition of gamma-ray spectra at different times during a neutron pulse period allows us to obtain a gamma ray spectrum during the neutron burst that is largely free of capture and delayed activation lines. We will refer to this time window as the “inelastic scattering window”. Similarly, after the PNG neutron burst we can collect spectra that are largely free of gamma rays produced by inelastic reactions and delayed activation. We will refer to this time window as the “capture window”. Figure 2 illustrates these two time windows and the gamma-ray spectra that are acquired by the GRS during these times. This time gating procedure permits the direct acquisition of spectra with much lower noise background from gamma rays produced by unwanted


reactions. The reduced noise produces results with better precision than would be obtained from a time-independent spectrum accumulation. Also included in Figure 2 are the “delayed activation + natural radioactivity” window (largely free of inelastic and capture reactions). Natural radioactivity is independent of the neutron generator and is constant over time. The gamma rays produced from delayed activation vary with time, but at any time, or integrated over time, the counts in the “delayed activation + natural radioactivity” window are directly related to the counts of these peaks present in the other windows. Since the lifetime of the delayed activity (not to mention the “natural” radioactivity) is much greater than period of neutron bursts, the count rates from these gamma rays in the inelastic and thermal neutron capture windows, even though it is difficult to see them, are the same as in the delayed activation + natural activity window, and they can be reliably subtracted from the first windows and reduce the “background” in those windows for the analysis. This third window, “delayed activation + natural radioactivity” is subtracted from the “inelastic scattering window” and the “capture window” in order to further reduce the background from unwanted reactions. The sensitivities for element detection by the PING instrument were demonstrated using the gamma-ray line spectra in both the inelastic scattering and the capture windows.

Experiments using optimized time windows as described above were performed at NASA GGAO using a 14.1 MeV PNG, an HPGe gamma-ray detector and a He-3 neutron detector on a large basalt monument (Bodnarik et al., 2013). The PNG pulsing scheme with 100 µs pulse width and 1000 µs pulse period was chosen to be applicable to a variety of material compositions that PING might encounter on Mars. The gamma ray data acquisition time windows were chosen with reference to this pulsing scheme. The inelastic neutron scattering window was chosen to start after the PNG pulse had achieved a constant output rate of 14 MeV neutrons as indicated by a constant total gamma ray count rate in the detector.


The end of the inelastic window coincides with the end of the PNG neutron pulse. The beginning of the neutron capture window occurs 50 µs after the PNG pulse ends to allow enough time for the fast neutrons in the material to thermalize to lower than epithermal neutron energies so that thermal neutron capture events can begin to occur. At the end of the neutron capture window, the capture gamma ray rate is sufficiently low to allow the measurement of gamma rays from delayed activation and natural radioactivity. The results from the analysis of the gamma-ray spectra acquired by the HPGe detector showed that the optimization of the time windows reduces the background and the separation of gamma-ray spectra by nuclear processes improves the overall gamma-ray line measurement precision (Bodnarik et al., 2013).

2.2 The Pulsed Neutron Generator (PNG)

The PNG emits energetic 14.1 MeV neutrons isotropically at an intensity of 1x108 neutrons per second. It can generate neutron pulses over a wide range of pulse widths (from a few microseconds wide to continuous production) and with substantial flexibility in pulse frequency (typically 1-10 kHz). PNGs have been used for decades in the harsh environment of oil well logging, the practice of making a detailed depth record of the geologic formations encountered down an oil well borehole. The technology used in this industry is proven to be extremely rugged. A great advantage of a PNG compared to neutron-emitting radioactive sources is that it can be turned off so it emits no radiation when it is not operating.

2.3 The Gamma Ray Spectrometer (GRS)


The PING GRS consists of a cylindrical (6.35 cm diameter, 7.6 cm long) ceriumdoped lanthanum bromide (LaBr3:Ce) scintillator wrapped in a 1 mm Cd metal thermal neutron shield and mounted on a photomultiplier tube (PMT). The Cd shield prevents thermal neutrons from reaching the scintillator. Gamma rays produced in the Cd shield can be detected by the GRS to measure the thermal neutron flux incident on the gamma-ray spectrometer without the need for a separate neutron detector. Detector sensitivity depends directly on its volume, its efficiency for stopping incident photons and its energy resolution. LaBr3 scores well for all of these characteristics. Scintillation spectrometers have been used in gamma-ray instruments flown on numerous orbital planetary missions since Apollo 15 and 16 (Bielefeld et al., 1976). Lanthanum halide detectors, such as the LaBr3 detector selected for PING, have the best energy resolution of all scintillators. PING’s LaBr3 GRS has an energy resolution of about 3% FWHM at 662 keV, and its high Z (La=57, Br=35) and high density (5.29 g/cm3) provide good stopping power for high efficiency. Saint-Gobain Crystals reports that the decay time of the light from LaBr3 is 16 ns (Saint-Gobain Crystals, 2009), an order of magnitude faster than most other scintillators. A fast light decay time makes very high counting rates possible, which is an important characteristic for a detector used with a PNG. LaBr3’s intrinsic radioactivity from 138

