REFLECTANCE SPECTROSCOPY FOR ORGANIC DETECTION AND QUANTIFICATION IN CLAY-BEARING SAMPLES: EFFECTS OF ALBEDO, CLAY TYPE, AND WATER CONTENT

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1 Clays and Clay Minerals, Vol. 64, No. 2, , 216. REFLECTANCE SPECTROSCOPY FOR ORGANIC DETECTION AND QUANTIFICATION IN CLAY-BEARING SAMPLES: EFFECTS OF ALBEDO, CLAY TYPE, AND WATER CONTENT H ANNAH H. KAPLAN* AND R ALPH E. MILLIKEN Department of Earth, Environmental, and Planetary Sciences, Brown University, 324 Brook St., Box 1846, Providence, RI 2912, USA Abstract Reflectance spectroscopy is a rapid and non-destructive method that can be used to detect organic compounds in geologic samples over a wide range of spatial scales that includes outcrops, hand samples, drill cores, and planetary surfaces. In order to assess the viability of this technique for quantification of organics and aliphatic compounds in particular, the present study examines how clay mineralogy, water content, and albedo influence the strength of organic absorptions in near-infrared (NIR) reflectance spectra. The effects of clay structure and water content are evaluated using kaolinite, smectite (montmorillonite), and a mixed-layer illite-smectite as starting materials. Absorption strengths for C H absorptions are compared to known total organic carbon (TOC) values using both reflectance spectra and single scattering albedo (SSA) spectra derived from a Hapke radiative transfer model. A linear relationship was observed between band depth and TOC for each sample suite, but strong albedo variation led to nonunique trends when band depths were calculated from reflectance spectra. These effects were minimized by conversion to SSA, for which band depth-toc trends were similar for all mixture suites regardless of albedo or hydration level, indicating that this approach may be more broadly applicable for clay and organic-bearing samples. Extrapolation of band depth-toc trends for the synthetic mixtures suggested a very conservative lower limit of detection of <1 wt.% TOC, but preliminary results for natural organicbearing shales indicated that detection limits may be an order of magnitude lower. Key Words Detection Limit, Organic Detection, Organo-clay, Quantification, Reflectance Spectroscopy. * address of corresponding author: Hannah_Kaplan@brown.edu DOI: /CCMN INTRODUCTION Infrared reflectance spectroscopy is a rapid, nondestructive technique that is valuable in many geologic applications due to its ability to detect simultaneously organic compounds and mineralogy through the identification of diagnostic vibrational absorptions. Smallscale applications of reflectance spectroscopy in this context include analysis of organics in drill core and soil samples (e.g. Nguyen et al., 1991; Nocita et al., 214; Herron et al., 214; Washburn et al., 215) as well as analysis of (abiotic) organic matter in carbonaceous chondrite meteorites (Cloutis et al., 212), to name just a few. Because it can be used as a passive technique (relying on solar radiance), reflectance spectroscopy also holds promise for large-scale applications including the search for organic compounds on Mars, Europa, C-type asteroids, and other planetary surfaces (Bibring et al., 212; Mustard et al., 213). Importantly, the past several decades have seen significant advances in the development of visible (VIS) and near-infrared (NIR) imaging spectrometers that can rapidly acquire spatially resolved spectral data for hundreds of wavelengths over a wide field of view, without the need to rasterize multiple point measurements (e.g. Van Gorp et al., 214; Greenberger et al., 215). Such instruments require no sample preparation and are capable of mapping samples at spatial scales of micrometers to kilometers. As such, they provide important spatial information to complement spectral detections, which can be particularly powerful for understanding links between organic compounds and mineralogy in terrestrial drill cores or on planetary surfaces. Despite these advantages, as well as the commercialization of imaging spectrometers and the use of VIS- NIR instruments on past, current, and upcoming planetary missions, only limited work has been done to understand the detection limits for organic compounds using reflectance spectroscopy and to establish the degree to which this method can be used to quantify organic content in rocks and sediments. Although relationships between reflectance spectra and organic content have been determined for select terrestrial applications (e.g. Washburn et al., 215), a more general understanding of the limitations of reflectance spectroscopy for organic detection is still desired. This is particularly true for planetary exploration, mapping of rocks and drill cores, and other applications where certain sample preparation methods (e.g. dilution of rock powder by KBr) are neither desirable nor possible. Understanding how variations in sample properties such as mineralogy and albedo can affect organic absorptions in reflectance spectra is particularly impor-

2 168 Kaplan and Milliken Clays and Clay Minerals tant for applications where such factors are poorly constrained or highly variable, as is often the case in planetary exploration. The present study represents a starting point for addressing these issues. A suite of synthetic clay- and organic-bearing mixtures was examined using point reflectance spectroscopy to: (1) understand how competing effects of mineralogy, water content, and albedo affect organic detection using this technique; and (2) develop data-analysis methods that can act as a foundation for future development of more complicated spectral models and analysis of spectral imaging data. BACKGROUND From Earth s rock record a strong link has been identified between organic content and clay abundance, and the Sample Analysis at Mars (SAM) instrument on NASA s Curiosity rover has also detected organic compounds in association with clay minerals in Martian mudstones (Glavin et al., 213; Freissinet et al., 215). Similarly, organic molecules are intimately associated with clay minerals in carbonaceous chondrite meteorites (Pearson et al., 22), and although such compounds have been studied previously using transmissionspectroscopy(e.g. Orthous-Daunay et al., 213), the upcoming Hayabusa2 and OSIRIS-REx missions both include reflectance spectrometers to observe the surfaces of potentially organic-bearing C-type