MP150527 MITRE PRODUCT
Variations in Infrared Spectroscopic Signatures
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ii Executive Summary
This report summarizes the findings of a thorough literature search and elucidates key physical phenomena related to stand-off spectroscopy of low-abundance samples measured in realistic en- vironments. The goal of this report is to assist key stakeholders of the Standoff Illuminator for Measuring Absorbance and Reflectance Infrared Light Signatures (SILMARILS) program in un- derstanding the underlying phenomenology that can impact standoff spectral measurements. The specific details of reflectance spectra depend on (1) intrinsic material physical properties that govern the light/matter interactions in that material and (2) extrinsic geometric properties of the material, its surroundings, and the illumination and viewing angles. Intrinsic effects ex- plored within this report include material properties that are dependent on thermodynamic state and molecular level interactions (specifically those due to adsorption onto a substrate, varying de- grees of hydration, and interactions within solutions). Important extrinsic factors identified in the literature review include particle size effects, optically thin material mixtures, sample morphology dependence, and illumination and viewing geometries. Key findings include:
• Thermodynamic State: When temperature or pressure variations result in either molec- ular conformational changes or phase changes, the shape and location of spectral features can change dramatically. For mixtures of reacting species, the temperature dependence of the reaction’s equilibrium constant will lead to adsorption spectra variations driven by the mixture’s changing composition. Materials with anharmonic intermolecular potentials expe- rience shifts in spectral feature locations and changes in feature widths as temperature and pressure vary. • Molecular Level Interactions: All forms of molecular level interactions introduce changes in the location and shape of a compound’s spectral features. Additionally, the novel inter- actions provided by the secondary species (whether the substrate, solvent, or sorbed wa- ter molecules) can lead to the appearance of new spectral features or to the disappearance of some features due to bonding geometries. Relative concentrations of the participating species affect both the quantitative and qualitative nature of spectral feature variations. • Extrinsic Factors: The scattering optical depth of a sample depends on the density and spatial-scale of inhomogeneities in the medium. The absorption optical depth depends on the total amount of the medium that light waves propagate through. Higher density, smaller-scale inhomogeneities tend to increase overall sample reflectance, while the corresponding change in spectral feature depth and width depends on whether the material is optically thick or thin on the spatial scale set by the inverse of the inhomogeneity density. Non-monotonic fea- ture depth/width changes can occur as the inhomogeneity density varies monotonically. For mixtures involving optically thin component media, the mixture spectrum typically evolves non-linearly between the pure component spectra as a function of mixture composition and it is not uncommon for the the mixture spectrum to not be bounded by the component spec- tra over at least some wavelength range. Variations in spectral contrast and overall spectral shape typically are present as illumination and viewing angles change.
Finally, we review the existing literature on spectral signatures of specific compounds of particular concern from a security-related perspective.
iii Table of Contents
1 Introduction ...... 1 2 Spectral Variations due to Extrinsic Factors in One-Dimensional Planar Geometry . . . .3 3 Spectral Signature Variations: Examples ...... 7 3.1 Intrinsic Factors ...... 7 3.1.1 Thermodynamic State ...... 8 3.1.2 Molecular Level Interactions ...... 11 3.1.2.1 Adsorption ...... 11 3.1.2.2 Hydration ...... 14 3.1.2.3 Interactions in Liquid Solutions ...... 18 3.2 Extrinsic Factors ...... 20 3.2.1 Particle Size Effects ...... 20 3.2.2 Optically Thin Samples in Mixtures ...... 21 3.2.3 Other Sample Morphology Effects ...... 23 3.2.4 Illumination and Viewing Angles: Sample BRDF ...... 24 4 Spectral Signatures of Example Explosive and Chemical Warfare Agent Related Com- pounds ...... 25 Appendix A Planar Slab Reflectance: Definitions, Notation, and Derivation ...... 31
iv 1 Introduction
In remote sensing applications, the infrared (IR) spectroscopic identification of a given molecu- lar compound typically relies on matching the measured spectrum of some unknown substance against pre-measured template signatures of know materials. Usually, the number of such template signatures used for a given compound is relatively small and represent measurements on a limited number of compound samples under a limited set of conditions, which may or may not be well controlled or characterized. This presents a potential problem: the spectral signatures of a given substance depends on a myriad of factors, and having only a limited number of template spectra, especially over a limited or unknown range of salient parameters, could lead to mischaracterization or even missed detections of a material of interest. The degree to which spectral signatures can vary depends on the nature of the sample under con- sideration. For example, in the case of macroscopic solid or liquid samples that are optically thick or in the case of non-interacting gas phase samples under standard conditions, a limited number of template spectra taken on similar samples may provide “close-enough” examples to allow de- tection over a wide range of conditions encountered in situ. (Accurate quantitative analysis and characterization of in situ samples based on limited sets of experimental reference spectra is likely another story, however.) On the other hand, when the sample quantity is small or the material ex- ists in a form that is optically thin (i.e., translucent or transparent) or experiences molecular-level interaction with its surroundings, a wider range of spectral variations is likely to occur. In the context of detecting and identifying trace and residue amounts of compounds of interest, it is this latter case that is most relevant. Complicating matters here is the fact that some of the causes of spectral variation in the low-abundance limit can depend on a sample’s surroundings. In such cases, detection via simple template matching may be woefully insufficient, particularly when interactions between a sample and its surroundings induce shifts in the wavelength location of the sample’s characteristic spectral features. Spectroscopic detection of trace quantities can therefore be expected to be a challenging endeavor due not only to the limited signal afforded by the small amounts of target analyte present but also on the wider spectral variability that can be exhibited by trace samples. The main goal of this report is to provide an overview of various physical mechanisms that can produce such spectral signature variations, paying specific attention to mechanisms that may be of particular import to signature variations in the trace quantity limit. Because spectral signatures are determined by light/matter interactions that depend on both molec- ular properties and bulk-sample geometric factors, factors influencing spectral variations can be either intrinsic or extrinsic in nature. Intrinsic factors are those that influence how light fundamen- tally interacts with a given substance. This interaction is quantitatively described by the medium’s complex refractive indices (or, optical constants),n ˜ = n + iκ. The real part, n, of the refractive in- dices describe an electromagnetic (EM) wave’s phase velocity in the medium while the imaginary part, κ, is related to the wave’s in-medium amplitude attenuation rate. Then ˜ are wavelength (λ) dependent quantities and are explicitly related to a medium’s quantum mechanical energy eigen- states and to the rate at which transitions between these states occur [1]. As such,n ˜ will depend not only on a substance’s molecular composition but also on its molecular geometry. So, e.g.,n ˜ differs between solid, liquid, and gas phases [e.g, 2, 3] and between different molecular configuration states within a given phase [e.g., 4, 5]. Chemical or physical interactions between a molecule and its surroundings alter the quantum states of the interacting media and, hence, their respectiven ˜.
1 The primary extrinsic factors of relevance are the geometry of both the target sample and its sur- roundings: EM waves scatter due to inhomogeneities inn ˜ [6]. Such inhomogeneities can be due to interfaces between two distinct media, fluctuations in a medium’s density, microscopic com- positional variations, defects in a solid’s crystal lattice, amongst other causes. The specifics of a medium’s geometry as it determines and relates ton ˜ heterogeneities plays a significant role in setting the magnitude and spatial distribution of the scattered EM fields. Factors such as parti- cle size and shape, internal inhomogeneities, etc. can all play a significant role in a medium’s spectral signature. The spatial distribution of the scattered fields, in turn, determine a medium’s bidirectional reflectance distribution function (BRDF), which is of importance in reflectance and emittance spectrometry[e.g., 7]. When the target sample is optically thin, its surroundings can significantly influence its spectral signature with the spectra of such optically-thin“mixtures” de- pending on the relative values of the components’n ˜ and the overall geometry. For a trace quantity sample, the likelihood of it experiencing significant interactions with its sur- roundings (altering itsn ˜) while also existing in an optically-thin morphological state (increasing the importance of the surrounding’s properties on the resulting scattering) increases. As such, the impact of both intrinsic and extrinsic factors on the spectra of low-abundance samples can be particularly significant. In the following, we will provide specific examples of how both types of factors alter a medium’s spectral signature while also highlighting general trends that occur across these examples. Throughout our emphasis will be on providing a qualitative understanding of the physics underlying the observed phenomenology. The remainder of this report is organized as follows. In §2 we examine the simple, idealized case of one-dimensional planar media. We do so for two reasons. One, to demonstrate that even in this simple geometry–and only considering the impact of extrinsic factors—there is already a rich phenomenology of spectral signature variation. Two, to illustrate general principles that connect extrinsic media properties to spectral signature variations. These general principles will continue to hold in the case of more complex sample geometries. We then turn to consideration of these more complex sample geometries and their spectral signature phenomenology in §3 by highlighting examples from the literature that illus- trate how various factors (both intrinsic and extrinsic) can impact the observed spectra in various material phases. In §4, we provide summaries of the literature regarding the spectral signatures of some compounds of specific security-related concern and the variations in these signatures that have been documented.
2 2.255 2.250 I0 IR 2.245 2.240
n 2.235 2.230 ~ 2.225 n0 2.220 2.215 ~ 10-1 d n1 10-2 ~ n -3 2 10 I T 10-4 0.9 1.0 1.1 1.2 1.3 1.4 1.5 λ (µm)
Figure 1: Basic planar slab media geometry utilized to Figure 2: The set of refrac- demonstrate spectral signature variations with extrin- tive indices used for medium-1 in sic factors. the calculation of planar slab re- flectances.
2 Spectral Variations due to Extrinsic Factors in One- Dimensional Planar Geometry
Many of the spectral signature variation trends produced by extrinsic factors can be seen even in the simple case of infinite planar media. The geometry of this idealized case is shown in Figure 1 (see also Figure A-1 for further details). Media heterogeneities in this geometry occur only in the vertical direction and consist of interfaces between otherwise homogeneous layers with individually specified thicknesses; each layer is infinite in extent in the horizontal plane across and out of the page. Further, the stack of media layers is restricted to the lower half of the vertical plane. Incident light originates from the upper-half plane, which is filled with an incident medium with optical constantsn ˜0 = 1 (i.e. air). For simplicity, we will consider plane-wave incident radiation with a specified medium-0 wavelength of λ0 and whose propagation direction makes an angle θ0 with the media stack’s surface normal. In this section, we will utilize this geometry to highlight the general principles that determine how extrinsic factors affect the qualitative nature of a medium’s spectral signatures. These general principles will continue to be applicable in more complex, realistic sample geometries.
Here we will focus on a sample’s spectral reflectance, R ≡ IR/I0 where I0, IR are the incident and reflected EM-waves’ spectral energy flux components normal to the interface (dimensions of [en- ergy area−1 time−1 wavelength−1 ]; note also that there is an implicit λ-dependence on all these quantities). To start, we will first examine the simplest case of a single layer of a homogeneous medium with some finite thickness, d, on top of an infinitely thick substrate (i.e. the exact case shown in Figure 1). The layer and substrate have λ-dependent optical constantsn ˜1 andn ˜2, re- spectively. For simplicity, we will only consider the case of incoherent reflection1. The sample’s incoherent R in this particular case (see Appendix A for details) is given by:
R + R e−2αd T T − R2 R 01 12 01 10 01 = −2αd . (1) 1 − R01R12e
1 When d is such that an EM-wave packet’s phase coherence can be maintained across the layer, coherent interference occurs between transmitted and reflected waves within the sample layer, altering the overall reflectance.
3 0.26
0.24 d =5 mm
(a) 0.22
(a) 0.20 (b) R (c) d =0.2 mm (b) 0.18
0.16 d =0.05 mm
(c) 0.14 0.9 1.0 1.1 1.2 1.3 1.4 1.5 λ (µm)
Figure 3: Reflectance of a planar slab as a function of slab thickness.
The R jk and Tjk are the single-interface flux reflectance and transmittance coefficients at the bound- ary between incident medium j and transmitting medium k. Both are θ0-dependent quantities. At normal incidence (θ0 = 0), these coefficients are given by: 2 2 n˜ j − n˜k nk 2n ˜ j R jk = , Tjk = . (2) n˜ j + n˜k n j n˜ j + n˜k The attenuation coefficient α determines the attenuation rate suffered by an EM-wave per per- pendicular distance it travels in medium-1 and is primarily determined by κ1. The attenuation coefficient is also θ0-dependent, but at normal incidence α = 4πκi/λ0. From these expressions we can highlight several basic principles. The reflectance of an EM-wave only occurs at boundaries wheren ˜ j =6 n˜k, with R increasing for greater differences between the optical constants. This is essentially just the statement in this particular geometry of the general principle that scattering occurs due to inhomogeneities inn ˜. Within each homogeneous region, scattering does not occur, but the wave experiences attenuation when α =6 0. Additionally, R has an explicit dependence on R12; put another way, the overall reflectance of a sample depends on its surroundings, not just on properties of the sample2. The extent to which the surroundings end up influencing R will depend on the specific geometry andn ˜-values involved. Note also that even if R12 were not influenced by a change in adjacent media, the overall R even in this simple geometry is neither an additive or multiplicative function of the individual component reflectances.
For specificity, we will illustrate how R changes under various specified geometries by takingn ˜1 equal to the set of optical constants shown in Figure 2. This particular set ofn ˜ is synthesized from the sum of three Lorentzian resonances whose central λ-values occur in the wavelength range shown plus a background dielectric constant specified so that n differs significantly from unity. To start, we consider R in the case medium-1 is surrounded on both sides by air (i.e.,n ˜0 = n˜2 = 1). Figure 3 provides examples of how R changes with d for this particular set ofn ˜. Case (a) in Figure 3 illustrates R when d is such that αd 1. In this case medium-1 is optically thick, meaning that light waves are attenuated essentially to zero amplitude before encountering a second interface. The only scattering occurs at the media 0 → 1 interface and the resulting R = R01 (as can be seen
2 This is a basic property of the the EM-scattering problem in general: the governing Maxwell Equations are partial differential equations whose solutions are conditioned on specification of boundary conditions.
4 0.26 (a) 0.24 1.45 1.44 (b) 1.43 1.42 (c)
0.22 0.24 2 1.41 n d =5 mm 1.40 1.39 0.20 1.38 (a) 10-1 R 0.22 0.18 10-2 θ0 2 0 10-3 0.16 ◦ 45 ◦ 0.20 -4 R 10 0.9 1.0 1.1 1.2 1.3 1.4 1.5 d =0.2 mm 60 ◦ 0.14 λ (µm) (b) 1.35
) 0.18
◦ 1.30 0
( 1.25 R
/ 1.20
) 0.16
0 1.15
θ d =0.05 mm
( 1.10 R 1.05 (c) 0.14 0.9 1.0 1.1 1.2 1.3 1.4 1.5 0.9 1.0 1.1 1.2 1.3 1.4 1.5 λ (µm) λ (µm)
Figure 4: Reflectance of a planar slab at various Figure 5: Impact of changing the refractive in- illumination angles. dices of medium-2 on the reflectance of the planar slab sample.
by taking αd → ∞ in Equation 1). In our particular case, n1 κ1 so the spectral character of R01 essentially mirrors that of n1 which does not vary strongly with λ. Because of this, R is essentially constant in case (a) and certainly does not exhibit any indication of typical spectral absorption features. We should note that there are cases where κ & n [e.g., 8–10]; in such cases the first- interface reflection coefficient can exhibit more spectral contrast since κ varies much more rapidly than n with λ. Cases (b) and (c) illustrate the behavior of R when a second interface is present at an optical-depth αd . 1. Scattering off the second interface produces additional reflected flux, increasing R. Most of the λ-range considered here is in this regime for the d-values specified. However, around the central λ of the strong feature near 1.18 µm, medium-1 remains optically thick even for case (c) (d = 0.05 mm). Apart from the increased R, the other qualitative difference between these and case (a) is the appearance of more typical absorption features in the R spectra. These features result from the differential attenuation experienced at differing λ as the wave propagates through medium-1 and scatters back off the second interface. The width and depth of absorption features narrow and decrease, respectively, as the layer’s d decreases. However, as R12 and R10 do not depend on d, the overall increase in R with d between cases (b) and (c) results from the decrease in absorption occurring in the wings of the resonances as d decreases.