La and 227Ac contributes to the background in the energy range ~1.4 - 2.7 MeV. Because of

long half-lives, this background component can be well characterized. With a high precision measurement performed as part of the instrument calibration before launch, the intrinsic background can be subtracted from the gamma-ray spectra without substantial increase in elemental uncertainties. Figure 3 shows the background measurement of a 2” x 3” detector placed inside a 4+” thick Pb enclosure. The lifetime for the measurement was 612213.87 seconds (= 7.1 days).


The data are adjusted to a 6.35 cm diameter × 7.6 cm long detector, which is what was modeled.

3. MCNPX modeling and results

3.1 Description of the model

3.1.1 Instrument and rover

Gamma rays emitted from a planetary surface are the result of both radioactive decay and the neutron interactions described in Section 2. The neutrons that produce the gamma rays on Mars come from three different sources: the PNG, the rover’s Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) and natural Galactic Cosmic Rays (GCR). The standard analysis technique to calculate the resulting gamma-ray flux that escapes from the Mars surface is to use Monte Carlo calculations to model the input neutron spectrum from these sources, the layering structure of the planet and the PING instrument. PING’s expected sensitivities for prompt gamma rays are based on model calculations using the Monte Carlo N-Particle eXtended (MCNPX) radiation transport code (Pelowitz, 2005; McKinney et al., 2006; Evans et al., 2012). This code has been used often to determine what may be detected from planetary measurements before instruments have even been sent for initial measurements (Jun et al., 2011). Sensitivities were calculated for the active mode (e.g. PNG neutron source is on) and for the passive mode (e.g. PNG neutron source is off). Model calculations for PING active measurements assume a neutron point source with an energy of 14.1 MeV emitted isotropically, a pulse width of 100 μs, pulse period of 1000 μs, and 1×108 neutrons per second


yielding 105 neutrons per pulse. The LaBr3 detector was modeled as a cylinder wrapped with a 1 mm thick Cd foil. The dimensions of the LaBr3 detector are given in Section 2.2. Passive measurements, other than for the radioactive nuclides (K, Th, U), depend on the GCR spectrum (McKinney et al., 2006) and the spectrum of neutrons from the MMRTG (Jun et al., 2013). In all cases, the Martian atmosphere and an MSL/Curiosity rover model (Jun et al., 2013) were part of the calculations, contributing to the gamma-ray signal. The position of the PING neutron generator and detector used in the model are mounted on the rear body of the rover on either side of the MMRTG. The PNG is separated from the GRS by 100 cm and they both are fixed at 80 cm above the Martian surface. The geometry of the model can be seen in Figure 1 and Figure 4.

3.1.2 Regolith

A great diversity of regolith types may well exist on Mars as evident from the regolith contrast across and within different sites such as Meridiani Planum and Gale Crater. However, to study the sensitivity of the PING instrument to the regolith of Mars, we decided to model a simple composition of layers, as discussed in Part 1 by Karunatillake et al. (2015, submitted). The models of the regolith include a monolayer and a dual-layer of Mars regolith, with dimensions that are large compared to the size of the instrument and the rover. Despite the likely compositional diversity of the Martian regolith, some global or at least regional consistencies are also possible as highlighted in Karunatillake et al. (2015, submitted). Accordingly, our monolayer model uses the most recent in situ homogeneous basaltic soil compositions (Blake et al., 2013). In our dual-layer model, the upper layer is always modeled as a layer of this homogeneous Martian basaltic soil (Blake et al., 2013) and varies from 5 to 20 cm in depth. Several compositions were modeled as the lower layer with a large depth


compared to the size of the instrument and the rover. Table 1 lists the derived composition of each regolith type, including the upper Martian basaltic soil layer. We discuss the motivation, justification, and derivation of each regolith type in Part 1 by Karunatillake et al. (2015).