asteroids (Pilorget and Bibring, 213; Lauretta et al., 215). Constraining organic detection limits and quantification methods for reflectance spectra of clay-bearing materials was chosen, therefore, as the focus of this study because it has wide ranging applications, spanning terrestrial hydrocarbon exploration to the search for extraterrestrial organic compounds. Several suites of synthetic clay-organic mixtures were analyzed using NIR reflectance spectra in order to isolate and assess the effects of clay mineralogy, albedo, and water content on the detection of organic absorptions at wavelengths of <4 mm. Clay minerals, especially those with expandable interlayers, are often associated with organic matter in the geologic record due to their unique physiochemical properties (Keil et al., 1994; Wattel-Koekkoek et al., 21). Organics and clays in such naturally occurring mixtures may be related structurally at a submicrometer scale (Keil and Mayer, 214), which is inherently more physically complex than the synthetic mixtures examined here. A foundation must be provided first for future application to more complex natural clay-bearing samples by evaluating the individual contribution of important variables in a well constrained system. Indeed, albedo, clay type, and water content are all known to have an effect on absorptions in reflectance spectra (e.g. Clark, 1983; Bishop et al., 1994; Milliken and Mustard, 27) and may confound attempts at organic quantification and detection using NIR reflectance techniques. Remote applications of reflectance spectroscopy can rely on incident solar radiation, and as such this method has been used widely in planetary science and astronomy to assess the composition of asteroids (e.g. Gaffey et al., 1989; Pieters and McFadden, 1994) and planetary surfaces (e.g. Tompkins and Pieters, 1999; Pelkey et al., 27). Unlike transmission spectra, however, absorptions in reflectance spectra do not conform to simple mathematical relationships such as Beer s Law due to complex and non-linear effects of multiple scattering in particulate materials (Hulst, 1981; Hapke, 1993; Clark, 1999). The assumption of linear spectral mixing is, therefore, often not valid for particulate mixtures of two or more components (i.e. weighted linear combinations of endmember spectra do not accurately reflect the mixture spectrum or modal abundances of the different components) (Hapke, 1993). In addition, physical properties such as particle size (Hapke, 1981; Mustard and Hays, 1997; Cooper and Mustard, 1999), albedo (Nash and Conel, 1974; Clark 1983), and porosity (Hapke, 28) are known to have a disproportionate (non-linear) effect on absorptions in reflectance spectra at VIS-NIR wavelengths. Fortunately, several radiative transfer models (RTMs) have been developed to account for these complexities, two popular ones being the Hapke model (Hapke, 1981) and the Shkuratov model (Shkuratov et al., 1999). Only the Hapke model was used here, because it has the advantage of accounting directly for viewing geometry (incidence, emergence, and phase angle), the values of which may differ between laboratory measurements or within images acquired by satellite or roverbased imaging systems. To obtain modal abundances from reflectance spectra in the Hapke model, conversion of the reflectance spectra to single scattering albedo spectra (abbreviated here as SSA) is necessary. The SSA may be considered as a description of the interaction between a single photon and a single particle, and as such SSA spectra have minimized the effects of interparticle scattering. Reflectance spectroscopy of organic compounds The ultraviolet (UV) and VIS-NIR wavelengths (.2 5 mm) are ideal for assessing mineralogy and organic matter due to electronic (charge transfer and electron transition) and vibrational absorptions in this range. Multiple wavelength regions exist where absorption by organic compounds (defined here as C Hbearing ) is detectable in a reflectance spectrum (Figure 1). The so-called fingerprint region falls between ~7 and 2 mm (15 5 cm 1 ) where bending and stretching vibrations create a complicated series of overlapping absorptions (Workman and Weyer, 28). At shorter wavelengths (2.5 6 mm; cm 1 ), absorptions arise primarily from C C, C O, and C H vibrations, along with the fundamental OH and H 2 O vibrations. The C H stretching region is found near

3 Vol. 64, No. 2, 216 Reflectance spectroscopy to detect and quantify organic compounds 169 Organic compound spectra Reflectance Wavelength (µm) Figure 1. FTIR reflectance spectra of pure, solid (particulate) sodium stearate (C 18 H 35 NaO 2 ) and hexamethylbenzene (C 6 (CH 3 ) 6 ). Absorptions due to fundamental C H vibrations, combinations, and overtones are prominent in the near- to mid-infrared wavelength range for both aromatic and aliphatic compounds. ~3 mm, with absorptions characteristic of aliphatic compounds occurring at longer wavelengths ( mm; cm 1 ) and those characteristic of aromatic compounds occurring at shorter wavelengths ( mm; cm 1 ) (Pendleton et al., 1994; Workman and Weyer, 28; Clark et al., 21) (Table 1). The spectra of 47 pure, particulate polycyclic aromatic hydrocarbons (PAHs) from mm and the positions of C H overtone and combination bands within the spectra at these shorter, VIS-NIR wavelengths were measured by Izawa et al. (214b) (Table 1). Similarly, absorptions in the UV to mid infrared (MIR) range for a variety of pure alkanes ranging in size from methane to paraffin were reported by Clark et al. (29). Those studies provide a spectral library of organic compounds which are relevant to both planetary science (e.g. surface and atmosphere of Titan, carbonaceous meteorites/asteroids, and comet nuclei) and hydrocarbon exploration on Earth. In a step toward quantification, Moroz et al. (1998) compared reflectance of natural, solid bitumen with X-ray diffraction (XRD) and 13 C- NMR measurements in order to track changes in H/C and O/C ratios. The general practice in which sediment or soil samples are studied for the purpose of quantifying organic content has been to use partial least squares (PLS) or principal component analysis (PCA). Both methods take into account purely statistical relationships between all wavelengths rather than any one absorption band or spectral parameter (e.g. Chang et al., 21; Vasques et al., 28; Washburn and Birdwell, 213; Washburn et al., 215). Caution must, therefore, be used