Variations of R with respect to incidence angle, θ0, also occur in this planar geometry. (Given the idealized, purely specular nature of the scattering surfaces, the view-angle dependence is a delta- function of the incidence angle; i.e., R =6 0 only at a view-angle of θ0). The upper panel of Figure 4 shows the polarization-averaged R at several different θ0 for a slab thickness of d = 0.02 mm. The ◦ ◦ ◦ θ0 = 0 case here is the same as case (b) in Figure 3. The increase in reflectance at 45 and 60 ◦ over that at θ0 = 0 is characteristic of R behavior in this planar interface geometry. Note, further, that there is a spectral dependence in the relative increases of R. Specifically, R within absorption bands increases more rapidly than in the continuum regions, as highlighted in the lower panel of Figure 4. This results in a decrease in band depth at these θ0 and a reduction in spectral contrast. More generally, this example shows that one should not expect a sample’s spectrum to maintain a fixed relative shape at varying illumination and view angles. Figure 5 demonstrates one way in which a sample’s surroundings can alter its light-scattering properties: via changes in surrounding media optical properties. Specifically, Figure 5 shows the impact of changing the optical constants of the substrate fromn ˜2 = 1 to the set shown in Figure 5’s inset. The three cases shown in Figure 5 correspond to the cases shown in Figure 3. In case (a), medium-1 is still optically thick and the underlying substrate makes no difference to
5 0.7
(a) 0.6 N =1
0.5
(b) (a) 0.4 (b) N =4 R (c)
0.3
(c) 0.2 N =10
dtotal =250 µm 0.1 0.9 1.0 1.1 1.2 1.3 1.4 1.5 λ (µm)
Figure 6: Impact of varying the number and thickness of multiple planar slabs on reflectance. Here, as the number of medium-1 slabs increase, the individual slabs thicknesses decrease to maintain a constant total thickness of medium-1 present.
the scattering properties. The case (a) R in both Figures is therefore the same. At lower optical depth, the substrate’s properties begin to have an impact and the case (b) and (c) reflectances are altered. The mismatch betweenn ˜1 andn ˜2 in Figure 5 is less than in Figure 3, reducing the single-interface reflectance, R12, at the bottom of medium-1. This in turn reduces R overall per equation (1) and as seen in comparing Figure 5 to Figure 3. Another qualitative difference appears in Figure 5 in the altered shape of the λ = 1.35 µm band. The newn ˜2 has an absorption feature that partially overlaps thisn ˜1 band, producing the notched morphology in the combined band. While this particular example was intentionally contrived, it still illustrates the point that when a sample’s surroundings have optical constants that are similar to the sample’s or that change rapidly over λ- ranges where the sample’s diagnostic features occur, the potential for significant changes in the feature’s appearance and strength will be present. Finally, we consider a slight modification to the planar sample geometry and consider multiple interfaces. Figure 6 examines the reflectance of three different cases where stacks of medium-1 slabs are surrounded and interspersed with layers of air. The three cases differ in the number, N, of medium-1 slabs present. However, the summed thickness of all the medium-1 slabs is the same in each case (i.e., the total amount of medium-1 present is constant). For N > 1, R is calculated using the so-called transfer-matrix method that generalizes the calculations of R and T to the multi-slab case [see, e.g., 11]. As N increases, the individual slab thickness decreases, altering the relative importance of scattering and absorption in each layer: scattering occurs at each media interface while the single-slab absorption decreases with d. The net effect is for R to increase overall with increasing N even within absorption features at λ-values where individual slabs are not optically thick. In such a regime, R increases rapidly with N as seen in Figure 6. While the absolute R level of absorption features increases with N, the relative depth and width of features vary in a more complicated manner. For the cases considered in Figure 6, the relative depth of each feature increases with N and there is a narrowing of each feature in the N = 10 case. However, for even larger N, a decrease in both width and depth of the features would be observed as scattering becomes increasingly dominant. The overall increase in R and varying feature morphology seen here carries over into more realistic cases with analogous phenomenology observed as a function of particle-size in particulate media, for example.
6 R.L. Hudson et al. / Icarus 243 (2014) 148–157 151
amorphous C2H4 ice. By analogy with ethane, we interpret the mid- Of the six hydrocarbon ice phases examined in this paper, dle spectrum as that of a low-temperature, metastable crystalline amorphous ethylene was the most difficult to prepare. Deposition 1 form of ethylene that cannot be achieved by warming but only rates of 1 lmhÀ or lower and temperatures below 20 K were by direct deposition. Fig. 4 shows expansions of several ethylene needed for reproducible amorphous C2H4 ices. Samples grown bands for all three phases at 20 K. Warming an amorphous C2H4 above 20 K at that same rate were at least partially crystalline, 1 sample gave distinct spectral changes near 35 K and again near and ethylene ices grown faster than a few lmhÀ were partially 50 K, as seen in Fig. 5. The first change produced a mixture of the or fully crystalline regardless of the temperature of formation. two higher-temperature crystalline forms, while the second gave The possible influence of deposition speed in determining an ice’s an almost-completely high-temperature crystalline phase, each phase has been noted before (Jacox, 1962; Rytter and Gruen, change being irreversible. The spectral changes corresponding to 1979), and we believe that the present work conclusively demon- warmings below 50 K were somewhat subtle for most of ethyl- strates the influence of condensation rate for the case of solid 1 ene’s IR features, as seen in the 4500-cmÀ region of Fig. 5, but ethylene. 1 the small 822-cmÀ band shown was found to be a very sensitive Metastable ethylene was another case in which deposition rate indicator of phase changes. All things considered, the spectral fea- was important. The only published spectra for this ice phase of tures we observed for metastable and crystalline ethylene were which we are aware are those of Jacox (1962), although others similar to those reported in the literature. have described their own results. We found that the key to
154 R.L. Hudson et al. / Icarus 243 (2014) 148–157
Fig. 4. Expansion of selected spectral regions of C2H4 ices showing details for each solid phase. The ice thickness in each case was about 1 lm. The crystalline ice (top) was 1 1 created by a slow deposit ( 1 lmhÀ ) at 60 K and then cooled to 20 K. The metastable C2H4 ice (middle) was created by a fast deposit ( 60 lmhÀ ) at 20 K. The amorphous 1 ethylene ice (bottom) was created by a slow deposit ( 1 lmhÀ ) at 12 K and then heated to 20 K.
Fig. 5. IR spectra of a 1- mCH ice grown at 12 K and warmed to the temperatures indicated. l 2 4 Fig. 8. Calculated values of n and k for the three crystalline phases of ethylene at 20 K. In the top panel, the phase-specific values of n670 from Table 1 have been subtracted 1 from n before scaling by the factor shown. Because they would otherwise fall outside the given plotting range, n values in the 850–800 cmÀ region for all three phases were (a) shifted by an additional 0.05 before scaling. (b) À
crystalline acetylene with a0 and A0, respectively, see Hudson et al. 4.2. Comparisons to previous work (2014). Figure 7: (a) Temperature evolution of amorphousTables 2 and 3ethylenesummarize our spectral-intensity(C2H4) ice calculations formedComparisons at 12 ofK our and results to warmed. published work are considerably for ethane and ethylene. The first column of each table lists hindered by a lack of experimental details in most of the earlier A phase transition to the crystalline solid conformationselected spectral peaks. Graphs occurs of each peak’s around height (absorbance) 45 K. (b)work. C For2 example,H4 ice the A absorbance0 values of our Table 3 are comparable as a function of ice thickness gave Beer’s-law lines whose slopes to two values published by Dows (1966), but the density assumed as a function of solid configuration at 20 K.are Reproduceda0/ln(10). The second columns from in Tables Figures 2 and 3 list 5a0 values. and 8by of the[12]. latter is unknown, precluding a meaningful quantitative Following calculations of optical constants, plots of k were exam- comparison. The only published mid-IR optical constants of which
ined for peak positions, and these are listed in the third columns we are aware for C2H6 are those of Pearl et al. (1991) for crystalline of Tables 2 and 3, followed by columns with calculations of a from ethane at 30 K. Our n-and-k results for amorphous ethane ices a v~ 4pv~k v~ . Finally, integrations of a and a0 over the ranges crystallized by warming from 12 K, and then recooling to 30 K, ð Þ¼ ð Þ $ listed in each table, and application of Eqs. (1) and (2), gave the are essentially the same as those of Pearl et al. (1991), but crystal- 3 Spectral Signature Variations:absolute and apparent band strengths, ExamplesA and A0, respectively. The line ices grown at 60 K and then cooled to 30 K gave intensities differences, particularly for ethane, between a and a0, and between that were up to a factor of two greater. Relevant details concerning A and A0, vary considerably and are difficult to predict in advance, thickness measurements are missing from Pearl et al. (1991), again emphasizing the need for optical-constants calculations for preventing a more-careful investigation. Perhaps the best compar- accurate intensity values. ison is Fig. 9, which shows our crystalline-ethane absorption Our discussion in §1 highlighted the generic physics that underpin the two categorical sources of spectral signature variations: variations in a material’s properties that changen ˜ and variations in the geometry of the material sample and its surroundings that alter the overall scattering characteristics. Variations inn ˜ are due fundamentally to changes in the quantum mechanical states available in a medium and the states’ respective occupation numbers. Variations due to geometric factors fundamentally result from the fact such changes alter the boundary conditions of the EM-wave scattering problem. We also have just seen in §2 that significant variations in spectral signatures can be produced just by solely changing geometric factors in the simplest case of one-dimensional planar media. With this general foundation in place, in this section we will discuss examples of how specific changes in a medium’s intrinsic and extrinsic properties lead to spectral signature variations, focusing particularly on factors than can be expected to have significant influence on the spectral variations in trace-quantity samples.
3.1 Intrinsic Factors
As already discussed, a material’s refractive indices are directly tied to its spectrum of quantum states and their occupation numbers. Multiple factors influence the exact energy levels available while its temperature typically controls the occupation numbers of these available states From this point of view, intrinsic factors influencing a material’s spectral signatures are those factors that alter a substance’sn ˜ via changes in its quantum mechanical state. Such factors include the thermodynamic state of a material and interactions with its surrounding environment that lead to changes in the states available to the overall system, whether by altering existing states or creating new states that come about due to such interactions.
7 192 P. Majewska et al. / Chemical Physics 354 (2008) 186–195
Table 5 Characteristics of modes for 7TPB with transition dipole moments close to be parallel or perpendicular to the long axis of dimer.
1 a b Calculated frequencies (cmÀ ) Assignment Experimental frequencies Calculated angle (deg) Dichroic ratio 1 c solid state (cmÀ ) D =(A /A ) Monomer Dimer Monomer Dimer || \
ar ar 852 852 c (CH) I + d(C1OC2) + m (CC) II 853 79 96 2.9(862–845) ar 947 943; 944 m (CC) I + m(NCS) 928 15 11 5.5(956–895) ar 1152 1151; 1152 d (CH) II + s(C14H2) 1120 52 87–89 1.7(1130–1110) 1514 1513; 1514 dsci(CH2)+das(CH3); das(CH3) 1456 79 86 1.2(1461–1454) ar ar ar 1551 1549 m (CC) II + d (CH) II + d (CH) I 1509 9 4 5.3(1520–1506) ar ar 1665 1663; 1665 m (CC) II + d (CH) II 1610 11 3–11 4.3(1640–1580) 2179 2202; 2208 m(NCS) 2109 19 9 3.3(2300–1900) 3037 3038 ms(CH3) 2868 9 6 1.3(2875–2860) 3052–3105 3064–3110 mas(CH2), mas(CH3) 2927 83–85 83–87 1.6(2990–2885) ar 3225 3226 m (CH) I 3104 86 90 1.2(3120–3090)
a Without scaling. b Angle between long axis and transition dipole moment vectors. MS. Zakerhamidi, H. Rahimzadeh / Journal ofc MolecularValues in Liquids parenthesis 172 (2012) written 41 as–45 a subscript give range of absorbance used to calculations43 of the D parameter.
Table 2 (a) Fitting parameters for the average refractive index and birefringence of the studied LCs. 0.8 1.62 0.6 n(iso) o o – – – – – – α (140 ) 74 C C3 B C5 C4 B C5 C7 B C5 1.6 o n(o) 68oC A 1.6536 1.6496 1.6493 α (50 ) 4 1 4 1 4 1 0.6 B −3.63×10− (K− ) −3.64×10− (K− ) −3.66×10− (K− ) 1.58 n(e) 66oC Δn 0.154 0.153 0.178 0.4 o 64oC β 0.1858 0.2318 0.2518 1.56 o 0.4 62 C 1.54 50oC Absorbance Absorbance 0.2 1.52 1 0.2 Refractive indices no 〈n〉− ΔnoQ: 11b ¼ 3 ð Þ 1.5
After subtracting Eqs. (11a) from (11b), Eq. (1) for the order 0 1.48 0 parameter (Q) can be acquired. This method can be directly applied 30003102500 3302000 3501500 3701000 390500 -1 2250 2200 21502100 2050 2000 1950 to the birefringence data rather than to refractive indices. In this WavenumberT (K)(cm ) Wavenumber (cm-1) approach, the orientational order parameter is calculated by means Fig. 5.(b)Comparison of the IR absorption spectra measured at 25 °C for the angles of of the Vuks assumption [28]: polarizer corresponding1.62 to the maximal and(a) minimal absorbance at 140 and 50°, Fig. 7. The temperature evolution of the(b)m(NCS) band by passing from the isotropic respectively. n(iso) to the crystalline state (via smectic A) measured at the angle of polarizer equal to 140°. 2 2 1.6 Δα n n n(o) S e − o Figure 8: Temperature driven conformational changes and n˜ in liquid crystals. (a) shows the evolution 2 12 tion as a precritical phenomenon with a tendency for perpendicu- α ¼ 〈n 〉−1 ð Þ 1.58 o n(e) of ordinary and extraordinary90 angle α n( )in the liquid crystallar arrangement C7-B-C5 of(λ molecules.-value This was event unspecified); can also be discussed increasing in 120 1 60 T decreases1.56 crystal ordering, reducing the degreeterms ofbirefringence. of the nematic ordering At whichT ≈ is postulated380 K, a in phase a very narrow change where ∆α αII−α is the anisotropy of polarizability and α is th th ðÞ¼ ⊥ 0.8 temperature range [13]. We also do not observe signs of transition mean molecular polarizability. To determine Δα , plot of linear part α to the1.54 isotropic state occurs. (b) Evolution of absorbanceto the smectic spectra phase from of the an overcooled liquid crystal isotropic 7TPB phase. However, near ν ≈ 2 2 0.6 3 ne −no T 150−1 30 it cannot be excluded that the ordering of molecules in the smectic of ln ðÞ2 2 against ln 1− T can be extrapolatedÀÁ to T=0 K. 2100 cm . The blue-shift and evolution in the relative strength of the two features accompanies a ne 2no −3 c 1.52
Refractive indices phase and in the solid state is identical, similarly to 6OTOLT [7]. þ 0.4 The intercept at T=0 K, where . completely ordered structure exist change from crystalline to isotropic phase. ReproducedA question from now Figure arises related 1 of to [5]the preferential and Figure orientation 7 of of[20], 0.2 Δα Δα 1.5 the molecules with respect to the surfaces of the windows. In the i.e. S=1, gives the value of scaling factor α . Assuming that α re- respectively. fi 180 0 case of the previously studied 6OTOLT [7], the molecules were en- mains xed for all the temperatures andÀÁ substituting this valueÀÁ into 1.48 Eq. (12), one can obtain values of order parameter at different tem- 300 320 340 360 380 400 tirely randomly distributed in the two-dimensional space parallel peratures. Thus, the smaller scaling factors and the larger values of T(K) to the windows, which was reflected by an increase in absorbance 2 2 by a factor equal to 3/2 when going from the isotropic phase to the ne −no 3.1.1 Thermodynamic State 2 render higher values for microscopic order parameter. 210 330 〈n 〉−1 (c) smectic and solid phases. In the present case we observe a marked 1.61 drop in absorbance, shown in Fig. 9. Close to the transition temper- n(iso) 3. Experimental T ature one observes an anomaly, i.e. aP rather deep minimumn that A material’s1.59 temperature,240 th300, and density,n(o) ρ (or,can bealternatively, interpreted as due pressure, to the appearance) influences of a critical pretransi- ˜ values 270 tional state of the nematic type. 3.1. Materials in several1.57 ways. Variations in temperaturen(e) play both direct and indirect roles in modifyingn ˜. The absorbance of the band ascribed to the transition between i Fig.Changes 6. Polar plots in of theT relativealter changes the in occupation absorbances in the regionsnumbers 2300– in various quantum mechanical states, with corre- 1 th 1 and j states caused by electromagnetic radiation is expressed by The liquid crystalline materials (cyano-benzoate liquid crystals) 1900 cmÀ 1.(d55) and 885–800 cmÀ (j). the equation were synthesized in the Institute of Chemistry of the Military Techni- sponding changes inn ˜ [13, 14]. On the other hand, Tth indirectly affectsn ˜ via molecular confor- Let us mention1.53 that in the present system we do not observe any 2 cal Academy, Warsaw, Poland. The chemical structures of these com- hmij 8p 2 2 tracesmation of the and dichroism phase detected changes previously in pure for 6OTOLTmaterials[7].As [5, 12,A 15–24]l andcos viah; its influence on the equilibrium c 2 ij pounds are shown in Table 1. The nematic to isotropic transition 51 ¼ h j j can be seenRefractive indices 1. in Fig. 9 we find a sharp decrease in intensity at temperatures (Clearing temperatures) for these nematogens were constants for reacting materials [25, 26]. Varying P will alter a medium’s density and, hence, the 66 °C, i.e. markedly above the crystallization temperatures where lij is a matrix element of the dipole moment operator and h measured using differential scanning calorimetry (DSC) and polarized (62.5medium’s°C).1.49 mean intermolecular distances. For materialsthe angle between with the anharmonic direction of the intermolecular electric field vector and interac- the microscopy methods and are given in Table 1. Further cooling leads to some increase in intensity and at 62 °C transition dipole moment vector. In the case of an isotropic liquid, tion potentials,1.47 such changes in mean separation lead to shifts in their states’ energy levels, with a stable level310 of intensity 330 is reached. 350 We can 370 discuss this 390 observa- 410 where molecular correlations can be neglected, and without any 3.2. Refractive index measurements corresponding shifts in theT(K)λ (or alternatively, the wavenumber, ν) at which spectral resonances occur [27, 28]. Phase changes can also be driven by P-induced ρ variations [29–32]. In some cases, Refractive index has been measured using Abbe's refractometer hav- Fig. 1. Temperature dependence of refractive indices (ne,no). Marker represents the ex- fi ing an accuracy of 0.0001 in the range of 1.3 to 1.7 (AR4). A polarizer perimentalthe induced data of (ne phases,no and niso) can for liquid persist crystals . Solid even lines after are the atting return curves to the original pressure [33–35], a phenomenon sheet has introduced clear contrast of the boundary line for ordinary usingof potential four-parameterrelevance model, Eqs. (8a) and to (8b) spectroscopic, (a) C3–B–C5 (b) C4–B indications–C5 (c) C7–B–C5. of shock-wave compressed media. Since ρ also and extraordinary rays in Abbe's refractometer. The temperature of Abbe's refractometer was controlled by circulating silicone oil in the typically varies with temperature, Tth variations will indirectly induce ρ-dependentn ˜ variations oil bath temperature controller. The temperature was measured by [e.g., 36, 37]. In liquids and solids, these indirect effects appear to be the dominant mode through placing a thermometer in close vicinity of the sample with an accuracy The temperature variation of the experimental data and four- fi of ±0.1 °C. While the ordinary and extraordinary refractive indices, no parameterwhich T modelth-variationstted curves, impact for ordinary a material’s and extraordinary spectral refrac- character. and ne, in the nematic phase have been directly measured. tive indices (ne,no) and birefringence (∆n) are shown in Figs. 1 and 2 forTemperature all the liquid crystals. dependent Data of fitting conformational curve parameters changes and exper- occur in numerous contexts. For example, Hud- 4. Results and discussion imental results of these liquid crystals show a fine comparison. Large polarizabilityson et al. of [12, the LCs 38] in theconsiders direction of the then ˜longbehavior molecular axisof ethane (C2H6), ethylene (C2H4), and acetylene 4.1. Birefringence, refractive indices and their temperature dependence leads(C2H to2 a) positive ices, each optical of anisotropy which (i.e. occur ne >n ino) overseveral the entireTth-dependent solid phases. Incidentally, C2H6 and nematic phase. As the temperature increases, the ordinary refractiveT The modified four-parameter model has four unknown constants A, indexC2H4 increasesprovide slightly, examples while the of extraordinary compounds refractive with indexth-dependent irreversible phase changes where the fi B, β and Δn0. These constants were obtained by tting experimental decreaseslower-T sharply.th amorphous and metastable phases convert to a higher-Tth crystalline phase. This higher- data of Δn andp〈n2〉 to Eqs. (6) and (7), respectively. The fitting param- T Inphase the investigated however LCs, the does number not of revert carbon atomsto the in theother alkyl phases when cooled [12]. Figure 7a shows this eters for investigated samples are listed in Table 2. chainth increases from three in case of the C –B–C to seven in case of ffiffiffiffiffiffiffi 3 5 impact on the absorbance of warming C2H4 ice formed at 12K through this phase transition. Note also that the C2H4 amorphous phase exhibits Tth-dependent absorption feature structure even be-