3.2 Results

3.2.1 Depth sensitivities

3.2.1.1 Method

The processes by which the PNG neutrons interact with the regolith to produce the gamma rays measured by the gamma-ray spectrometer are too complex for the spectrum to be derived analytically. The PNG emits 14.1 MeV neutrons isotropically. Some of the fast neutrons that penetrate the regolith produce secondary gamma rays, as explained in section 2.1. These gamma rays are emitted in all directions, but some of them will be headed towards the gamma-ray detector. After passing through the gamma ray-absorbing regolith and atmosphere, some of these characteristic gamma rays will intercept the detector. Some of the neutrons emitted by the PNG also interact with the material surrounding the detector, such as the rover and result in the production of additional secondary gamma rays. Some of these gamma rays will also reach the detector. Finally only some of the gamma rays that intercept the detector are going to interact in the detector and be recorded in the gamma-ray spectrum. A Monte Carlo computer simulation tracks each neutron and secondary gamma ray, simulating all relevant physical processes such as elastic and inelastic neutron scattering, neutron capture, and gamma-ray photoelectric absorption, Compton scattering and pair production. The MCNPX Monte Carlo tool was used to calculate the energy spectrum of


gamma rays impinging on the surface of the PING gamma-ray spectrometer. Typically, a total of 2×1010 PNG neutrons were simulated so that the statistics of the generated gammaray spectrum were adequate to calculate elemental abundances to sufficiently low uncertainty. This simulated spectrum was then passed through the response of the gamma-ray spectrometer producing a second simulated spectrum that takes into account the effective area (efficiency and surface area) of the detector. It is this detector output spectrum that is used (below) to determine instrument sensitivities. Natural radioactivity gamma-ray fluxes were determined from Mars Odyssey Gamma Ray Spectrometer orbital measurements and scaled to the surface and to the difference between the Mars values and the model compositions. Boynton et al. (2004) explain how a forward calculation is used to determine elemental abundances on the surface of Mars. In the case of the radioactive elements this means simply folding photon fluxes for assumed elemental abundances through atmospheric attenuation and detector response functions to match measured detector count rates. Count rates for surface abundances of K, Th, and U on the Martian surface derived from the forward calculation are then simply scaled by the elemental ratio of the model compositions. In practice, due to the energy resolution of the proposed LaBr3 GRS, the relative elemental abundances will be extracted from the PING data using the full spectrum fitting technique (Radtke et al., 2012). Using this technique the full spectrum response of the PING detector to each element in isolation will be determined through experiment and Monte Carlo simulation. The sum of the detector response functions for each individual element will then be fit to the PING data to determine the abundance of each element present. An advantage of this technique is that it makes use of the photon counts that end up anywhere in the energy spectrum, not just the photopeak. For these simulations, elemental abundances and uncertainties were determined from the spectral lines in the simulated spectrum.


3.2.1.2 Active mode

Identification and quantification of elements such as S, H, and Cl are key to finding areas of aqueous alteration and potential ancient habitats below the surface of Mars, both important NASA goals. Each of these elements produces strong neutron capture gamma-ray lines that stand out in our simulations. Element ratios to Si are used in our analysis for two reasons: 1) two factors which would otherwise add to the systematic uncertainties of the measurements cancel out: neutrons per pulse which may change with time, and changes in the neutron distribution due to the varying abundance of strong neutron absorbing elements which would have a large impact on count rates, and 2) Si abundance on Mars varies little and is well known (Boynton et al., 2007). Figures 5a and 5b show the gamma-ray count rate ratio of S/Si vs. H/Si and Cl/Si vs. H/Si for the mono- and dual-layer models. Neutroncapture lines for Si (3539 keV), H (2223 keV), S (5420 keV) and Cl (1951, 1959, 6111, 6620, 6628, and 7414 keV) were used. Hydrogen abundance and distribution can have a dramatic effect on the count rates of capture gamma-ray lines from other elements. For these reasons we plot S/Si and Cl/Si vs. H/Si. The figures show that the curve for each dual-layer model converges to the monolayer model when the thickness of the upper layer, the homogeneous Martian basaltic composition, is greater than 20 cm. The thicker this layer is, the greater the absorption of gamma rays. When this upper basaltic layer is greater than 20 cm, most of the gamma rays coming from the lower layer have been absorbed so that there are not enough gamma rays reaching the detector to identify the lower layer from the upper layer. As the energy of the gamma rays increases, the absorption decreases. The limit of detection is therefore energy dependent. From Figures 5a and 5b, we estimate PING’s limit of detection to be about 20 cm for the Martian compositions modeled.