when interpreting such data in terms of physical causes (e.g. relating PCA or PLS results to specific bonding environments). In addition, methods such as PLS that rely on training datasets may yield inaccurate results when applied to data or samples outside the range of the original training set. In spite of these issues, statistical methods such as PLS have been demonstrated to be capable of providing accurate estimates of the mineralogy and organic content (e.g. TOC) if they are calibrated for a particular sample suite or rocks within a given basin (Adams et al., 25; Washburn and Birdwell, 213; Washburn et al., 215). Such calibration steps can be time consuming and/or are not always possible (e.g. for planetary-surface applications); thus, evaluation of non-statistical methods that are instead based on fundamental physics of radiative transfer and photon scattering (i.e. the Hapke model) are warranted. Though computationally more complex than most statistical methods, radiative-transfer approaches are advantageous in that they provide a more generic method for analyzing disparate samples. When considering applications to planetary exploration, establishing lower limits of detection of organics is of utmost interest, particularly for geologic samples that may have experienced complex diagenetic and burial histories. On Mars, organic matter, if present, is assumed to be only in low concentrations; consequently

4 17 Kaplan and Milliken Clays and Clay Minerals Table 1. Near infrared and mid-infrared organic absorptions typical of the organic compounds used in this study. Previous work on alkanes and PAHs by Izawa et al. (214b) and Clark et al. (29) provides a spectral library for comparison with organic-bearing sediments of geologic and planetary importance. Name Wavelength (mm) Wavenumber (cm 1 ) Bonding environment IR absorptions of acyclic alkanes 1 CH 2 asymmetric stretch CH 2 CH 3 asymmetric stretch CH 3 CH 2 symmetric stretch CH 2 CH 3 symmetric stretch CH 3 First overtone 2uCH CH 2, CH 3 Second overtone 3uCH CH 2, CH 3 First combination region CH 2, CH 3 Second combination region CH 2, CH 3 Carbonyl 1.67, ; 5896 C=O Carbonate overtones and combinations ; ; CO 3 VIS-NIR of PAHs 2,3 Fundamental CC stretch C=C Fundamental CH stretch (aromatic) CH First overtone 2uCH CH 2, CH 3 Second overtone 3uCH CH 2, CH 3 First combination region (aromatic C H CH stretching and bending modes) First combination region (CH stretches and IR inactive C=C) CH, C=C 1 Workman and Weyer (28) 2 Izawa et al. (214b) 3 Hudgins and Allamandola (1997) instrument suites sent to Mars should be sensitive to low concentrations of organic matter (Mustard et al., 213). For instance, chlorobenzene at 15 3 parts per billion by weight in the Sheepbed mudstone measured by the NASA Curiosity rover in Gale crater, Mars, was reported by Freissinet et al. (215). Detection limits on laboratory mixtures of PAHs and a Martian soil simulant (JSC Mars-1) was assessed using an anthracene fluorescence band at ~419 nm, which was observed at.1 wt.% anthracene (Izawa et al., 214a). The lower limit of detection for organics in a dehydrated mineral matrix was suggested by Anderson et al. (25) to be closer to 5 ppm, however, but those authors provided no supporting data. An ongoing goal of the present study is to establish detection limits for aliphatic and aromatic organics in geologic samples using NIR reflectance spectroscopy, and the authors focus here on the stronger aliphatic absorptions. METHODS Synthetic mixtures Physical mixtures of thoroughly characterized clay minerals and pure, solid, organic compounds were made to test absorption strength (referred to here as band depth ) as a measurable parameter for TOC in a well controlled system. The variables in these mixtures were total organic carbon (TOC), hydration (H 2 O content), and albedo. Sodium stearate (C 18 H 35 NaO 2 ; Product S3381, Sigma-Aldrich, St. Louis, Missouri, USA), a sodium salt of stearic acid, was chosen as the primary organic compound for these mixtures because of its acyclic aliphatic carbon chain, abundance of sp2-bonded carbons, and because its physical properties facilitated mixing with clay. Several mixtures were also made using hexamethylbenzene (C 6 (CH 3 ) 6 ; Product , Sigma- Aldrich), an aromatic hydrocarbon with six methyl groups. The particle-size distribution of the organic compounds was not measured directly, but optical microscopy showed all particles or aggregates to be <<1 mm, though individual particles may be submicron in size. In addition to the pure clays, mixtures were made with.5 wt.% and 1 1 wt.% organics (in 1% increments), yielding a total of 12 different organic abundances for each clay type. The TOC for each mixture was determined from the measured organic wt.% based on the organic compound molecular structure, an appropriate assumption given that these are binary mixtures and that original clays were prepared to be organic-poor (see below). Three clay minerals were chosen for the mixtures based on their differing levels of hydration (i.e. the amount of interlayer H 2 O). From least to most hydrated, the clays used were kaolinite (KGa-1), illite-smectite (IsCz-1), and montmorillonite (SAz-1), all obtained from The Clay Minerals Society (CMS) Source Clays

5 Vol. 64, No. 2, 216 Reflectance spectroscopy to detect and quantify organic compounds 171 Repository. The particle-size distribution for the clays was not measured, but the preparation method (mill pulverization) for the CMS clays produces extremely small particle sizes, and individual clay crystals were submicron in size. Visual inspection with a microscope revealed, however, that the small clay particles formed aggregates with a larger effective particle size, potentially surrounding or co-mixed with the organic particles. The clays were heated to 15ºC in air for 1 h to help volatilize trace organic matter. This temperature was insufficient to induce full collapse of the interlayers, and samples were then exposed to ambient conditions to allow them to rehydrate to a stable H 2 O content. Reflectance spectra were acquired pre- and post-heating to verify that organics were removed without causing structural changes to the clay endmembers. The organic compounds used in this study were white, particulate solids and were not expected to reduce the albedo of the clay-organic mixtures. This is in contrast to many natural organic-rich rocks and carbonaceous chondrite meteorites, which are often quite dark. Albedo was controlled artificially by adding differing amounts of finegrained (submicrometer) carbon lampblack, an extremely efficient darkening agent with no absorptions at VIS-NIR wavelengths (Clark, 1983; Milliken and Mustard, 27). Because carbon lampblack is so highly absorbing, only a small amount was needed to cause a drastic change in albedo. The organic-clay mixtures were first analyzed with no carbon lampblack and subsequently mixed with.5 wt.