8 1994A&A...281..923J ouin fcmo topei aerosols. both containing atmospheric solutions aqueous Specifically, common of aqueous solutions of mixtures [25] chemically-interacting al. in et of Boer example hand, an other provides the On phase. gas com- features with absorption bined new of clear the show appearance spectra phase solid (C The coronene regions. of spectra absorp- the tion in poly- differences reported several their shows of 9 absorbance Figure forms (PAHs). the hydrocarbons gaseous aromatic cyclic measured and [15] solid of al. et Joblin state. crystalline to isotropic an from transitions terial feature’s absorption an in change a phase provides of [20] crystal terms al. in liquid et a Majewska of disappears. example birefringence material’s further the and occurs state isotropic The compounds. optical the of real-part extraordinary these is and phase, ordinary crystalline the the In of values crystals. constants, the liquid cyano-benzoate with several birefringent of are study materials a in 24] also [see [5] C solid of three the example that other shows 7b Figure reached. at is transition phase the fore ( solid of C of absorbance the between Comparison 9: Figure ttsi paeta steapaac fnwfaue.Teyai hw bobne(rirr units (arbitrary absorbance shows y-axis x-axis, The the features. lines); new plot of between appearance offsets the with is as apparent is states 1994A&A...281..923J T T th th 24 dpnet iue8 hw h vlto ftetwo the of evolution the shows 8a Figure -dependent. = H 12 0)ehbtsgicn ifrne nteiaiaypr fterotclconstants, optical their of part imaginary the in differences significant exhibit 20K) ntoselected two in n κ eedn ntedge owihteidvda oeue r lge,wihi turn in which aligned, are molecules individual the which to degree the on dependent , ν iue8 hw rmtcshift dramatic a shows 8b Figure : sit nfaue rsn nthe in present features in -shifts n T eouini mohu to up smooth is -evolution th die ofraincagsi rvddb aehmd n Rahimzadeh and Zakerhamidi by provided is changes conformation -driven ν T ν th rne.Pa arwn n hfigt higher to shifting and narrowing Peak -ranges. lcto stema- the as -location nue ˜ induced 24 H 12 ntwo in ) n changes ν ν ν 03–69–86 egtfato qeu H aqueous fraction weight 10.3%–16.9%–18.6% The 11. Fig. the with along K 298 at concentrations The 10. Fig. esrdtmeaue hwn h eprtr eedneo h mgnr ne frefraction. of index imaginary the of dependence temperature the showing temperatures measured osat loehbttecniumasrto swsse nteotclcntnso rusDadF. and D groups of constants optical the bisulfate in the seen of optical was magnitude These as The dependence. absorption distinct. temperature continuum are and features the concentration absorption exhibit complex the a also of exhibits constants all features sets absorption data sulfate these and of resolution the At ncm in ν - T th 9 rdcdfo iue9o ore l [25]. al. et Boer of 9 Figure from produced at bands the fate of at strengths band relative ion the sulfate in change the ducing SO The acid. HSO sulfuric and sulfate monium 10: Figure − k k ≈ 1 pcr fgopEauosslui cdamnu uft–moimntaeqaenr itrsa l measured all at mixtures quaternary nitrate sulfate–ammonium acid–ammonium sulfuric aqueous E group of spectra pcr f1.–691.%auosslui cdamnu uft–moimntaeqaenr itrsa all at mixtures quaternary nitrate sulfate–ammonium acid–ammonium sulfuric aqueous 10.3–16.9–18.6% of spectra erdcdfo iue2o [15]. of 2 Figure from Reproduced . 8 twihpitapaetasto oan to transition phase a point which at K 380 ..Be ta./Junlo uniaieSetocp aitv rnfr18(07 17–38 (2007) 108 Transfer Radiative & Spectroscopy Quantitative of Journal / al. et Boer G.J. 4 − T T T oscnetain are concentrations ions th 0 )adgsos( gaseous and K) 300 = κ κ n κ k pcrmo uewtrfo h ieaue(0%). literature the from water pure of spectrum ausas values vs. ν ν ν ≈ ν ν ν RIL NPRESS IN ARTICLE 8,15,ad19 cm 1190 and 1050, 880, o nauosslto fam- of solution aqueous an for ν ν ν 2 ≈ SO ν T 4 –(NH 10cm 1100 th ewe h a n solid and gas the between 2 aisfroeo these of one for varies H 4 ) 2 SO 4 T T T 4 ofrain (all conformations –NH T T T th − th dpnet pro- -dependent, 4 1 NO 7 )forms K) 770 = n h bisul- the and 3 ocnrto talmeasured all at concentration − κ 4 2 1 − An- . Re- . and T 33 . 30 M. Pravica et al. / Chemical Physics Letters 500 (2010) 28–34
was then filled with KBr powder which served as the pressure- beam to a 30 lm diameter spot which is then spatially filtered transmitting medium (KBr has negligible absorption in the to a 20 20 lm square (see Figure 2). Both of the mid- and far- Â mid-IR spectral region). The two halves of the DAC were assem- IR spectral acquisitions require sample placement into the differ- 362 EMMONS ET AL. bled and the device was ready for pressurization. The loaded ent microscopes and thus cannot be performed simultaneously. DAC was manually manipulated into the focal region of the More details regarding the experimental setup can be found in microscope objective through which the high flux polychromatic Ref. [19]. The spectral resolution for all of our measurements 1 IR beam passed. The spectrometer then collected Fourier Trans- was about 4 cmÀ . form Infra Red (FTIR) spectra downstream in transmission. The First-principles calculations of the total energy and optimized mid-IR experiments (including the acquisition of a background geometry were performed using the all-electron spin-polarized spectrum), required roughly 10 min for each spectrum. Back- density functional theory (DFT) implemented in the DMol software ground was collected at each pressure by laterally translating [20]. The exchange correlation energy was calculated using the lo- the DAC so that the gasket hole region which had no HMX sam- cal density approximation (LDA) with the parameterization of Per- ple (but just KBr – see Figure 2) was in the field of view of the dew and Wang [21] (PWC). A double numerical basis set (DNP) microscope objective. This background reference spectrum was including polarization functions on all atoms was used in the cal- then automatically subtracted from the sample spectrum that culations. The DNP basis set corresponds to a double-f quality basis was acquired at each pressure. set with d-type polarization functions added to atoms heavier than Infrared spectra were collected with each pressure increase of hydrogen. The DNP basis set is comparable to 6-31G(d,p) Gaussian the sample under study (mostly in 1–2 GPa steps), after waiting basis sets with a better accuracy for a similar basis set size [20,22]. some 20 min for the sample pressure to stabilize after pressure in- The energy tolerance in the self-consistent field calculations was 6 crease. Spectra were also recorded in both experiments as the sam- set to 10À Hartree. Optimized geometries were obtained using ple pressure was reduced from the maximum value to investigate the direct inversion in a subspace method (DIIS) with an energy 5 reversibility of pressure cycling. convergence tolerance of 10À Hartree and a gradient convergence 3
Our experiments were performed within the U2A beam station of 2 10À Hartree/Å. DFT calculations1992ApJ...385..577C were performed for an iso- Â situated on the Vacuum Ultraviolet (VUV) ring of the National Syn- lated molecule. chrotron Light Source (NSLS) at Brookhaven National Laboratory. For the sake of comparison with experimental data, normal Figure 4. Infrared band1 maxima for the 841 cm 1 Figure 2. The infrared absorptionInfrared spectrum spectra of PMMA were obtained within the 100–3400 cmÀ range. vibrational modes− of the equilibrium conformer were also calcu- The synchrotron beam from theambient VUV ring pressure is collected CH viarock a wedged mode as alated. function Starting of pres- from the relaxed geometry of a given model struc- as a function of pressure for the range 650–1850 cm 1. 2 diamond window, collimated,− sure. and then The directed different via symbols an evacuated indicate differentture, the Hessian data sets matrix was constructed using finite differences At the 7.5% concentration used in the scans shown, the pipe into a Brüker IFS 66s/VÒ Fourierat varying transform concentrations. infrared spectrom- Representativeof the analytic error bars gradient of the energy with respect to the atomic 1731 cm 1 carbonyl ν(C O) stretching mode is satu- − eter (FTIR). The FTIR spectrometerare shown contains indicating three distinct the estimated micro- uncertaintiespositions. The in Hessian the was evaluated using a 2-point difference rated at lower pressures (<3.6 GPa). All of the vibra- scope systems that enable measurementspressure and in frequency the far-IR measurements.and mid- of analytic forces, the finite differentiation proceeding from atom tional modes monotonically decreaseIR spectral in absorbance regions. For as the mid-IR region, the beam is focused onto to atom. The vibrational frequencies were obtained by matrix diag- the pressure is increased. the sample using a nitrogen-purged IR microscope (Brüker IR onalization of the resulting Hessian matrix in mass-weighted Scope II) and spectra are collectedpushed either closer in transmission together. or For reflec- the volume-dependentCartesian coordinates. In turn, diagonalization of the Cartesian ma- tion modes. For the far-IR experiment, the beam was directed into trix yielded the vibrational normal modes. Because of the weak in- are given in Table 2. An analysisa nitrogen-purged technique sim-mid-IR andGrüneisen far-IR microscope parameters, in which the thesam- datater points molecular below forces existing at ambient conditions in organic ilar to that of Dattelbaum etple al.3 chamberwas used. can be This purged with1.5 nitrogen GPa were gas. excludedA third microscope from the fits,molecular since insolids some such as HMX, the spectral and structural identity technique assumes that thereenables are two low temperature different far- andcases mid-IR they measurements were seen to in deviate a sim- fromof molecules a line passing is essentially preserved in the condensed state [7,23], regimes involved in the compression.ilarly nitrogen-purged In the low environmentthrough and the was high-pressure not used in these data. Allthus of facilitating the modes assignment of the fundamental normal modes of experiments. All of the microscopes can typically focus the IR vibration in this class of solids. pressure regime, the compression mainly involves were found to fit well with a linear function in the the removal of free volume. In the high pres- higher pressure regime, consistent with the mea- sure regime, the polymer chains themselves are surements of Dattelbaum et al. for a crosslinked poly(dimethylsiloxane).3 The intercepts of the lin- V(0) ear fits with the ln V(P) axis are also listed in the table. These give an indication of the pressure where the free volume! in" the polymer is removed.3 Figure 4 illustrates the random and system- atic uncertainties inherent in the measurements. Four different data sets are shown at different concentrations ranging from 11–30%. The scat- ter in a particular data set illustrates the random errors in the determination of the pressure and band centroids. The position of the band maxima were used to determine ν(P); however,this method was found to be reasonably consistent with cen- troids obtained by fitting different trial functions to some of the peaks. Due mainly to the inter- ference fringing, it was difficult to find a fitting function that fit the bands well, and hence the band maxima were used in the data analysis. The errors bars for the band maxima were determined Figure 3. The infrared absorptionFigure spectrum 3. Stack plotsof PMMA of far-IR spectra of HMX powder at various pressures. The black traces were taken in compression and the traces in red were collected during as a function of pressure for the C decompression.H stretching modes. by estimating how accurately the maxima could Note the shift to higher(a) frequency for all of the vibra- be interpolated. The errorsGRUNDY bars(b) AND for the SCHMITT: pressure H20 ICE 25,817(c)
tional modes as the pressure is increased.of our Gaussiansareinclude not errorslisted inin determinationTable I because of thethey wavelength 200 are extremely poorly constrained, and are only included to match spectral regionsJournal at of Polymerthe limits Science: of our Part sensitiv- B: Polymer Physics DOI 10.1002/polb ity range (at 1.1 and 2.7 ttm). Three others, corre- 1,50 sponding'to relatively weak absorptionsat 1.37, 1.6, and 1.8 /•m, have insufficient confidencelevels to jus-
1995A&A...299..835J tify interpretation of their temperature dependent be- havior. In addition, above about 130-150 K, the be- 100 havior of one or more band parameters of a few broad and stronglyblended modes (e.g., the frequencyof the 1.31 /•m mode and the width of the 1.56 /•m mode) '• 50 seem to follow trends reversed from those observed at lower temperatures. This situation may be an artifact of the increasingdifficulty of deconvolvingthe various components of less and less structured and more and o more blended bands at higher temperatures. In the following discussion,we restrict our attention to the temperature-dependentbehavior of the 12 well- -50 constrained Gaussian bands. For bands showing pe- 0 50 100 150 200 250 culiar trends at higher temperatures, we concentrate Tempero•ure(K) on their behavior at better-constrainedlower tempera- tures. Based on the temperature dependenciesof their Figure 5. Examples of the temperature dependent frequencies,widths, and peak absorptions,we were able shifts in frequency of several of our 12 well-constrained to distinguish(d)several different behaviorsamong these absorption bands, relative(e) to the 20 K values which are 12 bands. tabulated in Table 1. These curvesresult from fitting Gaussiansto the different componentsof the spectrum First, all bandsexhibiting significantfrequency shifts at each temperature, as describedin the text. with temperature(up to +200 cm-1 between20 and Figure 11: Anharmonic273 K) potential movetoward higher effectswavenumber under(shorter changingwave- P and T . (a) C-H band absorption spectra length) with increasingtemperature. All thesebands th follow similar trends: smaller variations near 20 K and absorption trend above about 130 K. It is not clear if of poly(methyl methacrylate)slopesincreasing morphologytoward higher temperatures. changesThis withbe- thisP effect; reproduced is real or simply due from to the [28].limitations (b) of our HMX absorption havior is well illustrated by the 1.50 and 1.99/•m bands deconvolutionprocedure for that band. in Figure 5. Contrastingwith this behavior,two bands, The behavior of the integrated intensity is the prod- spectra changes withatP 2.02; reproduced and 2.37/•m, have fromsmall negative [32].shifts, Solid never (c)uct of and the width gas and (d) the phasepeak intensity PAHcurves, moleculesresulting absorption exceeding-20 cm-1 overthe wholetemperature range, in evenmore varied behaviors (Figure 8). The trend of and the 2.52/•m band showsalmost no shift. The tem- the peak intensityseems to dominatethe integratedab- band morphology changesperature dependence with T ofth ;frequency reproduced for each band from was sorption [36, 40].for most For bands, (c),the mainT th exception= 303being K forthe the solid lines evaluated between 100 and 200 K and tabulated in the 1.50 ttm band, whichshows an increasein integratedab- last column of Table 1. sorption in spite of a decreasingpeak absorption. The and 513 K for the dashedAnother lines. general tendency (e) Observed is an increased shiftsFWHM intwo H sharpest2O icebands NIRat 1.31 andbands 1.65/•mwith again showT ththe , demonstrating with temperature(by factorsranging from 1.1 to 1.9 largest integrated intensity changes. that band shift behaviorbetween differing20 and 273 K), from with the the exception typicalof three discussed Taking all here these trends can together, occur; it is difficult reproduced to clas- from [18]. bands(at 1.04, 1.99,and 2.37/•m) displayingmoderate sify the bands into groups sharing similar behaviors, narrowingwith temperature(Figure 6). As for the fre- even ignoring the amplitude of the changesand only quency,the rate of variationin width (slope)tends to consideringtheir sign. The only group that seemsto increasewith temperature as well. emergequite clearly is a seriesof six bands (at 1.27, The behaviors of the peak intensity are more varied, 1.31, 1.50, 1.56, 1.65, and 2.06 /•m) that displayneg- with two thirds of the bands showingdecreases with ative frequency shifts, band broadening,and decreases increasingtemperature, sometimes quite strongly (by in peak intensity with increasingtemperature (at least ammonium sulfate andfactors sulfuric of more than acid15 for the show 1.31, 1.57, significant and 1.65/•m from variations 20 to 130 K). As in will the be discussed magnitudebelow, these of κ within cer- bands)and one third showingmoderate increases (at trends are also exhibited by several of the fundamental leastbelow 130 K) (Figure7). The two sharpestbands modes.We can alsogroup the 2.02 and 2.52/•m bands tain bands. The reasonat low for temperature, this is at that1.31 and the 1.65/•m, equilibrium undergo the as sharingconstantvery similar of trends, thesulfate-bisulfatein both shapeand ampli- ion reaction 2− − strongestdecreases with temperatureand almostvanish tude,for all threeband parameters. The fourremaining near the melting point. There is no generalT trend for the bandsall havedifferent combinations of the signof the (SO4 HSO4 ) inshape aqueous of the curves, solutionas was the case is for th frequency-dependentand temperature [39]. variation As of the the three equilibrium band parameters. concentration of width. It should be noted that all three componentsof Someof thesebehaviors may be comparedwith those, these two ions changes,the 2/•m the band absorption complexdisplay reversals in theirin their respective peak better known, bands of the varyvariousfundamental significantlymodes, in or- (Figure 10).