In Figure 5a, the Opaline Silica regolith composition is much lower in S than any of the other compositions, including the Basalt top layer (see Table 1). As a result, the S/Si ratio decreases as the buried Opaline Silica layer gets closer to the surface. For the other model compositions S is higher than in the Basalt, and S/Si increases.


3.2.1.3 Passive mode

3.2.1.3.1 Gamma-ray measurements

Figures 6a and 6b compare the depth sensitivity of our instrument between the passive (MMRTG only) and active modes by plotting the gamma-ray count rate ratio of S/Si vs. H/Si and Cl/Si vs. H/Si in a 10-min counting measurement. In active mode, the PNG provides the capability to probe below the subsurface of the soil because of the high flux and high energy (14.1 MeV) of the neutrons. When using the S/Si vs. H/Si measurements in passive mode, the limit of detection depth of the instrument is reduced. Figure 6a shows that when the layer of Martian basaltic composition is greater than 5 cm, there are not enough gamma rays reaching the detector to identify the lower layer from the upper layer. On the contrary, when using the Cl/Si vs. H/Si measurement in passive mode, Figure 6b shows that the instrument is sensitive to depths greater than 20 cm. Given the thermal neutron capture cross sections, the number of gamma rays produced from the capture of thermal neutrons and the abundance in sulfate bedrock of Cl and S (Table 1), there is about 10 times more gamma rays produced from thermal neutron capture in Cl than in S in sulfate bedrock. Table 2 provides the thermal neutron cross sections for Cl and S and their isotopes and Table 3 provides the intensity of the gamma rays from the capture of thermal neutrons as a function of the energy used in this study for both

35

Cl and 32S. However, in the passive mode, due to the smaller flux from the

MMRTG (an order of magnitude lower than the PNG, e.g 1×107 n/s (Jun et al., 2013)), the uncertainties for S, Si, Cl and H are higher in the passive than in the active measurements, which restrict the ability to get significantly measureable sensitivity in the same amount of measurement time.


3.2.1.3.2 Neutron measurements

Thermal neutron measurements are useful to detect changes in H content in passive mode when the rover is moving. Although PING’s sensitivity is reduced in passive mode using gamma-ray measurements, the subsurface thermal neutron flux produced by the MMRTG does provide a sensitive measure of elements such as H and Cl. Thermal neutron measurements alone cannot constrain values of both Cl and H simultaneously. However, the GRS will provide a measure of Cl that, combined with the thermal neutron measurements, will make it possible to quantify both of these elemental abundances. Because H is so efficient at thermalizing neutrons, higher H abundance produces higher thermal neutron fluxes, while higher Cl abundance reduces the thermal neutron flux because of its high capture cross section. Thermal neutrons escaping the surface are detected by their interaction in the Cd foil surrounding the PING GRS. When a neutron is captured by 113

Cd, photons are generated. It is therefore possible to make an indirect measurement of the

neutrons by detecting these photons. Figure 7 shows the rate of gamma ray counts generated in the LaBr3 detector resulting from thermal neutron capture in the Cd foil that surrounds it. This count rate is for the detection of the primary Cd line at 558 keV by the PING GRS with PING in its passive mode. Figure 7 shows that in passive mode, PING can make thermal neutron measurements in about 1 minute that are sensitive to mostly H, but also Cl. Our modeling of passive measurements shows background in this energy region is no more than about 100 counts/min, well below the Cd gamma-ray counts due to the neutron interactions in the GRS shield.

3.2.2 Rover contribution


The response of the detector was simulated using a MCNPX F8 pulse-height tally. This tally provides the energy distribution of pulses created in the detector by the gamma rays and includes characteristic x-rays, Compton scattering effect as well as double and single escape peak effect from pair production (Pelowitz, 2005). The intrinsic background of the LaBr3 detector was not included in the simulation. Section 2.3 describes the intrinsic background of LaBr3 detectors and the method to subtract it from the measurements. Figure 8 compares the gamma-ray spectrum in the LaBr3 detector when the rover is present and when it is not for the monolayer model (Martian basalt). The neutron source is on for 100 μs and the accumulation time is 150 μs after the neutron source is turned off. The main gamma peaks were identified and labeled in Figure 8. The difference between the two gamma-ray spectra is attributed to three factors: 1)

Elements such as Al and H are present in the composition of the rover and produce a

strong neutron capture gamma-ray line as identified in Figure 8. 2)

The materials that make up the rover also moderate the high-energy neutrons and

consequently change the intensity and the energy distribution of the neutrons that interact with the matter. 3)

Gamma-ray interactions in the rover result in changes to the spectrum in two ways.