% lampblack, re-measured with the spectrometers, then mixed with a total of 1 wt.% lampblack, and measured a final time. Because the maximum amount of carbon lampblack used was only 1 wt.%, no significant effects on the absolute abundance of clay and organics in the binary mixtures were noted. The TOC values reported here are for the original binary mixtures, prior to dilution by the minor addition of carbon lampblack. The combination of three different clay minerals (representing three different water contents and clay structures), three albedo levels (,.5, and 1 wt.% carbon lampblack), and twelve different sodium stearate abundances resulted in a total of 18 clay-organic mixtures, including the pure clay samples. The clay, organic compound, and carbon lampblack were weighed out using a balance to within Ô1 mg of the calculated value. For comparison, the total mass of the mixtures typically fell between 4 and 6 mg. Once weighed out, each component was added to a glass vial. The glass vial was shaken by hand for ~1 min. Creating homogeneous mixtures was considered an important factor for these experiments, but earlier testing using other mixing techniques (e.g. roto-evaporator and mechanical agitation) demonstrated that physical mixing by hand produced equivalent or better results for these particular materials. The heterogeneity of mixtures was tested by acquiring spectra of different aliquots of each mixture and, to assess the distribution of carbon lampblack, by examining the mixtures with an optical microscope. Distinguishing the bright clay and organic particles was impossible under the microscope using reflected light, but the distribution of the darker carbon lampblack particles was observed readily in the low-albedo mixtures. Reflectance measurements The reflectance spectra of the mineral endmembers and particulate mixtures were measured using an Analytical Spectral Devices (ASD) FieldSpec 3 (ASD Inc. Boulder, Colorado, USA) portable spectroradiometer from mm and a Nicolet is5 FTIR (Thermo Scientific, Waltham, Massachusetts, USA), equipped with a diffuse reflectance attachment, from 1.7 to 25 mm. The ASD measurements used a fiber optic light source with a 25º field of view (FOV) that was placed at 3º from normal. A receiving fiber attached to the spectrometer, also with a 25º FOV, was positioned at º emergence angle. The heights of the input and receiving fibers were controlled such that measurements integrated over a spot size of ~1 mm. The spectrum of each sample was measured relative to a white reference (Spectralon from Labsphere, North Sutton, New Hampshire, USA) taken at the same viewing geometry. Each final spectrum was an average of 5 scans. The FTIR was equipped with a Praying Mantis diffuse reflectance attachment (Harrick Scientific, Pleasantville, New York, US) and spectra were measured relative to a diffuse gold standard (Labsphere) using an IR source. A KBr beamsplitter and deuterated triglycine sulfate (DTGS) detector were used for all FTIR measurements, and each spectrum was an average of 5 scans over a spot size of ~1 2 mm. To better understand possible heterogeneity in the mixtures, particularly for organic absorptions between ~3 and 4 mm, each sample was measured with the FTIR three times. The sample cup was emptied and refilled between each measurement in order to examine different aliquots of the same mixture. Spectra measured by the FTIR were scaled and joined to the ASD spectra at ~1.7 mm, as the ASD spectra provide values closer to absolute reflectance. A subset of samples was measured multiple times with the ASD spectrometer in order to assess spectral homogeneity, including measuring different spots sizes (~1 9 mm) to evaluate spectral mixing effects for different fields of view. Analysis Band depth (Clark and Roush, 1984) is a measurement of the strength of a given absorption in the reflectance spectrum and was one of the primary metrics for relating spectral features to organic content. Band depth is defined as D(g) =1 R b (g)/r c (g) (1) where R b is the reflectance at the minimum of the absorption feature and R c is the reflectance of the

6 172 Kaplan and Milliken Clays and Clay Minerals continuum at a single wavelength, l. In the present study, an upper convex hull was fitted to each spectrum to define the spectral continuum and the original spectrum was divided by this continuum. This is similar to background corrections commonly used for transmission/absorbance spectra, and the result is a continuumremoved spectrum over a specified wavelength region. Continuum removal was carried out over three wavelength regions that include organic absorptions: mm, mm, and mm. For these small-wavelength regions, both a linear fit with fixed endpoints and a spline continuum fit performed equally well as the upper convex hull method. Band depths were then calculated for all organic absorptions using the continuum-removed spectra. Prior to continuum removal, the reflectance value at 1.7 mm was recorded as a measure of sample albedo. The FTIR spectra were also converted from reflectance to SSA using the equations described by Hapke (1981, 1993): m R ¼ o f½1 þ Bðg; fþšpðgþþhðm 4p m þ m ; oþhðm; oþ 1g ð2þ where reflectance (R) is a function of single scattering albedo (o), cosine of the emergence and incidence angle (m and m ), a back scattering function (B(g, f)), which, in turn, is a function of phase angle, g, and porosity, f), a phase function (P(g)), and a multiple scattering function (H) (Hapke, 1981, 1993). The viewing geometry was defined by an incidence angle of 3º (i), emittance angle of º (e), and a phase angle of 3º (g). Porosity, f, was set at.6, a common value for planetary regoliths (Hapke, 1981) and a reasonable value for these loose, unpacked powders. Single scattering albedo was solved explicitly at each wavelength using the measured reflectance values. Because viewing geometry and all other parameters