Both Tth and P variations altern ˜ in materials with anharmonic intermolecular potentials. Under increases in pressure (increasing ρ), absorption features typically broaden and shift to higher ν (corresponding to energy levels shifting upward). This behavior is observed in Figures 11a and 11b, which shows the absorbance in the C-H stretching modes of poly(methyl methacrylate) and in the far-infrared absorbance spectra of octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) evolving under increasing P [28, 32] . On the other hand, at (nearly) constant P, increasing Tth tends to decrease ρ, shifting feature to lower ν (larger λ) as occurs with decreasing P. Figures 11c and 11d show examples of this behavior in the case of different PAH molecules in the solid [40] and gas phases [36], respectively. However, the analogy here between an increasing Tth and decreasing P is not complete: feature widths broaden with increasing Tth in these examples, not narrow as with decreasing P. This difference in behavior is likely explained by the fact that with increasing Tth, while the material’s quantum energy levels shift downward, there is an overall shift in state occupation number toward higher-level states. Apparently in these examples, the corresponding increase in sample’s translation/vibrational kinetic energy produces observable increases in feature Doppler broadening. Finally, we note that while these absorption feature morphology trends with P and Tth are typical, they are not ubiquitous. Figure 11e shows the Tth shifts seen in near-infrared (NIR) bands of H2O ice, several of which shift to higher ν with increasing Tth [18].
10 H. Foerstendorf et al. / Journal of Colloid and Interface Science 416 (2014) 133–138 135
significantly affected, whereas the shape of the uranyl band re-
1528 1382 carbonate in the aqueous phase [28] or to an asymmetric band 10 shape due to simultaneous spectroscopically distinguishable ura- 5 nyl moieties [23,29].
-absorption / a.u. The desorption processes were induced by flushing the mineral ∆ film with a degassed 0.1 M NaCl blank electrolyte subsequently to C prolonged U(VI) sorption when no more spectralFig. changes 13. Typical were experimental ob- apparatus for RAIRS. The experiments are served for several minutes. The respective spectraperformed exhibit by negative focusing the IR beam from a commercial Fourier-transform infrared spectrometer through a polarizer and a KBr (or NaCl) window onto the t / min Mh(U) +
11 1072 T. Fornaro et al. / Icarus 226 (2013) 1068–1085
T. Fornaro et al. / Icarus 226 (2013) 1068–1085 1075
Fig. 1. Chemical structures and numbering schemes of nucleobases investigated.
T. Fornaro et al. / Icarus 226 (2013) 1068–1085 1081
Table 7 Geometrical arrangements of nucleobases on MgO and forsterite.
Adenine on MgO
Interaction with the N3C4C5C6 part of the molecule in a distorted nearly planar arrangement
1 Fig. 4. IR spectra of pure cytosine, cytosine adsorbed on MgO and pure MgO, represented in Kubelka–Munk units (KM) vs wavenumbers (cmÀ ). 1 Fig. 2. IR spectra of pure adenine, adenine adsorbed on MgO and pure MgO, represented in Kubelka–Munk units (KM) vs wavenumbers (cmÀ ).
Adenine on forsterite
Interaction with the NH2 group in a tilted arrangement
H. Zorgati et al. / Chemical Physics 362 (2009) 41–57 51
Cytosine on MgO and forsterite maximum value when the molecule lies just above the defect. In 5.4.2. Calculation of the spectra Face-to-face configuration contrast, due to the compensation of the terms in Eq. (51) the 5.4.2.1. Vibrational band of CO. The fundamental vibration of CO in 1 broadening smoothly increases when the distance decreases to gas phase is x0 2143 cmÀ . When the molecule is adsorbed on ¼ reach a maximum value on the defect site. As discussed in Section the perfect MgO surface at 5 K, a single peak occurs at the fre- 1 1 4.3, the shift can be positive (for the m2 band of NH3) or negative quency 2151:4cmÀ with a width equal to 0:07 cmÀ (Fig. 5a). This (for the m1 band of NH3) depending on the vibrational dependence shift is due to the vibrational dependence of theUracil CO–surface on MgO inter- P Face-to-face configuration of the potential parameters. For CO (not drawn), we expect a smal- action potential V nS (cf. Eq. (16)). The larger part of this shift comes ler dependence of the shift since the main contribution to the force from the static(c) contribution of this potential (no surface dynamics) constant comes from the dipole–quadrupole potential. At finite while the dynamical contribution (including external motions of 1 À Fig. 3. IR spectra of pure adenine, adenine adsorbed on forsterite and pure forsterite, represented in Kubelka–Munk units (KM) vs wavenumbers (cm ). 1 Fig. 5. IR spectra of pure cytosine, cytosine adsorbeddilution, on forsterite these and shifts pure forsterite, and broadenings represented in Kubelka–Munk are weighted units by(KM) thevs wavenumbers distribu- (cmÀ the). molecule coupled to substrate phonons) remains much smaller 1 (a) tion function of the defects on the surface to yield the spectra. ( 1–2 cmÀ ). (b) Uracil on forsterite results, in fact, in a resonance structure of uracil characterized by a on the surface. Uracil is in the neutral form at the equilibrium Interaction with the C2@O and N3H groups in a tilted arrangement single C4AO bond, the negative charge on the oxygen atom and a pH, and presumably interacts with the hydroxyl groups on the sur- double bond N3@C4, which account for the strengthening of the face of forsterite through the C2@O and N3H groups, which undergo ring stretching mode (Fig. 10). Probably, ionic and electrostatic the highest low frequency shifts. Figure 14: (a) and (b): Infraredinteractions absorbance dominate the adsorption of uracilspectra onto MgO and of the adenineThe IR spectra of and pure hypoxanthine cytosine and adsorbed adsorbed on MgO and on forsterite. disappearance of the most of the bands in the IR spectrum suggests forsterite are presented in Figs. 8 and 9. The band-peak positions Top plot provides pure materialthat the spectra molecules are laid while flatly parallel the to the surface middle (face-to- paneland the assignments shows are given each in Table 6 adsorbate. The assignments of IR on the substrate. face configuration). bands were based on comparison with the experimental and theo- Uracil adsorbed onto forsterite at pH 7.3 shows several high retical data reported in the literature (Ramaekers et al., 2001). Hypoxanthine on MgO and forsterite Adenine modes are still presentintensity when IR bands (assignment adsorbed reported in Table while 5), even if thecytosineThe spectrum modes of the pure solid disappear. hypoxanthine shows 26 (c): of the The orientation Face-to-face configuration amount of molecules adsorbed on the mineral is about 36 vibrational modes (Table 6). An analysis of the spectroscopic 2 of adenine (top panel) and cytosine4 lmol mÀ , indicating (bottom a tilted arrangement panel) of uracil molecules whenfeatures adsorbed suggests that theonto predominant the form ofsubstrate hypoxanthine is inferred from their IR mode activity. All figures reproduced from [44].
copper substrate. Similarly, the disappearance of characteristic nucleobaseindication modes of a probable break on of magnesium the XAH bonds as a consequence intensity, indicating that the strength of the bonds in the aromatic 1 of UV irradiation. The peak at 1761 cmÀ assigned to the C2@O ring decreased and part of the vibrations of the aromatic ring was 1 oxide and olivines have been used to determine nucleobase orientation onstretching these mode substrate remained unaltered, materials while the peak correspon- brought down; a new double peak at 1290–1271 cmÀ and a new 1 dent to the C4@O stretching broadened until the complete disap- single peak at 1165 cmÀ appeared, presumably corresponding to (Figure 14) [44, 52]. Other examples of mode disappearance occur commonlypearance at the end [e.g., of the UV 46, irradiation 47, experiment, 53]. when it single bond CAO stretching modes. Other minor forming peaks at 1 was covered by a broad band of water in the region of 1381 and 905 cmÀ appeared, probably corresponding to CAN 1 1700 cmÀ . The peaks assigned to the ring stretching, N3H bending, and CAO vibrations. Further confirmation of the degradation of Adsorbate and substrate modes can also coalesce upon adsorption [46]. On the other hand, adsor- 1 N1H bending and CH bending, in the region 1500–1400 cmÀ , the aromatic ring was the drop in intensity of the peaks at 1006, 1 broadened and overlapped after UV irradiation. This is an indica- 994, 585 and 569 cmÀ due to the ring stretching, in-plane ring bates can modify the substrate’s surface states, give rise to new electrontion states, of alterations and of thealter aromatic its ring surface and, consequentially, bending, out-of-plane NH bending and out-of-plane bending vibra- 1 changes in the force constants of the chemical bonds of the mole- tion of the ring. In the region around 800 cmÀ , the broad band of cule, which cause vibrations in a wider range of frequencies. The water, which increased in intensity during the UV irradiation pro- chemical activity [e.g., see 37 and references therein]. 1 most interesting changes were in the region 1300–1100 cmÀ , cess, covered the uracil bands. 1 where: the peak at 1242 cmÀ , correspondent to the ring stretch- In the case of adenine, none significant changes in the IR spectra Adsorbate/substrate systems exhibit a significant sen- ing, underwent a low frequency shift and a decrease of the were observed. Some peaks decreased and others appeared at 669, sitivity to locality specific effects. Adsorbate mode frequencies depend sufficiently on their specific ad- sorption site that spectroscopy can be used to identify adsorbate bonding locations, even to the point of being able to distinguish between adsorbates bound to crys- tal edges, faces, or corners [37, 42, 43, 54–56]. Sub- strate surface defects, which are localized by their very nature, influence the magnitude of adsorbate feature shifts and broadening, at least for polar molecules. The defect’s nature, size and proximity to adsorbates play key roles in how significantly such defects alter feature properties [47, 48]. Figure 15 shows the predictions of Fig. 5. Behavior of the IR profile of the vibrational band of CO adsorbed on MgO surfaces containing various concentrations of dipolar defects (a) at T = 5 K, (b) at T = 55 K. (a) Zorgati et al. [48] for how a vibrational modeBlack of circles,CO white circles, black triangles and white squares correspond to defect concentrations equal to 0%, 1%, 3% and 15%, respectively. (b) Black circles, white circles, black squares, black trianglesFigure and white squares 15: correspond Predicted to defect concentrations equal vibrational to 0%, 1%, 3%, 10% and 15%, moderespectively. of adsorbed onto magnesium oxide (MgO) is affected by CO adsorbed onto MgO in the presence of increasing concentrations of MgO surface dipolar de- dipolar surface defects at defect concentra- fects. Higher defect concentrations produce larger red- tions equal to 0%, 1%, 3%, 10% and 15%, shifts, increased broadening, and decreased maximum respectively. Reproduced from [48]. absorption in the CO mode. Adsorbate concentration is another important variable. As adsorbate concentration increases, the mutual self-interactions between adsorbate molecules can become important. Numerous studies of CO adsorbed on various substrates have observed significant shifts in modes along with the transition of single-peaked to double-peaked features
12 1322 E. Carrasco et al. / Surface Science 604 (2010) 1320–1325
C.D. Zeinalipour-YazdiIn et al.Fig. / Surface 3 Sciencea series xxx (2015) of xxx infrared–xxx spectra of CO adsorbed on3 Pt(111) appeared, further increase of pressure up to 100 mbar CO leads to only acquired in-situ at a temperature of 300 K and in the pressure range slight modifications in this spectral region. SCF cycles with a threshold of 10−4 eV (10−7 eV). The initialfrom charge 10− 9 assignmentmbar to of100 diffuse mbar reflectance is presented. infrared Fourier-Transform (DRIFT) According to Fig. 3 the appearance of the second on-top signal − 9 − 8 density was obtained by superposition of atomic charges, and theSpectra pro- spectra taken obtained at 1×10 for CO chemisorptionand 1×10 overmbar a highly CO dispersed show Rh/ twoγ- bands coincides with changes observable in the bridge region that can be at 2098 cm− 1 and 1853 cm−1 characteristic for CO adsorbed in on- related to the onset of the formation of CO compression structures on jection operators were evaluated in reciprocal space. Αl2Ο3 catalyst [18]. Due to computational cost, this method is limited top and bridge position at θCO =0.5. Spectral changes are observed by Pt(111) [19]. To check whether there is a direct relation between the We note that, for metallic systems, the B3LYP functional isincreasing not regu- theto the pressure smaller cluster to and sizes above with single 1× adsorbates.10− 7 mbar Therefore CO. we First addi- consider spectral changes in the on-top and bridge regions at this onset of larly used due to its failure to recover the homogeneous electronthe gas region so- tionally of bridge-bonded employed the more CO: commonly At a used pressure PBE functional of 1 for× the10 larg-− 7 mbar a compression, similar experiments have been carried out at tempera- lution for itinerant electron states in bulk metals [71].second For metal signalest cluster of bridge-bonded size, and to examine coverage CO appears effects. at 1867 cm− 1, which tures other than 300 K. Comparable spectral changes in the region of complexes the functional is quite widely used and a combinedshifts B3LYP/ to higherHere, wavenumbers we briefly examine with the dependence increasing of CO pressure. adsorption energy At the same bridge-bonded CO as observed in Fig. 3 are observed when the time, the band at 1853 cm− 1 loses intensity and is shifted towards experiments are performed at 200 K. The only difference is that the CCSD(T) study has appeared for cationic group 10 and group 11 carbon- on Pd cluster size, before considering the effect of CO surface coverage. lower wavenumbers (1841 cm−1 at 5×10− 6 mbar CO). An increase onset of the changes as well as of saturation is shifted to lower yl complexes [72]. The nanoclusters considered here are intermediateof pressure in The up energetics to 1 mbar of CO chemisorptionCO leads to were the studied disappearance for three high sym- of the low pressure, in accordance with the fact that at lower temperature, lower 1 size. We use the B3LYP functional only for its reliability in vibrationalfrequency signalmetry Pd and particles: a shift tetrahedral of the high Pd4(3,1) frequency (0.4 nm), band cubooctahedral to 1882 cm− , pressures are needed to saturate the surface with CO. In contrast, the analysis including intensity estimates for the IR modes ofwhich CO on the remainsPd13(3,7,3) constant (0.8 nm) thereafter. and cubooctahedral The same Pd38(O behaviorh)(1.1nm).Three of the bridge appearance of the second on-top signal at 200 K occurs at higher CO signal has been observed in a recent PM-IRAS study carried out at the pressure as compared to experiments that have been performed at smaller