Compton scattered gamma rays from the rover will contribute to the Compton continuum in the spectrum. Gamma rays that undergo pair production in the rover create two 511 keV gamma rays at 180° each. The interaction of one of the 511-keV gamma ray with the LaBr3 detector causes the number of counts in the 511 keV peak to increase by a factor of 1.4 when the rover is present.

PING’s LaBr3 GRS has an energy resolution of about 3% FWHM at 662 keV. The limited energy resolution of the LaBr3 detector can be seen in Figure 8. It shows that peaks


that are located to close to each other cannot be distinguished. A good example seen in Figure 8 is the doublet Fe peaks at 7631 and 7645 keV.

3.2.3 Uncertainties

3.2.3.1 Method

The simulated gamma-ray spectra were analyzed with standard peak fitting software (Evans, et al., 2007, 2012). The relative uncertainties in the results were a function of the statistical uncertainty and the goodness of the fit to the data. The net area for a peak Pn is the total counts Pt under the peak less the background counts B, so that Pt = Pn + B. From Poisson statistics, the uncertainty on the total peak counts Ut is given by the square root of the total counts Pt and the uncertainty in the background Ub is the square root of the background counts B. The uncertainty in the difference Pn is thus given by

Un = (Ut2 + Ub2) 1/2 = (Pt + B) 1/2 = ((Pn + B) + B) 1/2 = (Pn + 2B) 1/2.

For these simulated spectra, the relative uncertainty was equivalent to the square root of the sum of the peak area plus twice the background divided by the peak area. For peaks that are large compared to the background, B goes to zero and this relative uncertainty reduces to the square root of the net peak area divided by the net peak area.

3.2.3.2 Results


The elemental abundances in Table 4 are derived from the reference Martian basalt composition containing 1% H2O mass fraction. Table 4 gives the mass fraction and the relative uncertainty of each element for active and passive modes in 10-min and 2-hour counting measurements. By comparing calculations with only MMRTG or only GCRs, we find that most of the detected gamma rays with both MMRTG and GCR sources is due to the GCR source. Therefore, in Table 4, the relative uncertainties for the passive mode were calculated for the simulated gamma-ray spectra that result only from the interaction of the GCRs. Modeling of count rates with MMRTG and GCR is done in the same way as for the active modeling described previously; the same surface compositions and rover model are used, but the PNG neutron spectrum is replaced with the MMRTG spectrum (Jun et el. 2013) or a GCR spectrum (e.g. McKinney et al. 2006). The MMRTG neutron spectrum produces more of the lower energy inelastic lines, while the GCR contributes more continuum and greater line fluxes at higher energies. Overall, the GCR gamma flux is higher.

Since Figure 8 is a capture spectrum, the inelastic lines from Table 4 are not present. Also, the MCNPX simulation did not include the lines from naturally radioactive gamma-ray lines. Those count rates were based on straightforward estimates from decay rates and element abundances (Masarik and Reedy, 1996). We chose not to label the weak capture lines from Table 4 in the spectrum of Figure 8 to avoid cluttering up the figure.

Figure 9 shows the relative uncertainty for each element as a function of time for the active mode. The dotted lines represent the 5 and 10 % relative uncertainties.

This figure shows that the relative uncertainty decreases as the inverse square root of time for each element and can be used to determine the relative uncertainties of each element


at any time with the PING instrument. For example, it would take about 10 min to detect Si with a 5 % relative uncertainty while it would take about 2 hours to detect Mn with the same relative uncertainty. Figure 9 shows PING sensitivity for many elements for our standard Basalt model. One can see for Fe (~14 wt%), for example, that in less than 10 minutes active gamma measurements can define Fe to better than 5% relative (1 ). That is sufficient to distinguish this composition from the other model compositions.