are defined (and are similar between spectra), equation 2 is reduced to a sixth-order polynomial that can be written in terms of g, where g = (1 o) 1/2, that has only one solution for the constraint 4 o 41. The resulting SSA spectra were continuum-removed using the same method described above and band-depth values were recalculated. The Hapke equation described above is strictly valid only for particles whose size (or effective size) lies within the region of geometric optics; isolated submicron crystals or particles would, thus, violate this assumption. Arguments have been made, however, that closely packed particles may scatter coherently (e.g. Salisbury and Wald, 1992), and lab measurements have demonstrated that reflectance spectra of aggregates composed of submicron particles exhibit spectral behavior more consistent with the size of the aggregate than the individual crystals (Cooper and Mustard, 1999). That is, the aggregates may act as fundamental scattering/ absorbing units for finegrained components in closely packed media, as is the case for the mixtures in the present study. SWy-1 montmorillonite, which has bulk physical properties similartothesaz-1sample,wasmeasuredbycooper and Mustard (1999) who concluded that the relevant particle size in terms of the photon-sample interaction was the aggregate size and not the individual clay crystal size. This finding is in agreement with a visual inspection of the samples examined here, which showed aggregation within the fine-grained clay-organic-carbon mixtures. Building upon these previous studies, the assumption in the use of the Hapke model for the mixtures examined here is that the aggregates of the particles act as coherent scatterers and, thus, the assumption of geometric optics (and the Hapke model) is acceptable. The bulk water content of each of the three clay minerals was calculated based on the H 2 O absorption near 2.9 mm using the effective single particle absorption thickness (ESPAT) as defined by Hapke (1993), using the same methods as described by Milliken and Mustard (25, 27). A coefficient to convert from ESPAT to water content (H 2 O wt.%) for mixtures of montmorillonite and carbon lampblack is also described in that paper. The kaolinite, illite-smectite, and montmorillonite used in this study, after organic removal and rehydration under ambient lab conditions, have estimated water contents of.4%, 1.2%, and 3.8%, respectively. No independent measurements were made of these water contents, but the measurement and dataanalysis procedures were identical to those of Milliken and Mustard (25). A linear regression was used to assess the relationship between band depth and TOC or organic wt.%. The effects of other variables discussed in the present study (hydration, albedo) on band depth were also analyzed using a multiple linear regression. By normalizing each variable, the relative importance of each as a control on band depth is shown. Normalization was done by subtracting the mean and dividing by the standard deviation (z-transform); once each variable is measured on the same scale, the magnitude of the regression coefficient can be used to gauge the importance of each variable in the regression model. In the present study the lower limit of detection was defined as the organic content at which spectral evidence of organic compounds was no longer present. If the band depth-toc trends are shown to be linear over the range of interest, then the x-intercept in the linear regressions can be used as an estimate for the lower limit of detection for the different mixtures (i.e. at what TOC wt.% does band depth approach zero?). RESULTS Overview of relevant spectral features Sodium stearate gave rise to absorptions in all mixture spectra, including those mixtures with.5 wt.% organic (~.3 wt.% TOC), the lowest abundance measured in this study. These absorptions were found near 1.73 mm,

7 Vol. 64, No. 2, 216 Reflectance spectroscopy to detect and quantify organic compounds 173 between 2.1 and 2.5 mm, and between 3.3 and 3.6 mm. The mm absorptions were fundamental aliphatic C H stretching absorptions that appear in a typical triplet formation due to the presence of both CH 2 and CH 3. As the organic abundance increased, the strength of these absorptions increased (Figure 2a). As noted by other authors (e.g. Clark, 1983; Milliken and Mustard, 27; Pommerol and Schmitt, 28), the addition of carbon lampblack or other darkening agents reduced the absolute reflectance values and weakened the clay and organic absorptions (Figure 2b). These wavelength positions and trends were consistent for each of the three clay minerals. Finally, distinct differences were observed in the strength and shape of OH and H 2 O water absorptions in the ~3 mm region for the three clays, confirming that they contained different amounts of H 2 O (Figure 2c). All three clays may have contained water adsorbed onto grain surfaces, but for the montmorillonite and illite-smectite the majority of the H 2 O is expected to reside in the interlayers. Determination of TOC Band-depth values for different organic absorptions were compared to for each albedo level and each clay type (Figure 3). The three wavelength regions of interest (~1.73, ~2.31, and ~3.42 mm) correspond to the first CH overtone, the first CH combination, and the fundamental CH stretch, respectively. Values of TOC exhibited a roughly linear relationship with band depth in all cases, though for some mixtures, particularly those with 1 wt.% lampblack, the values appeared to flatten off at higher TOC values. Note that the slope of the band depth-toc trend was very similar for all three clays when no carbon lampblack was present, but that the slope decreased dramatically as the albedo was reduced (i.e. as carbon lampblack was added) (Table 2). Darkening of the samples had the strongest effect on the overtone and combination bands at wavelengths of <2.5 mm, which were the weakest absorptions, and the effects were less pronounced in trends for the fundamental stretching band near ~3.4 mm. Clearly, in the 2.3 mm band depth vs. TOC plots, the y-intercept was not zero (i.e. band depth never reached zero), which was due to partially overlapping metal-oh clay absorptions in this region that were consistently present even as the organic bands weakened. In SSA spectra, the slope difference was less between brighter and darker samples in the band depth vs. TOC plots (Figure 4), indicating that non-linear effects due to darkening were reduced (Milliken and Mustard, 27). The band depth at mm was not evaluated in this Table 2. Slopes and R 2 values for the linear trends shown in Figures 3 and 4. Part A below reports slopes and R 2 values for the data shown in Figure 3, where band depths are calculated in reflectance; part B reports slopes and R 2 values for data shown in Figure 4, where band depths are calculated in single scattering albedo. A Clay % C. lampblack Slope (1.731 mm) R 2 (1.731 mm) Slope (2.311 mm) R 2 (2.311 mm) Slope (3.42 mm) R 2 (3.42 mm) Kaolinite Kaolinite Kaolinite Illite-smectite Illite-smectite Illite-smectite Montmorillonite Montmorillonite Montmorillonite B Clay % C. lampblack Slope (2.311 mm, SSA) R 2 (2.311 mm, SSA) Slope (3.42 mm, SSA) R 2 (3.42 mm, SSA) Kaolinite Kaolinite Kaolinite Illite-smectite Illite-smectite Illite-smectite Montmorillonite Montmorillonite Montmorillonite