clusters. The total adsorption energy per CO molecule (ΔΕads,CO) distinct configurations were identified and are presented in Fig. 2: same conditions as presented in Fig. 3 [19] as well as in UHV 300 K (1×10−5 mbar at 200 K vs. 1×10− 7 mbar at 300 K). Moreover, was calculated using Eq. 1, linear (lCO), bridge (bCO) and hollow (hCO) bound molecules, investigations of high coverage CO structures on Pt(111) [5,16]. The at temperatures below 200 K we do not observe the second on-top evolution ofwhich theresemble bridge signal the stable with adsorption increasing configurations pressure found seems over to be a signal. These observations suggest that the second on-top signal is ΔΕads; CO EPdm CO n−EPdm−nCO ECO = nCO reliable1 indicatorRh4(3,1) for[10,17] the. Additionally, occurrence di-carbonyl of compressed (di-CO) and CO tri-carbonyl overlayers on related to a different adlayer structure, the formation of which is ¼ ðÞ Á ð Þ Pt(111) andspecies the (tri-CO)similarity were of stable UHV on Pdandbut high-pressure could not be identi studiesed on in the subject to kinetic limitation. ÀÁ 4 fi coverage range between θCO =0.5 and θCO =0.7 suggests that there is The thermal stability of the compression structure giving rise to where Ei is the total energy of fully optimised species i and nCO is the Pd38(Oh)andhencewerenotfurtherconsidered;palladium no pressure gap for CO adsorption on Pt(111), which was also two on-top signals was studied by temperature dependent IRAS number of adsorbed CO molecules. Note that this de nition means dicarbonyl species are known to be particularly unstable [75],akin fi concluded from high-pressure STM investigations [10]. measurements presented in Fig. 4.Anadlayerpreparedata that negative adsorption energies are favourable compared toWe gas alsoto observe their Rh analogues changes which in the are region only found of on-topin supported bonded catalysts CO when temperature of 220 K and a background pressure of 1×10− 4 mbar phase CO and a free nanoparticle. The surface coverage of COa has pressure been ofas isolated 1×10− mononuclear7 mbar CO moieties or higher[76,77] is. Calculated applied. adsorption When a en- pressure CO served as the starting point. Under these conditions, the PM-IRAS defined based on Eq. 2, of 1×10−7ergiesmbar of CO CO at a is low reached, coverage (θ a→ 0) shoulder are given in appearsTable 1. For on all ad- the high spectrum (lowest trace in Fig. 4) exhibits two CO on-top signals at 1 1 frequency sidesorption of the sites main we observe on-top a strong signal. particle With size-dependence increasing in CO good exposure 2113 cm− and 2095 cm− , respectively, with more spectral weight 1 1 this shoulder develops into a separate signalC.D. at Zeinalipour-Yazdi 2109 cm− etat al. the / Surface Scienceon the xxx (2015)higher xxx frequencyxxx band. A bridge band at 1880 cm− is also θCO nCO= nPd;surf 8 2 agreement with earlier theoretical studies [32,41,64]:onPd4 – ¼ expenseð Þ of the main on-top band. Once−1 this second on-top signal has present. This spectrum is comparable to one obtained at 300 K and ΔΕads = − 130 to − 257 kJ mol ;onPd13 ΔΕads = − 167 to 1 mbar CO (Fig. 3). Subsequent cooling to 90 K in CO atmosphere does −1 -1 −1 -1 where nPd,surf is the number of surface Pd atoms of the NP. The vibra-(a) −223 kJ∆ molν = 63;andforPd cm 38 ΔΕads = −161 to −196 kJ mol .In- (b) not signiCOhficantly0b0l1 , θ change = 0.031 the spectral signature,∆ν = 29 cm apart from a slight COh1b0l0 , θ = 0.031 8 shift of the on-top signals to higherC.D. wavenumber Zeinalipour-Yazdi et and al. / Surface a narrowing Science xxx (2015) of xxx–xxx tional frequencies were explicitly calculated by diagonalizing the terestingly, this cluster size-dependence of CO adsorption energy 2COh0b0l2 , θ = 0.063 Hessian matrix using the finite-difference (FD) method. Additional cal- was dependenth-CO on the adsorption configuration. For hollow and the bridge line. After evacuating CO at 90 K the on-topl-CO signals remain 2COh b l , = 0.063 1 2 0 0 θ unchanged.4COh In0b the0l-14 , bridgeθ = 0.125 region, however, the main band at 1880 cm− -1 ∆ν = 63 cm (b) COh0b0l1 , θ = 0.031 ∆ν = 29 cm culations using the density-functional-perturbation-theory (DFPT) bridge-bound CO, ΔΕads, CO indicates weaker binding with increasing (a) −1 loses intensity6COh0b0 andl6 , θ a= broad0.250 feature appearsCOh1b0l0 at, θ 1860= 0.031 cm , pointing to 4COh4b0l0 , θ = 0.125 2COh0b0l2 , θ = 0.063 method within VASP were used to ensure that agreement within NP size (0.4 nm → 1.1 nm), whereas linear bound CO becomes more some rearrangement of CO molecules in the adlayer. The sample was l-CO −1 12COhh-CO0b0l12 , θ = 0.375 2 cm could be obtained with this computational protocol. The relative strongly bound. The calculated sensitivity of CO adsorption energy to 2COh2b0l0 , θ = 0.063 4COh0b0l4 , θ = 0.125 8COh8b0l0 , θ = 0.250 then heated to the temperatures indicated in Fig. 4 and PM-IRAS spectra intensities of linear-CO (lCO), bridge (bCO) and three-fold (3f) hollow NP size scales roughly with the coordination number (i.e. number of were acquired24COh2b at9l13 these, θ = 0.625 temperatures in vacuum. Upon heating to 150 K,6COh0b0l6 , θ = 0.250 4COh4b0l0 , θ = 0.125 12COh12b0l0 , θ = 0.375 the broad feature in the bridge region again disappears, which leaves the (hCO) species were calibrated against the results for tetrahedral (Td) Pd\\C bonds), such that hCO N bCO Nb-COlCO. 32COh10b7l15 , θ = 1.000 12COh0b0l12 , θ = 0.375 −1 b-CO 1880 cm signal as the main contribution8COh8b0l in0 , thisθ = 0.250 spectral range. This Pd4(3,1) and cubooctahedral (Oh) Pd13(3,7,3). Infrared spectra were According to these results, the experimentally observed trend 24COh b l , = 0.625 20COh16b4l0 , θ = 0.625 signal remains constanth-CO upon further heating to 225 K. At 250 K the 2 9 13 θ simulated by fitting a Lorentzian function with a FWHM = 15 cm−1, should then depend on the site occupancies for the three positions 12COh b l , θ = 0.375 b-CO 12 0 0 32COh10b7l15 , θ = 1.000 b-CO centred at each stretching frequency calculated from the FD method. which may be influenced by sample pre-treatment. Campbell and co- 20COh16b4l0 , θ = 0.625 h-CO workers [31] suggested that the experimentally observed weakening 3. Results and discussion of adsorption could result from a Van der Waals dispersion effect, which would be expected to reduce with particle size. We have used Absorbance (arbitrary units) (arbitrary Absorbance 3.1. Effect of NP size on CO adsorption units) (arbitrary Absorbance Absorbance (arbitrary units) (arbitrary Absorbance Previous computational [41,64] and microcalorimetric [32] studies units) (arbitrary Absorbance 1750 1800 1850 1900 1950 2000 2050 2100 2150 1750 1800 1850 1900 1950 2000 2050 2100 2150 of CO adsorption on Pd NPs have suggested a strong cluster size- Wavenumber (cm-1) Wavenumber (cm-1) dependence of the adsorption energy. At low coverages, i.e. θCO b 0.1 1750 1800 1850 1900 1950 2000 2050 2100 2150 1750 1800 1850 1900 1950 2000 2050 2100 2150 −1 ML, CO adsorption energies can vary by almost 100 kJ mol (falling Wavenumber (cm-1) Wavenumber (cm-1) −1 −1 from −202 kJ mol for Pd13 to −109 kJ mol for Pd25), resulting in (c) a critical cluster size (50–100 atoms) wherein CO adsorption is weakest [41]. Another microcalorimetry study showed that initial heats of ad-(c) Calc. DFT linear-CO 91 -1
exp. 2090-2120 cm Reflectance arbitrary ( units) sorption that fall linearly with particle size from the Pd(111) surface Exp. DRIFTS (c) Calc. DFT linear-CO −1 −1 calc. 2058-2102 cm-1 91 -1 value of 149 ± 3 kJ mol down to 106 ± 1 kJ mol for particles of exp. 2090-2120 cm Reflectance arbitrary ( units) Exp. DRIFTS 2 nm dimension [31]. Adsorption microcalorimetry offers precise ad- calc. 2058-2102 cm-1 sorption heats [73,74], but no direct insight, into CO bonding modes. At- hollow-CO omistic simulations herein, provide adsorption energies of CO species exp.27 1830-1900 cm-1 hollow-CO according to their structural identification (i.e. lCO, bCO or hCO),Fig. 3. how-PM-IRAS spectra of CO adsorbed on-1 Pt(111) at 300 K acquired under continuous Fig. 4. Temperatureexp.27 1830-1900 dependence cm-1 of PM-IRAS signals from compression layers of CO CO exposure at increasingcalc. pressure 1839-1894 (from cm bottombridge-CO to top). adsorbed on Pt(111), see text for details. ever it is clear from the introductory discussion of site preference that exp.(a)91 1930-2000 cm-1 calc. 1839-1894 cm-1 bridge-CO this is likely to give insufficient accuracy to allow relative abundances calc. 1916-1979 cm-1 exp.91 1930-2000 cm-1 -1 (nlCO,nbCO,nhCO) to be determined. However, DFT calculations can be calc. 1916-1979 cm used to interpret IR spectroscopic signatures of adsorbed CO species by obtaining the IR intensity factors as a function of CO position, and then using experimental data to interpret the site populations. IR inten- sity calculations are not currently available in VASP for these systems, Absorbance(arbitrary units)
and are most accurate using a hybrid functional method for which the Absorbance(arbitrary units) computational expense increases rapidly with system size. Accordingly, we have performed calculations using small reference systems (Pd4 and 1750 1800 1850 1900 1950 2000 2050 2100 2150 1750 1800 1850 1900 1950 2000 2050 2100 2150 Pd13), and extrapolated the results to the larger Pd38 cluster size. The Wavenumber (cm-1) Wavenumber (cm-1) choice of hybrid B3LYP functional for the calculation of IR oscillator Fig. 2. Structures for linear, bridge and three-fold (3f) hollow bound CO on Pd4(3,1), frequencies was based on its earlier success in the spectral band Pd13(3,7,3) and Pd38(Oh), respectively. (b) Fig. 8. Simulated IR absorption spectra for a range of Pd38(CO)n structures created with (a)Fig.algorithm 8. Simulated 1, (b) IRalgorithm absorption 2 and spectra (c) comparison for a range(d) of of Pdalgorithm38(CO)n structures 2 with experimental created with DRIFTS(a) algorithm spec- 1, (b) algorithm 2 and (c) comparison of algorithm 2 with experimental DRIFTS spec- trum of CO on Pd/KIT-6 for = 1. Oscillator intensities scaled in the ratio lCO:bCO:hCO−1 = 1.00:0.68:0.58 taken from Pd in Fig. 4. Frequencies have been shifted by 49 cm−1 which is the Please cite this article as: C.D. Zeinalipour-Yazdi, et al., CO adsorptiontrum of CO over on Pd/KIT-6 Pd nanoparticles: for θCO = 1. A Oscillator general intensitiesframework scaled for IR in simulations the ratio lCO:bCO:hCO on = 1.00:0.68:0.58 taken fromθCO Pd13 in Fig. 4. Frequencies have been shifted by 49 cm which is the 13 difference−1 between the calculated vibrational frequency− of1 gas phase CO (ν = 2131 cm−1) and the experimental value (ν = 2180 cm−1) [18]. nanoparticles, Surf. Sci. (2015), http://dx.doi.org/10.1016/j.susc.2015.07.014difference between the calculated vibrational frequency of gas phase CO (νCO,PBE = 2131 cm ) and the experimental value (νexp = 2180 cm ) [18]. CO,PBE exp Figure 16: (a): The evolution of the reflection/absorption IR spectra of CO adsorbed onto platinum −1 −1 asFig. a function 8a–b, alongside of a ambientcomparative experimentalP (a proxy DRIFTS for spectrum CO surface for Fig. 8frequencya–b, concentration); alongside between a comparative 1825 and experimental reproduced 1900 cm−1 (cf. DRIFTS 1843 from spectrum and 1898 Figure for cm−frequency1 in 3 of between 1825 and 1900 cm (cf. 1843 and 1898 cm in CO adsorbed over a 2.22 wt% Pd/KIT-6 mesoporous catalyst, with Fig. 8c). Agreement between the present calculations at θCO = 1 via al- CO adsorbed over a 2.22 wt% Pd/KIT-6 mesoporous catalyst, with Fig. 8c). Agreement between the present calculations at θCO = 1 via al- mean Pd NP diameter of 1.7 nm (Fig. 8c). gorithm 2 and experimental observations is astonishingly good. Band [42].mean (b): Pd NP diameterGraphic of 1.7 showing nm (Fig. 8c). the bonding of CO togorithm Pd in 2 and the experimental linear, bridge,observations and is astonishingly hollow good. (h-CO, Band b- IR spectra simulated via algorithm 1 display significant vibrational positions and relative intensities of linear and bridge-bound CO from IR spectra simulated via algorithm 1 display significant vibrational positions and relative intensities of linear and bridge-bound CO from CO, and l-CO, respectively) configurations. (c):coupling, Simulated evidenced IR by absorbancefine structure within spectra the hollow-bound for CO CO adsorbedour simulations are also in excellent correspondence with the DRIFT coupling, evidenced by ne structure within the hollow-bound CO our simulations are also in excellent correspondence with the DRIFT onto palladium as afi function of total CO numberband, and which adsorption (albeit infrequently site. present) The appears peaks as a weak, corresponding broad fea- spectrum to of a saturated CO adlayer over a 2.22 wt% Pd/KIT-6 catalyst band, which (albeit infrequently present) appears as a weak, broad fea- turespectrum in DRIFT spectra of a saturated of supported CO adlayercatalysts over[18]. aFig. 2.22 8a also wt% shows Pd/KIT-6 the catalyst[15] (Fig. 8c). The extremely weak experimental hCO band for Pd NPs ture in DRIFT spectra of supported catalysts [18]. Fig. 8a also shows the [15] (Fig. 8c). The extremely weak experimental hCO band for Pd NPs each CO adsorption site are labeled. Note the peakpresence shifts of bridge-bound and morphology CO at intermediate changes coverages (θCO as= CO0.625), coveragesupported on the KIT-6 mesoporous silica likely reflects a combination presence of bridge-bound CO at intermediate coverages (θCO = 0.625), whichsupported overlapswith on the hollow KIT-6 CO mesoporous features, indicative silica likely of similar reflects adsorption a combinationof (i) the smaller IR absorption coefficients with respect to bCO and increases.which overlaps (d): with Comparisonhollow CO features, indicative between of similar experimental adsorption energeticsof data (i) atthe high and smaller coverage. one IR absorption The of latter the observation coefcalculationsficients is consistent with respect in with (c). theto bCO FigureslCO and (Fig. 4), and (ii) the experimental protocol, in which the Pd catalyst
energetics at high coverage. The latter observation is consistent with the weakeninglCO (Fig. Pd\ 4\),hCO and bond (ii) the with experimental increasing θCO protocol,from 0.03 in→ which0.625 appar- the Pd catalystwas flushed with an inert gas after CO adsorption at 298 K prior to spec- (b)-(d) reproduced from [57]. −1 weakening Pd\\hCO bond with increasing θCO from 0.03 → 0.625 appar- ent inwasFig.fl 7ushed, which with induces an inert a pronounced gas afterCO 63 cm adsorptionblue-shift at 298 in the K prior hCO to spec-tral acquisition [15]; thermodynamics suggest that CO is only stable in ent in Fig. 7, which induces a pronounced 63 cm−1 blue-shift in the hCO bandtral average acquisition position.[15] A; similar, thermodynamics albeit, weaker suggest blue-shift that CO (29 is cm only−1, stablehollow in sites at ambient temperature under CO partial pressures exceed- −1 band average position. A similar, albeit, weaker blue-shift (29 cm , Fig. 8hollowb) was sites observed at ambient with increasing temperatureθCO for under linearly-bound CO partial pressures CO bands exceed-ing 1000 mbar [92].