4. Conclusion

Using its active mode, PING can interrogate the material below the rover down to about 20 cm due to the penetrating nature of the 14.1 MeV neutrons and the resulting secondary gamma rays. Although the uncertainties are higher in passive mode than in active mode, PING can also operate without the PNG (e.g. passive mode) to measure gamma-ray spectra that can be used to detect changes in key marker elements and make thermal neutron measurements in about 1 minute that are sensitive to mostly H, but also Cl. PING is capable of identifying most major and minor rock-forming elements, including H, O, Na, Mn, Mg, Al, Si, P, S, Cl, Cr, K, Ca, Ti, Fe and Th. PING’s use of a PNG reduces the required observation times by an order of magnitude. PING can map out the subsurface elemental composition during short (10 min) mid-traverse rover stops. We found that in active mode, a 10-min measurement would allow PING to measure Al, Fe, O, Si and Ti with uncertainties under 10 %. For a more complete elemental inventory, we found that a 2-hour measurement would allow PING to measure Al, Cl, Fe, H, K, Mg, Mn, O, S, Si and Ti with uncertainties under 10 %. While the active mode allows for more complete elemental inventories with higher sensitivity, the gamma-ray signatures of some elements are strong


enough to detect in passive mode while the rover is moving. We showed that in passive mode, a 2-hour stationary measurement would allow PING to measure Al, Cl, Fe, K and Si with uncertainties under 10 %.

5. Acknowledgements

Funding for this work was provided by NASA/GSFC and NASA/JPL.


References

Bhat, M. R., Evaluated Nuclear Structure Data File (ENSDF), Nuclear Data for Science and Technology, page 817, edited by S. M. Qaim (Springer-Verlag, Berlin, Germany, 1992).

Bielefeld, M. J., Reedy, R. C., Metzger, A. E., Trombka, J. I. and Arnold, J. R. (1976), “Surface Chemistry of Selected Lunar Regions”, Proc. Lunar Sci. Conf. 7th, 2661–2676.

Blake, D. F. et al. (2013), “Curiosity at Gale Crater, Mars: Characterization and Analysis of the Rocknest Sand Shadow”, Science, 341(6153), 1239505.

Bodnarik, J. G. et al. (2013), “Time-resolved neutron/gamma-ray data acquisition for in situ subsurface planetary geochemistry”, Nuclear Instruments and Methods in Physics Research A 707 135 – 142.

W. V. Boynton et al. (2004), “The Mars Odyssey Gamma-Ray Spectrometer Instrument Suite,” Space Science Reviews, January 2004, Volume 110, Issue 1, pp 37-83.

W. V. Boynton, G. J. Taylor, L. G. Evans, R. C. Reedy, R. Starr, D. M. Janes, K. E. Kerry, D. M. Drake, K. J. Kim, R. M. S. Williams, M. K. Crombie, J. M. Dohm, V. Baker, A. E. Metzger, S. Karunatillake, J. M. Keller, H. E. Newsom, J. R. Arnold, J. Bruckner, P. A. J. Englert, O. Gasnault, A. L. Sprague, I. Mitrofanov, S. W. Squyres, J. I. Trombka, L. d’Uston, H. Wanke, and D. K. Hamara (2007), “Concentration of H, Si, Cl, K, Fe, and Th in the lowand mid-latitude regions of Mars,” J. Geophys. Res. 112 E12S99, doi:10.1029/2007JE002887.


Chadwick, M. B., et al., ENDF/B-VII.1 Nuclear Data for Science and Technology: Cross Sections, Covariances, Fission Product Yields and Decay Data, Nuclear Data Sheets, Volume 112, Issue 12, December 2011, Pages 2887–2996.

Evans, Larry G, Robert C Reedy, Richard D Starr, Kristopher E Kerry, and William V Boynton (2007). “Analysis of Gamma Ray Spectra Measured by Mars Odyssey.” Journal of Geophysical Research 112, no. 3 1–21. doi:10.1029/2005JE002657.

Larry G. Evans, Richard D. Starr, Johannes Brückner, Robert C. Reedy, William. V. Boynton, Jacob I. Trombka, John O. Goldsten, Jozef Masarik, Larry R. Nittler, and Timothy J. McCoy (2001) “Elemental Composition from Gamma-Ray Spectroscopy of the Near-Shoemaker Landing Site on 433 Eros,” Meteoritics & Planetary Science 36, 1639-1660