8 174 Kaplan and Milliken Clays and Clay Minerals a) Organic Content Kaolinite Organic wt.%: Illite-Smectite Montmorillonite Wavelength (µm) Wavelength (µm) Wavelength (µm) b) Albedo Kaolinite Illite-Smectite Montmorillonite Reflectance (no offset) C. Lamp black wt.%: Reflectance (no offset) Reflectance (no offset) Wavelength (µm) Wavelength (µm) Wavelength (µm) c) Hydration H 2 O absorption bands Reflectance (cont. removed) Reflectance (offset) Reflectance (offset) Reflectance (offset) Wavelength (µm) Figure 2. Effects of organic content, albedo, and hydration on reflectance spectra of organic-clay mixtures. (a) Reflectance spectra of the kaolinite, illite-smectite, and montmorillonite mixed with different proportions of the organic compound sodium stearate; only a subset of the data is shown here and these spectra are offset for the sake of clarity. The addition of sodium stearate produces absorptions in the near-infrared region (~1.7, , and mm) which increases in strength with increasing organic wt.%. A total of 12 mixtures were made for each clay type, with a representative range shown here. (b) Decrease in reflectance of pure clay end-members due to the addition of.5 and 1 wt.% carbon lampblack. These proportions of lampblack were added to all clay-organic mixtures, and small amounts of lampblack clearly lead to a significantly lower absolute reflectance and weaker absorptions (i.e. the spectra are not offset). (c) Spectral differences near ~3 mm for the clay minerals due to differences in hydration state (water content). The wt.% H 2 O was calculated using the ESPAT parameter and methods described by Milliken and Mustard (27).

9 Vol. 64, No. 2, 216 Reflectance spectroscopy to detect and quantify organic compounds 175 a Kaolinite Illite-Smectite Montmorillonite Band depth (1.731 µm) b Kaolinite Illite-Smectite Montmorillonite Band depth (2.311 µm) c Kaolinite Illite-Smectite Montmorillonite Band depth (3.42 µm) Albedo: Carbon black % Carbon black.5% Carbon black 1% Figure 3. Band depth, as calculated from reflectance spectra, for three organic absorptions vs. total organic carbon (TOC) for each clay type and albedo level. Band depth values at (a) mm, (b) mm, and (c) 3.42 mm exhibit a linear relationship with TOC. Although the three clay minerals exhibit different H 2 O contents, this seems to have little effect on band-depth calculations for the organic bands and mixtures studied here. Different colors correspond to the different levels of albedo (carbon lampblack), and the slope of the band depth vs. TOC relationship appears to have a strong dependence on albedo. For samples with carbon lampblack, the TOC values represent the total organic carbon of the original binary mixtures, prior to dilution with carbon lampblack. Data points reflect mean band-depth values and error bars report the range in band depth across multiple (3) measurements. study for the SSA spectra due to the weakness of this absorption feature (<1% band depth) at the examined TOC values. The effect of converting to SSA was evidenced most concisely using the estimated coefficients (standardized slopes) in a linear regression model that included TOC, albedo, and hydration as controls on band depth using normalized variables. When using reflectance spectra, albedo and TOC both had large coefficients, implying that they were important controls on band depth (Figure 5). Ideally, TOC would be the

10 176 Kaplan and Milliken Clays and Clay Minerals a.8 Kaolinite.8 Illite-Smectite.8 Montmorillonite SSA Band depth (2.311 μm) b Kaolinite Illite-Smectite Montmorillonite.35 8 SSA Band depth (3.42 μm) Albedo: Carbon black % Carbon black.5% Carbon black 1% Figure 4. Band depth, as calculated from single scattering albedo (SSA) spectra, for three organic absorptions vs. total organic carbon (TOC) for each clay type and albedo level. Band-depth values at (a) mm and (b) 3.42 mm exhibit a linear relationship with TOC. Different colors correspond to the different levels of albedo (carbon lampblack), and the slopes for the band depth vs. TOC relationships appear to converge when SSA spectra are used instead of reflectance spectra. For samples with carbon lampblack, the TOC values represent total organic carbon of the original binary mixtures, prior to dilution with carbon lampblack. primary control on band depth, with no influence from either albedo or hydration. These results confirmed previous studies that have shown low albedo or the presence of strong absorbers can have significant nonlinear effects on absorption strength (Clark, 1983; Milliken and Mustard, 27). Indeed, from Figure 3 an accurate TOC value clearly could not be determined without aprioriknowledge of the specific band depth-toc trend (slope) for a sample of a given albedo. When the spectra were converted to SSA, however, this albedo dependence was reduced significantly. This was evident in band depth-toc plots for SSA spectra (Figure 4) as well as in the regression model results (Figure 5). In particular, after conversion to SSA the band-depth values at 3.42 mm clearly were strongly correlated with TOC, whereas albedo and water content had significantly weaker relationships with TOC. For the absorption band at 2.31 mm, the influence of albedo was diminished in SSA spectra but not removed completely. In all of these cases, hydration level (water content) had a regression coefficient with a value near zero, suggesting that the clay water content of <4 wt.