4 M. Buchholz et al.simulated / Surface Science via algorithm xxx (2015) xxx 2. –xxx withFig. varying8b) was observed CO with concentration increasing θCO for linearly-bound[e.g., 42,54]. CO bands Theseing 1000 mbar [92]. simulated via algorithm 2. The utility of these simulations was assessed for Pd38(CO)32 by 3.5. Coverage-dependent blue-shift of CO on Pd38 benchmarking against frequency ranges and band assignment for spectralThe utility variations of these simulations are attributed was assessed to for Pd the38(CO) changing32 by 3.5. Coverage-dependent blue-shift of CO on Pd38 RAIRS studies on model Pd/Al O catalysts [86] and vibrational sum fre- The preceding coverage-dependent vibrational frequencies for CO in benchmarking against frequency ranges and band assignment for 2 3 quency generation (SFG) of CO adsorption on Pd NPs and Pd(111) sur- each of the three adsorption sites over a Pd (O ) NP derived via algo- strengthRAIRS studies of on CO-CO model Pd/Al interactionsO catalysts [86] and as vibrational CO concentra- sum fre- The preceding coverage-dependent vibrational frequencies for CO in 38 h 2 3 faces [39]. The RAIRS study of Wolter et al. recorded absorption spectra rithms 1 and 2 are summarised in Fig. 9. In all cases, the CO stretch exhib- quency generation (SFG) of CO adsorption on Pd NPs and Pd(111) sur- each of the three adsorption sites over a Pd38(Oh) NP derived via algo- tion varies. Figure 16a shows a dramatic exampleforof CO on nanoparticles ranging from Pdb10 to Pd7100 at 90 and 300 K. ited a significant blue-shift with increasing coverage, with the faces [39]. The RAIRS study of Wolter et al. recorded absorption spectra Featuresrithms between 1 and 2 are 1930 summarised and 2000 in cmFig.−1 9were. In all assigned cases, the to CO bridge- stretch exhib-sensitivity of this shift in the order hCO N bCO N lCO, akin to that ob- thesefor CO effects on nanoparticles in the ranging case from of PdCOb10 to adsorption Pd7100 at 90 and onto 300 K. plat-boundited CO, a and signi thoseficant between blue-shift 2090 and with 2120 increasing cm−1 to linearly-bound coverage, withserved the in electrochemical RAIRS studies of CO adlayers on Pd(110), − 1 N N −1 Features between 1930 and 2000 cm were− assigned1 to bridge- CO.− Thesesensitivity1 compare of this extremely shift in favourably the order to hCO correspondingbCO lCO, predictions akin to thatwhich ob- demonstrated a 10 cm blue-shift for θCO =0→ 1 [93]. We at- inum (Pt). The bands at 1853 cm −1 and 2098 cm bound CO, and those between 2090 and 2120 cm to linearly-bound of 1920served–1983 in cm electrochemical−1 and 2062–2106 RAIRS cm− studies1 from our of CO simulations adlayers using on Pd(110),tribute the stronger coverage-dependence observed herein to quantum −1 areCO. characteristic These compare extremely of CO favourably adsorbed to corresponding at bridge predictions andalgorithm lin-which 2 demonstrated(Fig. 8b). The signal a 10 cm from hollowblue-shift CO for (hCO)θCO was=0 reported→ 1 [93]. Wesize at- effects, and note that an earlier study of CO adsorption on Rh4(3,1) of 1920–1983 cm−1 and 2062–2106 cm−1 from our simulations using to betribute weak in the these stronger RAIRS coverage-dependence experiments, however photoelectron observed herein diffrac- to quantumreported an even greater blue-shift of 80 cm−1 [16]. The coverage-
earalgorithm site locations 2 (Fig. 8b). The (see signal Figure from hollow 16b). CO (hCO) As was CO reported surfacetionsize studies effects,[27] andand note RAIRS that measurements an earlier study over of Pd(111) CO adsorption at tempera- on Rh4(3,1)dependent blue-shift may therefore provide a means by which to differ- Fig. 3. Hydroxyl region of IRRA spectra of benzoic acid (BA) on rutile TiO2(110). The sub- b N −1 to be weakstrate in was these exposed RAIRS to different experiments, amounts of however BA at room photoelectron temperature:−1 (A) 0.09diffrac- L, (B)tures 0.18 L,reported200 K an and even350 greater K [92] blue-shiftsuggest of an 80 indicative cm [16] stretching. The coverage-entiate between hollow and bridge/linear bound CO in experimental IR concentrations(C) 0.36 L, and (D) increase, 1.44 L. the 1853 cm mode ex- tion studies [27] and RAIRS measurements over Pd(111) at tempera- dependent blue-shift may therefore provide a means by which to differ- the presence of various TPA species depending on the coverage,Please as cite this article as: C.D. Zeinalipour-Yazdi, et al., CO adsorption over Pd nanoparticles: A general framework for IR simulations on periencestures bdiscussed200 a K broadening and in detailN350 in KSection[92] andsuggest 4. then an indicative splitting stretching into twoentiate between hollow and bridge/linear bound CO in experimental IR nanoparticles, Surf. Sci. (2015), http://dx.doi.org/10.1016/j.susc.2015.07.014 3.3. DFT calculations bridge modes that seems to be an indicator of a CO Fig. 4. IRRA spectra of terephthalic acid (TPA) on rutile TiO2 (110) at different coverages. Please citeIn allthis calculations, article as: adsorption C.D. Zeinalipour-Yazdi, of the deprotonated et al., carboxylic CO adsorption acids in over Pd(A, B)nanoparticles: submonolayer, (C, A D) general monolayer, framework (E) multilayer. for IR simulations on an upright position was assumed. For the remaining proton, the adsorp- nanoparticles,tion at O2c Surf.and Sci. O3c (2015),sites washttp://dx.doi.org/10.1016/j.susc.2015.07.014 investigated. The binding to O2c was found overlayerto be forming 2.5 eV more stable [42]. than As to O the3c. The bridge calculatedmode OH frequencies transi- are lightFigure and adsorbate-related 17: Spectra vibrations of TPAis required. on When rutile, applying going IRRAS −1 −1 3795 cm for O2c and 3614 cm for O3c, respectively. The difference to characterize molecular adsorbates on metal surfaces, the so-called between the two OH frequencies amounts to 181 cm−1. For the numer- surface selection rule has to be considered: Only vibrational modes ical calculations of the OH frequencies, only the movements of the in- withfrom a transition submonolayer dipole moment (A) (TDM) coverage orientated perpendicular to a multi- to tion is occurring,volved O and H a atoms second have been linear considered. mode In also particular appears, for the the surface can be excited by p-polarized light resulting in a reduction
more flexible O2c position, this approximation can cause an uncertainty in reflectivity (positive absorbance bands). In contrast to metal surfaces, in the frequency. forlayer dielectrics (E). (oxides), Reproduced the situationfrom is much more [58]. complex. Both s- and supportingAs theexpected, idea the that adsorbed new carboxylic modes groups are of beingBA and TPA estab- show p-polarized components of the incident light can couple to adsorbate similar vibrational frequencies. We observed the symmetric stretching vibrations (Fig. 6). The sign of the vibrational signals on dielectric −1 −1 νs(OCO) at 1383 cm for BA and 1363 cm for TPA. For the asymmet- materials can be explained by the reflectivity calculations described −1 ric stretching νas(OCO), higher frequencies of 1452 cm (BA) and in Refs. [18–21,29]. The s-polarized light is oriented parallel to the sur- −1 ab initio lished in1441 the cm forming(TPA) were CO obtained. overlayer. BA shows an additional The vibration face and perpendicular to the incidence direction (Fig. 6A). The absor- − −1 with contributions of the COO group at 1409 cm . In our calculations, bance bands excited by s-polarized light (Es) are always negative. For the carbonyl stretching vibration ν(C_O) of the COOH group in TPA is p-polarized light, it is more complicated, the electric field can be orien- −1 found at 1730 cm and the bending mode of the COH group at tated parallel to the surface (tangential p-polarized light Ep,t) and nor- −1 1327 cm . mal to the surface (normal p-polarized light Ep,n). The IRRAS bands A dianionic form of TPA was energetically 2.5 eV less favorable than excited by p-polarized light can be negative or positive depending on the monoionic one. For the dianionic configuration, the first frequencies the incidence angle Θ and the refractive index n of the substrate (see below the C\\H stretching bands are ring vibrations starting at Fig. 6B). The Ep,n component couples only to vibrations with a compo- −1 1600 cm , the asymmetric stretching mode νas(OCO) of the upper nent of the TDM perpendicular to the surface. The component of the − −1 −1 COO group is found at 1470 cm . The bands at 1405 cm and TDM parallel to the surface can be excited either by Es or by Ep,t compo- −1 1344 cm are linear combinations of the symmetric νs(OCO) of13 both nent, depending on the azimuth orientation. carboxylate groups. Since the carboxylate-related IRRAS bands are either negative (in- crease in reflectivity) or positive (decrease in reflectivity), we have cal-
4. Discussion culated the reflectivity differences (ΔR=R0 − Ra) between the clean (R0) and adsorbate-covered (Ra) r-TiO2(110) substrates as a function To gain deeper insight into the adsorption geometry of BA and TPA of incidence angle Θ for both 1426 cm−1 and 1498 cm−1 frequencies.
on TiO2(110), a detailed analysis of the interaction between the incident They show the similar ΔR curves (Fig. 6B). For an incidence of 80°, like
Please cite this article as: M. Buchholz, et al., Interaction of carboxylic acids with rutile TiO2(110): IR-investigations of terephthalic and benzoic acid adsorbed on a single crystal substrate..., Surf. Sci. (2015), http://dx.doi.org/10.1016/j.susc.2015.08.006 modeling of Zeinalipour-Yazdi et al. [57] provides theoretical backing to this notion, predicting a concentration dependent variation in the propensity for CO to be adsorbed at different palla- dium (Pd) substrate sites, the evolution of multiple-peak features, and an overall concentration- dependent mode frequency shift (Figure 16c). At sufficiently high adsorbate concentrations, the mutual interactions also give rise to new collec- tive modes. Adsorbate monolayer formation will occur as the adsorbate concentration increases to effect full coverage of the substrate with further adsorption producing multi-layered coverage; the character of the collective modes evolves during this process as the influence of the substrate on the upper-surface adsorbate layers decreases [37, 58]. Figure 17 provides an example of this effect in the case of terephthalic acid (TPA) on rutile titanium dioxide (TiO2). At low TPA coverage, two C-O stretching vibrations are present with new modes appearing as TPA dosage increases indicat- ing the nascent formation of a monolayer. At even higher dosages, further modes appear and the spectrum begins to resemble that of isolated, solid TPA [58], indicating the influence of the TiO2 substrate has substantially decreased on the regions of the TPA layers most strongly influencing the observed spectra.
3.1.2.2 Hydration
Because of the variable, yet nearly ubiquitous, presence of water in the terrestrial environment, we consider here examples of its interactions with other substances and the impact these interac- tions have on then ˜ of the participating materials. The various themes concerning the impact of intermolecular interactions onn ˜ discussed in §3.1.2.1 appear again in this context; this is not sur- prising given that intermolecular interactions involving water are just a specific case of the prior, more general, considerations. In particular,n ˜ variations will be seen to depend on the details of the substrate media, the specific site to which H2O molecules are bound, and the H2O concentration. Above we explicitly only considered surface interactions between adsorbate molecules and sub- strates; relevant phenomenology in the present case also includes diffusion of H2O into the bulk of the substrate. However, the impact onn ˜ of H2O incorporation into the substrate’s bulk shares qualitatively similar features to the impact of surface-only interactions.
A primary result of H2O-substrate2506 Y. Takeshita et al. / Polymer 55 (2014) 2505e2513 interactions is to produce frequency shifts in the location of H2O ab- sorption features and changes in the strength and shape of these features. The magnitude of these changes de- pends on the nature and strength of the bonds that H2O molecules form both with the substrate andFig. 1.eachVarious possible states of water absorbed into an epoxy network. Not all possible states/bonding arrangements are shown in this figure. The numbers in parentheses correspond to the number of brackets labeled in the Introduction. other [60, 61]. For pure water, in Figure 18: The various forms of bonding between H2O the vapor phase, the H2O fundamen- molecules interacting with substrates. Reproduced from Fig- result of the attraction of two molecular dipoles. It is not necessary 2. Experimental tal symmetric stretching, bending,for one of the atomsure in 1 this of interaction [59]. to be a hydrogen atom, and the interaction typically has a lower dissociation energy than 2.1. Materials and asymmetric stretching modes—hydrogen bonds. (4) van der Waals forces; van der Waals force is the sum of three different molecular interaction forces that can−1 A polytetrafluoroethylene (PTFE) substrate is cleaned and ν1, ν2, ν3, respectively—occurhave at anν attractive=3657, or repulsive 3756, effect betweenand 1595 molecules. cm These (λpainted=2.734, with each 2.662, of the three andcoating 6.271layers consecutively with a forces have very low dissociation energies. (5) Free water; Free brush by hand. A drying time of 24 h is− allowed1 between the µm; [62]). In liquid H2O, thewater stretching is not bonded bands to the polymer are network shifted and simply to lowerfills any frequenciespainting of each layer. (ν For1: individual 3280 layer cm samples,, a single layer of empty space in the network. Various states of water can be grouped the coating system is painted on a PTFE substrate also by hand. For together and detected by using different measurement methods samples on a steel substrate, all sides of the substrate are painted such as differential scanning calorimetry (DSC) and attenuated total equally to ensure that neither the substrate nor the bottom/middle reflectance Fourier transform infrared spectroscopy (ATR FTIR). layer of the coating is exposed. After all the applied layer(s) have Water absorbed into a polymer network can also exist in several dried on the substrate, it is allowed to rest for at least 30 days until ‘states’ that correspond to the14 freezing temperature of the water it reaches an age appropriate for testing. Two different coating [14,15]. The water can exist in the network either as free water, systems were used in this study. The compositions of each of the weakly bound freezable water, or strongly bound non-freezable films are detailed in Table 1. water. Free water, which is unconstrained by molecular bonds to For DSC measurement, samples were removed from the PTFE the polymer network, will freeze at or near 0 C. Weakly bound substrate and cut into small sections approximately 10 mg in mass. freezable water is connected to the polymer network through weak The samples were weighed and placed in distilled water for a intermolecular bonding. This bonding to the network lowers the certain amount of time to absorb water, for instance, two days. After freezing temperature of the water [14e16], which was observed to absorption, the samples were removed from the water, dried using be between 40 C and 65 C in our research. Strongly bound a paper towel, and again weighed. The samples were then placed in À À non-freezable water is bonded to the polymer network through DSC sample pans, which were crimp-sealed. strong intermolecular bonds such as hydrogen bonds. These bonds For ATR FTIR measurements, the samples were removed from prevent the water from freezing at any temperature. Different the PTFE substrate and cut into squares approximately 1 cm 1 cm  states of water are detected through differential scanning calo- in size. rimetry (DSC). During the cooling process water will create an exothermic peak as the latent heat of fusion for each state of water 2.2. DSC measurements is expelled as that state freezes. IR spectroscopy provides information about the types of bonds The samples were tested as soon as possible after preparation to within a material by measuring the resonant frequency of the minimize any loss of absorbed water through evaporation. The bonds. Specific absorption peaks in the IR spectrum correspond to prepared samples were placed in a DSC (EXSTAR DSC 7020, SII the deformation of a specific bond, such as OeH or CeO, through Nano-technology, Japan) testing chamber. The location and size of either stretching or bending deformation. Identifying the type and DSC peaks depended heavily on the heating/cooling rate of the relative number of bonds within a material provides a powerful system, and whether the sample was being measured during the tool for characterizing the internal structure of the material. heating or the cooling process. Previous tests have shown that the In this study we attempt to estimate the manner in which water peaks that appear during the cooling process are more separated absorbed into a water-based epoxyeurethane coating system is and well-defined than those that appear during the heating pro- bonded to the polymer network. We characterize absorbed water cess, with lower cooling rates producing more separated and into states based on the results of testing performed by using dif- defined peaks. Therefore, the cooling process and its rate of 2.5 C/ ferential scanning calorimetry and attenuated total reflection IR min were chosen to produce well-defined and easily measured spectroscopy. The individual layers of two different coating systems peaks. The large temperature range was chosen to ensure that all are tested and the results are correlated with the molecular possible transition peaks were covered in the testing range and that structure of the materials to understand how specific functional there was a cushion space between the peaks and the edge of the groups of the molecule contribute to the population of each state of testing range. The program was then run with starting and final absorbed water. temperatures of 25 C and 75 C, respectively. À E12001 MILLIKEN AND MUSTARD: WATER CONTENT OF MINERALS E12001
Figure 19: Reflectance spectra of hydrated montmorillonite clay (left-hand panel) and magnesium sulfate as the samples are heated, driving off sorbed water. Reproduced from Figure 7 of [69].
−1 −1 ν3: 3490 cm ; [63]) and the bending mode to higher frequency (ν2: 1644 cm ; [64]). The ν-shifts are due to hydrogen bonding [65] that tends to create short-lived tetrahedral molecular networks in the liquid phase [66]. Similar considerations apply in the solid phase, where the de- gree of crystallinity and Tth impact band location and strength[18, 67, 68].