Evans, L. G., Peplowski, P. N., Rhodes, E. A., Lawrence, D. J., Nittler, L. R., McCoy, T. J., Solomon, S. C., Sprague, A. L., Stockstill-Cahill, K. R., Starr, R. D., Weider, S. Z., Boynton, W. V., and Hamara, D. K. (2012), “Major-Element Abundances on the Surface of Mercury: Results from the MESSENGER Gamma-Ray Spectrometer”, J. Geophys. Res. Planets, 117. I. Jun, I. Mitrofanov, M. L. Litvak, A. B. Sanin, W. Kim, A. Behar,1 W. V. Boynton, L. DeFlores, F. Fedosov, D. Golovin, C. Hardgrove, K. Harshman, A. S. Kozyrev, R. O. Kuzmin, A. Malakhov, M. Mischna, J. Moersch, M. Mokrousov, S. Nikiforov, V. N. Shvetsov, C. Tate,4 V. I. Tret’yakov, and A. Vostrukhin (2013), “Neutron Background Environment Measured by the Mars Science Laboratory’s Dynamic Albedo of Neutrons Instrument During the First 100 Sols”, J. Geophys. Res., 118, 2169.


Jun, I., Kim, W., Smith, M., Mitrofanov, I., Litvak, M. (2011), “A study of Venus surface elemental composition from 14 MeV neutron induced gamma ray spectroscopy: Activation analysis”, Nuclear Instruments and Methods in Physics Research A 629 140–144

J. Masarik, J. and R. C. Reedy, (1996) “Gamma ray production and transport in Mars”, Journal of Geophysical Research 101: doi: 10.1029/96JE01563. issn: 0148-0227.

McKinney, G. W., D. J. Lawrence, T. H. Prettyman, R. C. Elphic, W. C. Feldman, and J. J. Hagerty (2006), “MCNPX Benchmark for Cosmic Ray Interactions with the Moon”, J. Geophys. Res., 111.

Mitrofanov, I. G., M.L. Litvak, A.B. Varenikov, Y.N. Barmakov, A. Behar, Y.I. Bobrovnitsky, E.P. Bogolubov, W.V. Boynton, K. Harshman, E. Kan, A.S. Kozyrev, R.O. Kuzmin, A.V. Malakhov, M.I. Mokrousov, S.N. Ponomareva, V.I. Ryzhkov, A.B. Sanin, G.A. Smirnov, V.N. Shvetsov, G.N. Timoshenko, T.M. Tomilina, V.I. Tret’yakov, A.A. Vostrukhin (2012), “Dynamic Albedo Of Neutrons (DAN) Experiment Onboard NASA’s Mars Science Laboratory”, Space Sci. Rev., 170, 559–582.

Parsons, A. M. et al. (2011), “Active neutron and gamma-ray instrumentation for in situ planetary science applications”, Nuclear Instruments and Methods in Physics Research A 652 674 – 679.

Radtke, R .J., Lorente M, Adolph B, Berheide M, Fricke S, Grau J, Herron S, Horkowitz J, Jorion B, Madio D, May D, Miles J, Perkins L, Philip O, Roscoe B, Rose D, and Stoller C


(2012), “A New Capture and Inelastic Spectroscopy Tool takes Geochemical Logging to the Next Level,” SPWLA 53rd Annual Logging Symposium

Saint-Gobain

Crystals,

Technical

note,

http://www.crystals.saint-

gobain.com/uploadedFiles/SGCrystals/Documents/Technical/SGC%20BrilLanCe%20Scintillators%20Performance%20Su mmary.pdf

Pelowitz, D. B. ed. (2005), “MCNPX User’s Manual, Version 2.5.0”, Los Alamos Natl. Lab., Los Alamos, N. M., Rep.LA-UR-94–1817, 473.


Table 1. Elemental composition used in the MCNPX model of Mars regolith. Opaline

Paso Robles

Sulfate

Silica

equivalent (Sol 723)

Bedrock

Basalt

Element

Element mass fraction % or mg/kg

Si

20.77

32.34

12.32

15.56

Ti

0.61

0.36

0.26

0.41

Al

5.04

0.79

0.52

2.93

Cr

0.28

0.19

0.27

0.12

Fe

13.93

5.19

10.25

10.76

Mn

0.28

0.02

0.03

0.22

Mg

4.92

4.36

1.99

4.21

Ca

4.84

0.71

0.48

3.13

Na

1.94

0.40

0.08

1.11

K

0.39

0.13

0.01

0.43

P

0.39

0.19

0.18

0.41

S

2.25

1.34

11.5

7.92

Cl

0.67

0.83

0.26

0.99

Br mg/kg

59.07

127.512

0

75.58

Ni mg/kg

455.07

834.44

0

551.86

Zn mg/kg

302.28

783.104

0

357.58

H

0.11

0.89

1.98

1.22

O

43.45

52.05

55.65

50.46


Table 2. Thermal neutron capture cross sections for Cl and S and their isotopes. Isotope