% had little effect on the analysis of reflectance or single-scattering albedo spectra. Lower limits of detection and mixture heterogeneity Lower limits of detection can only be estimated by extrapolation of the data in this study due to constraints on making mixtures with very low TOC. Given the wide range of TOC mixtures (~.3 7 wt.%or.5 1 sodium stearate wt.%) and the apparent linear trend, the use of linear regression to examine the TOC at which band depth approaches zero (Figure 6) was possible. The linear regression was weighted based on the variance in the band-depth data (from multiple measurements of each sample) and a 95% confidence interval was reported on that trend; a separate trend was found for each of the different clays and albedo levels (nine in total). One could, therefore, be 95% confident that the lower limit of detection falls within wt.% and the x- intercept of the 95% confidence line for each particular clay-albedo combination (Figure 6b). For the different mixture scenarios reported here, that lower limit fell below 1 wt.% TOC in all cases except for the darkest montmorillonite samples (1 wt.% carbon lampblack). In general, as the samples got brighter, the 95% confidence range occurred at lower TOC values. The most hydrated samples (montmorillonite mixtures) had greater detection limits than the least hydrated (kaolinite

11 Vol. 64, No. 2, 216 Reflectance spectroscopy to detect and quantify organic compounds 177 Band depth µm) ~ 1 + TOC + albedo + hydration a Reflectance Single scattering albedo TOC TOC b Alb. Alb. Hyd. Hyd Standardized slope (ΔY/Δsd(X)) Standardized slope (ΔY/Δsd(X)) TOC Band depth (@3.42 µm) ~ 1 + TOC + albedo + hydration c Reflectance TOC d Single scattering albedo Alb. Alb. Hyd. Hyd Standardized slope (ΔY/Δsd(X)) Standardized slope (ΔY/Δsd(X)) Figure 5. Relative importance of total organic carbon (TOC), albedo (Alb.), and hydration (Hyd.) as controls on band depth of organic features based on linear regression models in which the variables were normalized. Plots are shown for regressions of band depths calculated at (a, b) mm and (c, d) 3.42 mm using reflectance (a, c) and single scattering albedo (b, d) spectra. When reflectance spectra are used, albedo and TOC are both strongly related to band depth. In contrast, the influence of albedo is diminished in SSA spectra, though it remains a non-negligible factor at mm (i.e. in part b). mixtures). Kaolinite with no carbon lampblack had the lowest detection limit confidence interval at.21 wt.% TOC, which approaches the.1 wt.% limit reported by Izawa et al. (214a). Full 95% confidence intervals on the regressions spanned a range of 1.8 wt.% TOC on average; therefore, while the results provide a satisfactory baseline, the uncertainties in band-depth values and the lack of mixtures with <.3 wt.% TOC in this study probably led to an overestimation of the detection limits. True detection limits are probably much lower. For instance, the detection limits for mixtures with montmorillonite and 1 wt.% C. lampblack fell at <1.1 wt.% TOC, yet evidence was clear that organic absorptions at.3 wt.% TOC were far stronger than the level of noise in the spectra. Variability in organic band-depth values contributed to the ambiguity in lower limits of detection. When a sample was measured multiple times with the FTIR, different organic-absorption strengths were recorded in each measurement (Figure 7). Although this was reported as an uncertainty in band depth, it was actually an uncertainty in the true organic content that fell within the beam of the FTIR. In other words, the range in banddepth values for a given sample was a reflection of sample heterogeneity and not precision or accuracy of the spectral measurement itself. Heterogeneity in the clay-organic mixtures meant that slightly different amounts of organic particles could be incorporated in the 1 2 mm area over which the FTIR measurement integrated, leading to spectral differences caused by an organic wt.% that was not the same as the bulk sample organic wt.% weighed out during preparation of the mixtures. This heterogeneity, which was probably due to aggregation and clumping of the mixture components, could lead to as much as ~5% difference (absolute) in continuum-removed reflectance values (Figure 7). As the organic wt.% of the mixtures decreased, the number of organic particles became small compared to the number of clay particles and homogeneity became even more difficult to achieve for small FOVs. The subset of ASD (shorter wavelength) measurements that were collected using a FOV equal to the full diameter of the

12 178 Kaplan and Milliken Clays and Clay Minerals a Band depth (3.42 μm) Montmorillonite X-intercept = -.79 R-squared = % confidence range of LLD b 95% Confidence range of LLD C. black 1%.5% % 1%.5% % 1%.5% % Montmorillonite Kaolinite Illite-Smectite 1.2 Figure 6. Estimates of lower limits of detection (LLD) of organics in organic-clay mixtures based on the absorption feature at 3.42 mm. (a) A 95% confidence estimate on the lower limit of detection (at 3.42 mm) is estimated by extrapolating the band depth vs. TOC trends (e.g. Figure 4b) with a linear regression. The estimated TOC value at which band depth is predicted to be zero is taken as the lower limit of detection; 95% confidence intervals on that regression are shown as red dashed lines. This plot shows a representative example based on the montmorillonite-sodium stearate mixtures with % carbon lampblack, which have a detection limit of <.7% TOC within the 95% confidence interval. (b) Bar graph showing the lower limit of detection ranges for the nine mixture types examined in the present study. As expected, detection of organics becomes increasing more difficult for low-albedo samples, particularly for the dark montmorillonite-organic mixtures. Heterogeneity (kaolinite mixtures) 1 wt.% organic 5 wt.% organic 1 wt.% organic.5 wt.% organic Reflectance (continuum removal) Reflectance (continuum removal) Wavelength (µm) Wavelength (µm) Figure 7. Assessment of heterogeneity in organic-clay mixtures. Each synthetic mixture was prepared in a sample dish multiple times and measured with the FTIR using identical procedures. Spectral variation is probably due to differing amounts of the organic compound within the ~1 2 mm beam of the FTIR, which gives rise to a range in band-depth values for a given mixture. The example shown is for the kaolinite-sodium stearate mixtures (continuum removed from mm).