The ν-shifts seen in H2O-substrate systems similarly result from several different bonding mech- anisms of varying strength, illustrated schematically in Figure 18 [59]. Direct hydrogen bond- ing between a H2O molecule and a strongly polar region of the substrate molecule provides the strongest bond. Next is secondary hydrogen bonding where a second H2O molecule binds to a polar region of the substrate via another, directly hydrogen-bonded H2O molecule. Dipole-dipole interactionsFigure 7. provideContinuum-removed the next strongest spectra bond, of purging followed series by for the (a) weaker SWy-1 montmorillonite bonding due to and molecule- heating moleculeseries van forder (b) SWy-1, Waals interactions. (c) Mg-exchanged In addition SWy-1, to(d) the reagent-grade fundamental MgSO stretching4, (e) a Hawaiian and bending palagonite, bands, and (f) clinoptilolite (a zeolite). The strength and shape, as well as the evolution during dehydration,−1 of several H2O overtone and combination bands near ν ≈ 7000, 5200, and 4540 cm (λ ≈ 1.43, the water absorptions vary greatly between these samples. A 3 mm band is present in all samples even 1.93,after and they 2.2 µ havem) been are particularly heated to 800 diagnostic°C, but the of 1.9 themmcombinationovertoneand2.2 relative importance of variousmmmetal-OHband bonding mech- anismstypically in water-substrate disappear at T systems>500°C. across Temperature multiple values substrate represent material the highest classes. temperature to which the sample was heated and are not necessarily representative of the temperature of the sample during the For example,FTIR measurements. in smectite All clays purging water or can heating bind spectra to clay for interlayer a given sample surfaces, were interlayer acquired on cations, the same and day be adsorbedusing on the to same grain sample. surfaces (in addition to the ubiquitous H2O-H2O bonding) [70]. Water inter- acting with such clays (see, e.g., the left-hand panel of Figure 19) show splitting of the fundamental bands that are interpreted as being due to cation bound versus adsorbed H2O molecules [70–75]. The λ ≈ 1.43 and 1.93 µm combination/overtone13 of bands 25 exhibit the same splitting [72, 74, 75]. Both H2O-bonding types can be present simultaneously in the clay. The broad class of silicate (SiO) minerals can be hydrated to various degrees with H2O bonding through direct or indirect hy- drogen bonding and dipole-dipole interactions, each of which exhibits absorption bands at different frequencies [76–78]. The 1.9 and 2.2 µm combination bands again exhibit λ-splitting attributed to the two hydrogen bond types [79, 80]. Studies considering H2O interactions with various poly- mers come to similar conclusions concerning the presence of two or more H2O-polymer bonding mechanisms based on ν-shifts and evolution of various band components as a function of hydration level [59, 66, 81–90].
As the H2O concentration in one of these systems is varied, the relative contribution to the overall absorbance made by differently bonded H2O molecules changes. For Na- and Mg-montmorillonite
15 A. Lasagaba´ster et al. / Polymer 50 (2009) 2981–2989 2985
0.35 νOH -1 8466 Z.H. Ping et al. / Polymer 42 32001)7 8461±8467 3537/20 cm 3193/50 cm 0.30 -1 2150 cm 6 δOH 700 cm-1 0.25 ν OH 5 /s)
0.20 2 4 (m δ -1 OH 700 cm -14 0.15 3 Dx 10 0.10 2
Absorbance (arbitrary units) 0.05 1 2150 cm-1 0.00 0 4000 3500 2500 2000 1500 1000 500 10 20 30 40 Wavenumber (cm-1) %EVOH Fig. 5. Changes in the wave number of the hydroxyl stretching vibration in Fig. 5. Diffusion coefficients for water vapour at 25 C and 0.98 water activity in PP/ Fig. 3. Subtractionthe FTIR PE- spectrag-AA2Li collected1 membrane at different with the watersorption content times inthe in themembrane; case of a: Fig. 6. Changes in the spectra of the PVA hydroxyl stretching vibration with (a) EVOH films as a function of EVOH(b) content. water vapour sorption test at aw 0.98 in a 70/30 PP/EVOH film. the water content in the membrane; a: 4.2%, b: 6.3%, c: 10.2%, d: 19%, e: 0%, b: 5%, c: 17%,¼ d: 31%, e: 48%, f: 54%, g: 64%. 40%, f: 59% (the spectra were obtained by subtracting the spectra of swel- Figure 20: (a): Evolution of absorption bands in a PP/EVOHling membranes film as from its that hydration of the dry ones). increases; repro- assigned to vibrations from the scission and rocking of water; the mean diffusion coefficient. Fig. 5 gathers the D values of the main duced from Figuremolecules 3 of (due [84]. to an entropy (b): Changes effect) throughout in1 the the hydroxylentire stretching mode of PVA membrane for water OH in-plane bending vibration (dOH) at 1652 cmÀ and the water bands and the two peaks that form the fundamental OH 1 polymer matrix. On the contrary, in hydrophilic polymers, site (compared with that of hydrogen-bondable molecules) different700 cmÀ degreesband arising of hydrations; from the out reproduced of plane vibrations from of Figure O–H 6stretching of [82]. vibration, as function of EVOH content at a 0.98. A water molecules are so strongly bound to speci®c polar sites for PVP and for PE-g-AA salts (Table 1), where non-freez- w ¼ groups or librations.by hydrogen The fundamental bonds that they OH cannot stretching gather with vibration other mole- is firstable look water reveals must that consist the of D values molecules diminish coming linearly from the from 10 to 30% divided into twocules peaks. to form The crystallizable one in the water.higher The frequency removal region, of water EVOH.second Nevertheless, hydration layer. except for the bending band, these differences 1 (smectitearound 3520–3530 clays),molecules cmtheÀ , evolution from has been the sites assigned of would the to require unassociated two 1a large9 water,m driving bandslie under within the varying experimental hydration error (ANOVA levelsP < demon-5%), which is mainly dimers and looselyforce bound (chemical water. potential), The peak which in the cannot lower be. frequencyprovidedµ by due to the difficulty to obtain reproducible film thickness and the stratesregion a is structural associatedthe surrounding with change water medium bound with during by a strong feature-shoulder cooling. hydrogen bonds todue tonon-uniform4. the Conclusionλ ≈ composition1.96 µm profile band within disappearing each sample. at Secondly, the The OH stretching band of liquid water is very large, 1 1 lowthe hydration polar groups levels, of the polymer while[8] the. 1.91 µm feature remains,coincidence albeit at of lower the D strengthvalues of the (left-hand 2150 cmÀ , paneldOH and 700 cmÀ Sorption curveswithout were shoulders, plotted asdue percent to the existence absorbance of continuum gain of the of peaksBelow could a water allow content the use threshold of any whose of them value to depends determine on diffusion ofwater Figure bending 19).hydrogen band This (dOH bondsis) interpreted vs. of square different root strengths. as of implying time Although for PP/EVOH the the alcohol 1.96 (ANOVA,µthem chemical bandP < 5%).being and physical However, due structures to the surface best of the candidate polymer,adsorbed is the the bending films of increasinghydroxyl EVOH stretching content band at a inw PVA0.98 is also (Fig. large 4). The and is linear in the vibration,water molecules because absorbed the errors in hydrophilic associated polymer with it cannot are smaller. The H2O while the 1.91 µm being produced¼ by the tightly bound interlayer surface and cation H2O shape of the curvessame frequency up to 50–60% range, wemaximal were able sorption to evidence levels its indi- varia- reasonform ice lies crystals in the in thefact polymer that this matrix. band Beyond does this not thresh- overlap with the tion in frequency with increasing water contents in the poly- moleculescated that thethat processes requires can significantbe described as dehydration Fickian. Furthermore, to drivepolymer offold, the[69, signalsabsorbed 70]. and water A does similar crystallizes not shift trend at over a temperature the occurs entire lower sorption for process mer by subtracting the spectrum of the dry membrane to that than the normal-water melting point, which increases with from least-squares analysis of the data using Eq. (10), the n values [5–7]. Therefore, we will mainly refer to the bending band from the splits in theof theν1 swollen-band membranes located (Fig. at 6).λ One≈ 2 can.83 see andtwo distinct 2.98 µmincreasing in the water same content Figure in the polymer. 19 panel, Although with the water the for the four water bands were approximately 0.5, corroborating now on. bands at ®xed frequencies but with different intensities, molecules of this type are not directly attached to the poly- 2.83Fickianµm diffusion, band that independently creates the of shoulder EVOH content in the and large waterλ = 2Concerning.75 µm feature the fundamental produced stretching by the region, more the diffusion depending on the water contents. The OH stretching band mer polar sites, their behavior is1 modi®ed from that of bulk activity. 2 2 tightly boundat H 32802O cm molecules.1 is more pronounced The λ than= that2.2 atµ 3400m cm band1 coefficients inwater. the same of the system 3190 cm isÀ producedpeak are approximately by Mg- twice the OH directThe diffusion hydrogenwhen coefficient the bonds water (D content) was and assumed in persists membrane to be until is independent lower very than 20%. significant of valuesWe dehydration showedof the that higher the absorbed frequency occurs. water band The in hydrophilic in right-hand the four poly- compositions the concentrationWhen of the water penetrant content and in PVA Eq. (9) increases,used to the calculate OH stretching the studied.mer develop Moreover, two types the ofD hydrogenvalues of bonds, the latter one corresponds are in agreement with panel of Figureband 19 at 3400shows cm21 similarlybecomes more the and more spectral intense variations(Fig. 6). thoseto of water of magnesium the molecules other water directly sulfate bands, attached supporting at to thevarious active the site levelsidea of the that the global diffusion process at high water activity is governed by the diffusion of hydration; theThese differences two bands have in approximately H2O band the same shape intensities and at evolutionpolymer relative to form the to ®rst the hydration Mg-montmorillonite layer, the second to ca. 20 wt% of water in the polymer (Fig. 6). Thus, there are ofwater loosely molecules bound in water the second and that hydration the different layer. The types latter of water are 2400 highlight the facttwo distinct the substrate populations materialof water molecules, strongly which influences are absorbedare present the at morphology in a different the polymer rate. even of at the low water OH contents, features. i.e. In silicate minerals,present at lower every water water content concentrations level in the polymer. lead The to SiOHtheFrom second another features hydration point becominglayer of view, can be the formed more bending on certainapparent band sites diffusion coeffi- 2000 non-freezable-water fraction in polymer systems40% of low cientsbefore for all PP/EVOH polar sites 90/10 are saturated and 70/30 with films water are molecules. presented in Fig. 6 as relative to non-bondedwater content water includes features then water molecules [91]. of the second aThis function difference of water in the activity, type of together the water with molecules data found bound in literature hydration layer. However, there should also be a dynamic forto EVOH the polymer copolymer polar sites of the led to same the observed ethylene changes grade in[4] the. 1600 In polymers, theexchangeν1 and of waterν3 moleculesfrequencies between sites tend and to hydration shift to lower-frequenciesbehaviorIn relation of the to absorbed PP/EVOH water with 90/10 in crystallization. increasing films, the diffusion The bond non- coefficients 30% layers. Apparently, these exchanges did not prevent the decreasefreezable exponentially water did not consist with exclusively water activity, of water reaching mole- a constant strength betweenmolecules a H from2O molecule being under theand polar-site the substrate interaction [84];cules so, from e.g., the ®rst for hydration2 H2O layer. in polypropylene- 1200 value at aw 0.82 (r 0.998). The same trend is observed for 70/ ®eld, which kept the water molecules non-freezable. The different¼ states¼ of water in hydrophilic polymers poly(ethylene-co-vinyl Areas /100 g polymer alcohol) (PP/EVOH) mixtures, the30 films stretching but the transition bands occurs develop at a lower two water peaks, activity, 0.55–
OH These results are also consistent with the high values of re¯ect the power of the interactions between the absorbed −1 20% 0.68 (r2 0.990). Moreover, 70/30 films display significantly lower one in800 the 3520-3530the average cm number ofrange non-freezable produced water molecules by unassociated per molecules and¼ and weakly the polymer bound sites. H The2O in¯uence and another of these −1 values than 90/10 blends (Student’s t-test, P < 0.05) in the whole near 3200 cm associated with H2O hydrogen bondedactivity to polar range. groups Similar results within have the been polymer, encountered as for the other shown400 in Figure 20. Lines in this figure correspond10% to spectrawater bands. obtained at different times during −1 Opposite to inert gases, marked decreases of the diffusion a waterNormalised sorption process. The 3200 cm peak predominatescoefficients at with first water and vapour is then concentration overtaken have by been observed −1 the 35000 cm peak as time goes by, indicating that asin several water polymers. diffuses This in is the a consequence substrate, of the direct strong localized 0 100 200 300 400 500 interactions developed between the water molecules and polar hydrogen bonds form first,t1/2 followed (s1/2) by weaker indirect hydrogen bonding. The weaker bonds groups in the polymer [29,30]. Accordingly, the decrease of the D continueFig. 4. FTIR forming water sorption at curves a faster for PP/EVOH rate films as of water increasing content EVOH content increases at values [84; with 85–87, water activity 92 report is a consequence similar findings]. of the ‘‘sticking’’ of the This25 C behavior and 0.98 water appears activity. similar to a saturation effect noticedfirst water by Ping molecules et al. at the [82] OH in groups their of studythe EVOH of forming the water in hyrdophilic polyvinyl alcohols (PVAs); there up until some critical water concentration,
16 2674 C. Sammon et al. / Polymer 44 (2003) 2669–2677
4.5. The effect of water–polymer molecular interactions
Because the n OH (or n OD ) bands of liquid water are sensitive primarilyð toÞ water–waterð Þ OH–O interactions (and collective) dynamics, it is not obvious from such profiles (nor with their change as a function of sorption [1–3,34,42]) that strong water–polymer interactions are formed. There are, however, sometimes obvious markers for such inter- actions. Two particular ones are found in this work are shown in Figs. 8 and 9. The wider literature demonstrates that normal modes of a number of chemical groups (notably –CyO, CyN, SO, NO2, etc.) may shift and intensify when hydrogen bonding takes place in liquid mixtures [6,7,16,17] or in thin films [67,68] or at interfaces [69]. But relatively Fig. 7. The effects of isotopic dilution in the n OD band of a D O (4%) ð Þ 2 little work of this kind has been published for polymeric H O mixture in S8 polymer. (A) n OD band of HDO in liquid 2 ð Þ functional groups. Nevertheless, there is good evidence D2O(4%)/H2O mixture. (B) n OD /band of HDO in the polymer. ð Þ from a variety of sources that water–polymer hydrogen- bonding does occur [28–47,70,71]. Fig. 9 potentially band shape. We have determined P based on Eq. (1) with provides a detailed ‘snapshot’ (over the first 20 min of concentration adjusted for the equilibrium represented by water sorption) of the changing polymer–water interactions Eq. (5). The results are included in Table 1. It is seen that the as water enters the ‘free volume’ (defects, microvoids, etc.) P values are somewhat greater for the decoupled water in the polymer matrix. It is clear that the shift of the n CyO ð Þ molecules HOD than for D2O (or H2O) molecules. The band of PET is due to such interactions. Fig. 10 shows that possible significance of this result is discussed below. But it strong water interactions with the polymer surface occur at is clear that the high extinction coefficients are not solely 3–4 min into the sorption process and again at about due to ‘collective mode’ intensity, nor to delocalised ‘OH’ 20 min. We interpret this to mean that between the two motions, nor to intramolecular coupling. 168 A. Wang, Y. Zhou / Icarus 234 (2014) 162–173 4.4. The effects of ‘percolation’ processes
There have been a number of investigations [64–66] of a b ‘percolation’ based processes in polymeric materials, mainly connected with the calculation or simulation of percolation thresholds for drug-release from porous media. a However, the direct measurement of transport coefficients with fractal dimensions in porous media does not seem to have been reported in the polymer literature, possibly because ‘pore’ design and/or control is difficult. It is unlikely therefore that ‘collective’ water transport phenom- ena in polymers could be detected using vibrational spectroscopy, especially for systems without any control of pore distribution.