Isotopic fraction

Thermal capture cross section (b)

(%)

(Chadwick et al., 2011)

35

Cl

75.77

43.74

37

Cl

24.23

0.43

Thermal neutron capture cross section for Cl: 33.2 b 32

95.02

0.53

33

0.75

0.35

34

4.21

0.22

36

0.02

0.15

S S S S

Thermal neutron capture cross section for S: 0.5 b


Table 3. Intensity of gamma rays from the capture of thermal neutrons for 35Cl and 32S (Bhat, 2006). Gamma rays Intensity (% of strongest Isotope

Energy (keV)

produced per transition) 100 captures

35

Cl

1951

71

19

35

Cl

1959

46

12

35

Cl

6111

74

20

35

Cl

6620

28

8

35

Cl

6628

16

4

35

Cl

7414

37

10

Total number of gamma rays emitted per 100 captures in 35Cl: 73 32

S

5420

92

60

Total number of gamma rays emitted per 100 captures in 32S: 60


Table 4. Calculated relative uncertainties for 10-min and 2-hour measurements for Martian basaltic soil hydrated at a nominal 1% H2O mass fraction. In the table, In = inelastic scattering, Cap = capture, Nat = natural radioactivity.

Element

Mode

- Element

energy

Mass

(keV)

fraction %

Active Mode

Passive Mode (GCR)

Relative

Relative

Uncertainty %

Uncertainty %

10 min

2h

10 min

2h

or

mg/kg Al

In - 2211

5.0

39.0

11.3

57.6

16.6

Ca

Cap - 1942

4.8

75.5

21.81

93.5

27.0

Cl

Cap - 1951, 0.7

18.8

5.41

33.4

9.64

1959, 6111, 6620, 6628, and 7414 Cr

In -1434

0.3

55.0

15.89

144.3

41.7

Fe

In - 847

13.9

3.89

1.12

16.5

4.77

H

Cap - 2223

0.1

34.2

9.86

67.8

19.6

O

In - 6129

43.5

5.78

1.67

35.0

10.1

K

Nat - 1461

0.4

17.4

5.02

17.4

5.02

Mg

In - 4238

4.9

20.7

5.98

135.0

39.0

Mn

In - 1166

0.3

16.1

4.66

136.5

39.4


Na

Cap - 6395

1.9

58.6

16.91

135.2

39.0

P

In - 1266

0.4

48.8

14.09

142.6

41.2

S

In - 2231

2.3

14.0

4.04

63.1

18.2

Si

In - 1779

20.8

4.87

1.41

19.2

5.54

Th mg/kg

Nat - 2615

0.62

180

52.0

180

52.0

Ti

In - 983

0.6

7.47

2.16

54.8

15.8


Figure 1. PING’s PNG excites the nuclei in the Martian soil resulting in the emission of characteristic gamma rays. The detection of the characteristic gamma rays analyzed by the GRS yields the elemental composition and layering information.


Figure 2. PNG time gating configuration and the different gamma-ray spectra acquired by the GRS.


Figure 3. LaBr3 self-counting background


Figure 4. Location of the PING's PNG and GRS on the back of the rover.


a.

b.

Figure 5. Modeled PING gamma-ray count rate ratios in active mode, a) S/Si vs. H/Si, b) Cl/Si vs. H/Si for four different compositions: homogeneous Martian basalt and 5 cm, 10 cm


and 20 cm of Martian basalt over sulfate bedrock, opaline silica and Paso Robles equivalent (Sol 723). Error bars are 1σ results obtained in 10 min PING simulations.


a.

b.


Figure 6. Modeled PING gamma-ray count rate ratios in active and passive mode, a) S/Si vs. H/Si, b) Cl/Si vs. H/Si for homogeneous Martian basalt and homogeneous Martian basalt over a sulfate bedrock layer. Error bars are 1σ results obtained in 10 min PING simulations.


Figure 7. Thermal neutron measurements in 1 minute for four different compositions: 5 cm, 10 cm and 20 cm of Martian basalt over sulfate bedrock, opaline silica and Paso Robles equivalent.


a.

b.


Figure 8. Labr3 capture gamma-ray spectrum comparison when the rover is present and when it is not for the monolayer model (Martian basalt).


Figure 9. Relative uncertainty as a function of time in active mode.