13 Vol. 64, No. 2, 216 Reflectance spectroscopy to detect and quantify organic compounds 179 sample cup (~9 mm) show less band-depth heterogeneity than when using a smaller spot size (e.g. ~1 mm). The spectral variability observed for the larger FOV was on the order of ~1% absolute reflectance or less, whereas spectra for the smaller spot sizes had variability on the order of ~5% (similar to the FTIR measurements). DISCUSSION Reflectance spectroscopy as a tool for organic detection Near-infrared reflectance spectroscopy has many advantages as a combined detection method for organics and minerals: non-destructive and rapid measurements, the ability to operate in a passive mode (using incident solar radiation), and the ability to do in situ measurements and preserve spatial context over large areas. Yet, currently no consensus exists as to the lower limit(s) of detection of organics using this method or standardized spectral parameters that can provide accurate quantification of organics irrespective of bulk mineralogy, chemistry, or geologic/burial history. Sediment properties such as albedo, hydration, grain size, and texture are known to influence reflectance spectra, and the effect of organic properties such as composition and organicmineral relationships are areas of active research (Reeves, 212; Herron et al., 214). These variables tend to change from one depositional environment to the next, and recent studies have demonstrated strong basinspecific relationships between reflectance spectra and TOC (Adams et al., 25; Herron et al., 214). In this context, a foundation-level laboratory approach that explores the influence of a range of variables can provide the basis for making sense of complicated natural samples. This is particularly true given that natural organic-bearing samples often have very different H/C ratios, degree of maturation, diagenetic histories, organic abundances and compositions, and are associated with different mineral assemblages. The parameter space covered by the organic-clay mixtures in terms of albedo, hydration, and TOC was meant to span a range that may be characteristic of natural samples that will be used in future studies. The albedo of the samples ranged from ~1 8% (.1.8) at 1.7 mm, the clays contained ~ wt.% H 2 O, and TOC values spanned.3 7 wt.%. Carbonaceous chondrite meteorites and potential C-type asteroid parent bodies are notoriously dark materials that often have maximum reflectance values between 5 and 15% in the near infrared (Johnson and Fanale, 1973; Chapman et al., 1975). Carbonaceous chondrites also contain hydrated minerals, including clay minerals (Barber, 1981; Rubin et al., 27), and up to 5 wt.% organic carbon (Pearson et al., 26). Although carbonaceous chondrites are dark, they fall roughly within the ranges of the parameters that are tested in this study, leading to the possibility that this method could be used for in situ study of carbonaceous asteroids (e.g. with the VIS-IR spectrometers that have been selected for the Japan Aerospace and exploration Agency (JAXA) Hayabusa-2 mission and NASA s OSIRIS-REx missions) as well as laboratory study of meteorites. Note, however, that the actual clay minerals and formation conditions pertinent to carbonaceous asteroids/meteorites differ from those explored in the present study. Specifically, although a 7 Å clay (kaolinite) was examined here, the dominant clay type in many carbonaceous chondrites is serpentine, including Ferich varieties such as cronstedtite. The octahedral cation probably has little (if any) effect on the parameters and absorptions examined here, but the structural properties of the clay (e.g. curved serpentine morphologies), how these relate to trapping and binding of organics, and the nature of organo-clay complexes in C chondrites may affect organic absorptions in meteorite reflectance spectra. In addition, organic compounds in carbonaceous meteorites are quite variable and much more complex than the simple compounds examined here. Additional studies are clearly warranted to fully understand detection limits and quantification of organics in carbonaceous meteorites/asteroids, but the results presented here demonstrate that band depth-toc trends maybelinearandthatssaspectrashouldbeusedto minimize effects due to low albedo. Many materials on earth (soils, drill cores) also fall within the parameter ranges examined here, and orbital observations of Mars suggest that much of the surface falls within these albedo and hydration levels (Kieffer et al., 1977; Milliken et al., 27; Bell et al., 28; Audouard et al., 214). Any organic-bearing materials on Mars, however, are at best likely to be at the very low end of the TOC wt.% range examined here (Summons et al., 211). The results presented above demonstrate that hydration had little influence on band depth for the range of water contents studied, despite the major organic absorptions being superposed on the strong 3 mm water features. Albedo, on the other hand, exerted a strong control on absorption bands in reflectance spectra. This effect was largely mitigated by converting from reflectance to single scatter albedo, as discussed by other workers (Clark, 1983; Milliken and Mustard, 27). It should be noted, however, that highly hydrated samples (e.g. waterlogged sediments or suspensions) would saturate the reflectance values in the entire 3 mm region, probably removing any evidence of the fundamental CH stretch. Though such conditions are unlikely for meteorite or Martian samples, this may be a factor in the exploration of icy bodies or the analysis of wet terrestrial drill cores. One important variable that was not thoroughly explored in this paper is organic composition/chemistry. Sodium stearate was chosen as an adequate and easy to work with spectral representative of an aliphatic carbon compound, though it is of course not relevant to most