Table 2 Comparison of band positions and widths of n OH and n OD bands of ð Þ ð Þ water, both coupled and decoupled vibrations
Pure water Water in SPEES/S8
Position Width Position Width (cm21) (cm21) (cm21) (cm21)
n OH H2O 3200–3500 ,450 3200–3600 ,450 ð Þ n OD D2O 2400–2600 ,300 ,2500 ,320 ð Þ n OH HDO (4%D2O) ,3400 ,350 ,? ,? ð Þ Fig. 8. The IR n SO2 band of PES (S5) before and after hydration sð 3 Þ showingb strong polymer water interactions. (Reproduced, from Pereira M, Fig. 6. Raman spectra of dehydration products of epsomite under Mars relevant n OD HDO (4%D2O) ,2500 ,230 ,2550 ,230 (a) (b) ð Þ PhD Thesis, Durham University, 1994.) pressure and partial H2O pressure at 294 K: (a) spectral range for H2O vibrational modes and (b) spectral range for fundamental modes of SO4. Figure 21: (a): Changes in polyether sulphone ν(SO−) bands with increasing hydration; reproduced obviously3 relate to their structural and chemical features, which from Figure 8 of [66]. (b): Evolution of hydratedwould MgSO affect the4 activationspectra energy with values changing for phase degree transitions. of hydration; reproduced from Figure 6 of [97]. 4.2. Results of LRS measurements – the dehydration pathways
Laser Raman spectroscopic (LRS) measurements were taken on only strongly bound H2O molecules were present.five reaction Above vials from this each ofconcentration, six sets of dehydration the experiments number of H2O molecules directly bound to the polymer quicklyof alunogen saturates and melanterite. while Those weakly-bound reaction vials were taken H O out molecules from the vacuumed desiccator at pre-determined different2 time appear and continue to increase in number.intervals The that number are larger of than strongly-bound those for gravimetric measurements. H2O molecules at These reaction vials were never put back, thus the dehydration saturation depends on the polymer involvedproducts and reflects in the vials the maintained overall the ability same structural of a formpolymer’s and polar groups to interact with H O in the polymer matrix.hydration degree A different as they were H takenO out. binding In addition order to LRS was mea- observed 2 surements, XRD measurements were2 made on the samples to con- c for water diffusing into a polyhydroxyalkanoate,firm LRS where phase H identifications.2O molecules The mass first measurements diffuse into of the the micro- dehydrated samples corresponded with the five LRS measurements voids in bulk water form or are dispersed on theare marked surface as large in diamonds free water with black form, edge and in Fig. then 5. The penetrate aver- into the polymer matrix and hydrogen bond withaged the numbers polymer’s of H2O hydrophilicper salt molecule weregroups marked [90]. in Figs. 6–8, next to their Raman spectra. For comparison purpose, Raman spectra of dehydration prod- Water diffusing into a substrate material canucts affect of epsomite the substrate’s from a similar set structural of experiment and run under chemical Mars proper- relevant conditions were first shown in Fig. 6 (experiments re- ties. Exposure to water can lead to hydrolysisported in in someWang etpolymers al., 2009). At and 294 K, alter epsomite the first polymer’s dehydrated intrinsic
partially to hexahydrite (MgSO4 6H2O) in 20 min, shown as m1 peak hydrogen-bonding interactions[82, 93, 94]. Water sorption1 causesÁ polymer1 to swell [87], decreas- at 984.1 cmÀ shifting to 983.6 cmÀ (Fig. 6b) accompanied by a
ing polymer crystallinity, increasing molecularchange mobility, of H2O peak and shape reducing and additional glasspeak transition shoulder temperatures near 1 [95, 96], particularly in hydrophilic polymers3200 [82]. cmÀ (top Such three structural spectra in Fig. 6 changesa). This phase have transition corresponding re- flects the lost of one structural H2O per epsomite that is not coor- impacts on spectral feature locations and morphology.dinated with Mg E.g., cation Schoonover but weakly bonded et al. in crystal [93] lattice reports by shifts in Fig. 5. Number of H O per sulfate molecule (Al (SO ) 17H O, FeSO 7H O, and 2 2 4 3Á 2 4Á 2 hydrogen bonding (the H2O molecule colored in yellow in epsom- MgSO 7H O), as n(t)/n(0)m (%) vs. experimental duration in minutes, during the N-H4Á 2 and carbonyl group modes’ frequenciesite as structure, a functionFig. 1c). The of continuous hydration dehydration in a poly(ester caused the col- urethane). process of dehydration under Mars relevant P and PH2O, calculated based on gravimetricOther measurements. frequency-shifts Each point is the average in various mass value at polymer specific time groupslapse of are hexahydrite reported lattice in that [82, produced 90]. Figure the amorphous 21a shows an interval during dehydration, calculated from the averaged mass measurements of MgSO xH O, shown as the appearance (starting at 40 min) and 4Á 2 − 10 sampleexample vials after of removing hydration-induced the maximum and minimum shiftsvalue. The standardin the symmetricgrowth of a veryν(SO broad m)1 bandRaman peak in a (Fig. polyether 6b). Following sulphone the [66]. deviation of the ten values is calculated and shown as error bars. Temperates of the development of dehydration3 (from 5.5w to 1.8w), the central posi- experiments are (a) at 294 K; (b) at 273 K, (c) at 261–265 K. Larger symbols with 1 tion of this broad peak continued a shift from 1025 to 1034 cmÀ blackIn edge hydrated represent the time sulfate intervals when minerals, a sample were changes taken out for inlaser hydration can initiate changes in crystal structure [97], Raman spectroscopy measurement and the Raman spectra were presented in (indicated by a dotted line in Fig. 6b). The last four spectra in Figs.again 6–8. leading to variations in spectral features.Fig. 6b Figure suggests 21b that provides the entire Mg-sulfate an example sample of became variations in H2O and SO4 bands in epsomite as the sample’s hydration is reduced. The disappearance of the 983 cm−1 peak and appearance of a peak near 1025 cm−1 (that shifts to higher ν as dehydration continues) is due to a phase change that occurs due to the loss of one H2O molecule per epsomite that is not coordinated with a Mg cation [97].
17 G. Openhaim, E. Grushka / J. Chromatogr. A 942 (2002) 63–71 69
24 The European Physical Journal E
Fig. 2. Refractive index of methanol–water vs. % methanol. ♦, Fig. 5. Refractive index of 1,3-dioxolane–water vs. % 1,3- ♦ 8 j 8 m 8 8 3 8 d 258C; j, 308C; m, 358C; —, 408C; 3, 458C; d, 508C. dioxolane. , 25 C; , 30 C; , 35 C; —, 40 C; , 45 C; , 508C.
Fig. 3. Refractive index of acetonitrile–water vs. % acetonitrile. Fig. 6. Refractive indices of the(a) four mobile phases as a function ♦, 258C; j, 308C; m, 358C; —, 408C; 3, 458C; d, 508C. of modifier percentage at 308C. ♦, 1,3-dioxolane; j, THF; m, Fig. 3. a) Comparison between(b) the experimental data of this ACN; d, MeoH. work (open circles) and those of ref. [12] for the temperature Fig. 4. a) Concentration dependence of the slope (dnD/dT ) Figure 22: (a): Changes in solution n (λ = 254 nm)of 20 with◦C. b) solvent Comparison mixing between fraction the experimental for 1,3 dioxolane data of this obtained after a non-linear square fit of the experimental data work (open circles) and those of ref. [25] for the temperature (see, for instance, fig. 2a) to a straight line in the tempera- (diamonds),2 acetonitrile (triangles), THF (squares), and dichloromethane (circles); reproduced from of 25 ◦C. ture range between 15 ◦Cand27◦C. The inset in this figure RI i 2 1 FigureR 5V ]] 6 of [98].] (b): Changes in solution n with(4) H2O mol% for water-ethanol mixtures; reproduced magnifies the low water concentration region and the vertical iiRI 2 1 2 from Figurei 3 of [99]. straight line is a mass of the relative error in the estimation of where V is the molar volume of the component and the slope. b) Example of the corresponding residuals for three i different water concentrations of the ethanol-water samples. RI is its RI. ular segregation and existence of water clusters formed i most likely by three water molecules [10]. This indicates 3.1.2.3The molar Interactions volume of each in Liquid pure liquid Solutions was calcu- atendencyofwaterandalcoholtosegregateandbuild lated by dividing the molecular mass by the density percolated networks [11]. The maximum in nD(x)and Aat substance 298.158K. Thein solution values obtained, experiences in ml/mol, a significantly are anomalies different in other distribution magnitudes of haveintermolecular been related forces to these the sense of a perturbation in the intermolecular inter- than40.7012 when for inMeOH, isolation. 52.8995 As for in ACN, the two81.5699 cases for examinednetworks. so At far, very the low change water concentrations in potentials it seen seems by un- actions. For this concentration, it is energetically more THF, 69.5979 for 1,3-dioxolane and 18.0630 for likely that percolated networks are built but the water efficient to extract molecules from the liquid to the at- bothwater. solute With the and aid solvent of Eq. (4), molecules and the molar in a solution volume canmolecules lead to may changes rather in form both clusters component’s that evolven ˜ and to a the per- mosphere. This concentration coincides with that where overallvalues mentioned spectral characteristics here, the molar of refractive the solution. indices colated network with increasing water content. Moreover dnD/dT and the thermal expansion coefficient deviate from the smooth behaviour. As far as dn /dT and n Fig. 4. Refractive index of THF–water vs. % THF. ♦, 258C; j, of the components were calculated. The values are the pressure-dependent elastic constants show an anomaly D D at about 20 mol% water in methanol [30] that can be a hint do not represent the same physical mechanisms, the two 308C; m, 358C; —, 408C; 3, 458C; d, 508C. As8.2330 in the for case MeOH, of adsorption, 11.1540 for where ACN, 20.0033 adsorbate for concentration influencesn ˜ behavior, solute concen- tration is also an important variable. For example,to thesomen changesof liquid in intermolecular mixtures varies binding as a or function segregation. of anomalies can be of different origin and it is difficult to in- Assuming the above discussion, the maximum in nD(x) fer whether the intermolecular perturbation and the clus- the mixing ratio of the solution. Examples of suchobserved behavior at about are shown 40 mol% in water Figure in ethanol-water 22 [98]. In the mix- tering and evolution towards percolation are related effects case of solutions of 1,3 dioxolane (diamonds) andtures THF could (squares) be related in water, to cluster the formation. variation In of thisn with sense or not. This intermolecular perturbation could be also re- the 10 mol% water concentration in ethanol-water mix- sponsible for the suppression of monoclinic and plastic solvent mixing fraction is monotonic between theturesn of seems the individual to be also components. a special value However, as is the aque- case of crystalline phases observed in Brillouin spectroscopic ex- ous solutions of acetonitrile and dichloromethaneabout (triangles 20 mol% and water circles) in methanol-water exhibit a non-monotonic mixtures. The ex-n periments on ethanol due to non-controlled moisture. Un- that peaks near a 50/50 mixing ratio and that exceedsistence the of index a minimum of either in the pure boiling liquid. point Water-ethanol at atmospheric fortunately, the actual water concentration of the samples solutions exhibit similar behavior as seen in Figurepressure 22b [99]. of ethanol-water This non-monotonic mixtures can behavior be interpreted would in was not clearly established [26]. appear to indicate that new energy states are being generated by solute-solvent interactions. The absorption features of a compound in isolation versus in solution show shifts in ν due to in- teractions between the solvent and solute [e.g., 47, 102–106, for a small sample]. This behavior is so common that multiple constructs have been developed to quantitatively describe the observed shifts [e.g.,see references in 102, 107]. Band shifts and band shape variations are dependent on the solvent materials [see Figure 23a; 100]. Solute-solvent interactions may also produce solute molecule conformation changes [108]. Additionally, there are examples of solute absorption fea- tures splitting in solution. Further, the ν-separation between such split-modes can depend on solute concentration Hernandez´ et al. [106]. In Hernandez´ et al. [106], the authors proposed the observed mode splitting mechanism to be solute-solute interactions that indirectly involves water molecule complexes interacting with several different groups in the solute molecules. Finally, the solute’s band shapes and positions can also depend on solution concentration [see Figure 23b; 100, 101].
18
34 D. Yamini et al. / Vibrational Spectroscopy 61 (2012) 30–37
502 I. Bratu et al. / Spectrochimica Acta Part A 54 (1998) 501–506
2. Experimental m−1 n 2 −1 w =A+B +C s 2m+1 2n 2 +1 2-BrP, a polar molecule (2.04 D in C6H6), was (m−1)(n 2 −1) purified by distillation. Solvents of UVASOL +D (1) (2m+1)(2n 2 +1) grade from Merck were used without further purification, except chloroform which contains accounts for the influence of polarity ( f(m)-term ethanol as stabiliser and consequently was dis- characterized by the relative permitivity m) and the 2 tilled. Their refractive indices n (at room tempera- polarizability ( f(n )-term characterized by refrac- ture) and the dielectric constants were taken from tive index n). To evaluate the importance of the 2 literature [2]. In order to minimize the quasi reso- last term ( f(m, n )-cross term) in Eq. (1) which nant transfer of the vibrational energy to different describes the mutual influence of the two men- solvents vibrational modes, they were selected so tioned effects, a multidimensional regression anal- ysis [6] was performed. The A, B, C and D as not to absorb in the proximity of the w(C–Br) constants are: (547.048, −26.898, −1.624 and 0) band. and (546.458, −15.484, 3.142 and −63.807) Infrared spectra of pure liquid and of various when the last term is neglected or taken into solutions were recorded at room temperature on a consideration, respectively. The correlation factor SPECORD 75 IR Carl-Zeiss Jena spectrophoto- r of the multilinear regression (in 13 selected meter. The scanning parameters were carefully solvents) increased from 0.976 to 0.983 when the selected to avoid distortions of the band shape. cross term was considered. Therefore, in order to The spectral slit width was set at about 1.2 cm−1 and the spectra were digitized at a 0.5 cm−1 step. The profiles were recorded at least five FWHH
(Dw1/2) far into the wings. The base lines were constructed by joining the flat ends of the band. A variable path length cell was used to compensate the absorption due to the solvent. The Fourier transform of the infrared absorp- tion bands i.e. the time correlation function IR(t) was obtained using a modified program described in Ref. [3].
3. Results and discussion
3.1. Sol6ent shifts
A selection of the w(C–Br) band profiles for 2-BrP in pure liquid and in different solvents (of 1 M concentration) is presented in Fig. 1.
The values of the peak maxima, ws, in all inves- tigated solvents, (Table 1), are shifted towards lower values relative to the gas phase frequency. The frequency of w(C–Br) in gas phase IR spec- −1 trum was measured by us, (wg =551 cm ); the
literature [4] gives a value of 549 cm−1 obtained
from the Raman spectrum. Fig. 1. The IR profiles of the(a)w(C–Br) band of 2-BrP inFig. pure 5. Carbonyl stretching wavenumber of(b)2′-HAP in the three different solvents at
The well known Buckingham equation [5], liquid and in different solvents at 1 M concentration. different mole fractions of 2′-HAP: (a) methanol, (b) acetonitrile, (c) carbon tetra- chloride.
Figure 23: (a): The transmission spectra about the ν(C-Br) band of 2-bromopropane in the indicated
Fig. 6. Variation of Raman peak position with changing mole fraction of 2′-HAP in
solvents showing how the band’s shape and location depend on the solvent; reproduced from Figure binary liquid mixtures: (a) methanol, (b) acetonitrile, (c) carbon tetrachloride.
This causes the increase in the carbonyl stretching wavenumber in
1 of [100]. (b): The carbonyl stretching mode of 20-hydroxyacetophenone in carbon tetrachloride at
the Raman spectrum for decreasing concentration of the solute.
different solute concentrations; reproducedThe from carbonyl Figurestretching 5 of [101].wavenumber in the binary liquid mix- makes the carbonyl bond free which increases the force constant
ture of 2′-HAP and acetonitrile exhibits an upshift in the Raman of the carbonyl bond. This is the reason for the observed increase
spectrum for decreasing concentration of the solute. Acetonitrile, in the carbonyl stretching wavenumber in the Raman spectrum for
beingThe a polar miscibilityaprotic solvent, of binaryforms liquiddimer mixturesat lower isconcentration another phe- decreasing concentration of the solute. This behaviour of carbonyl
of thenomenonsolute. In binary that couldliquid havemixture interestingwhich consists implicationsof freely rotat- for a stretching wavenumber is represented as a minor deviation from
ing moleculessolution’sthe spectrum.only possible Ininteraction general, theis between miscibilitythe dipole of bi- linearity in Fig. 6b.
moment of the carbonyl group of the solute and the dipole moment The carbonyl stretching mode of 2 -HAP in the binary liquid mix-
nary liquid mixtures exhibits a dependence on temper- ′
of the solvent. The acetonitrile dimer orients along the direction of ture of 2′-HAP with carbon tetrachloride on dilution also displays
the electricature thatfield canof the besolute describedto have bya possible a phaseinteraction diagramwith simi-it an upshift in the Raman spectrum. The dipole induced dipole inter-
whichlar results to left-handin the formation side ofof Figureweak attractive 24 [109].type AtC sufficientlyH O and action exists between chlorine atom in carbon tetrachloride and
· · ·
C H N intermolecular hydrogen bonds. As a consequence of this highly electronegative oxygen atom in carbonyl group of 2 -HAP. As
high· · · temperatures, the mixture is totally miscible. As ′
dipole–dipole interaction, it weakens the OH O C fragments and a result of this interaction the intramolecular hydrogen bond gets the temperature is lowered, a phase· transition· · occurs and the single solution separates into two phases of different concentration ratios, and therefore different refractive in- Figure 24: Prototypical phase diagrams dices. At the interface of the two phases, reflection will for binary liquid mixtures. Reproduced occur due to the mismatch in refractive indices in the two from [109] phases. As the phase diagram shows, the concentration ratios of the two phases, and therefore the corresponding n˜, exhibits a Tth-dependence throughout the phase diagram, translating to a temperature dependent reflectance at the interface between the two phases. In some special cases, the coexistence curve will form a closed loop as shown on the right in Figure 24,where the liquids will return to a single miscible phase below some lower critical Tth.
19
10-13 In transmission mode, the infrared absorption spectrum of NaNO3 has been measured by various groups. The nitrate 11-13 anion has trigonal planar geometry and belongs to the D3h point group. The fully symmetric N-O stretch is ν1, and since it belongs to the a1g irreducible representation, it is only Raman active. For the IR-active modes, Harris and co- workers8 measured the absorption spectrum from 2000-600 cm-1 and observed the strongest band around 1378 cm-1 -1 which is assigned to ν3, the asymmetric stretch. A weaker band at 836 cm is assigned to ν2, the out-of-plane bend. The -1 other fundamental molecular vibration, ν4, occurs at 726 cm ; it is a very weak feature in the absorption spectrum and represents the planar deformation. A shoulder also appears in the absorption spectrum at 1447 cm-1 and is assigned to the -1 first overtone of ν4 (i.e. 2ν4). Finally, a weak feature at 1789 cm is observed and is assigned to a combination band, ν1 + 11 -1 ν4. Gadzhiev and co-workers also measured the absorption spectrum for NaNO3 from 4000-500 cm . They observed -1 combination bands at 2101 and 2440 cm corresponding to ν3 + ν4 and ν1 + ν3, respectively. A doubly-peaked band is -1 also observed at 2762 and 2849 cm and is assigned to the first overtone of ν3 (i.e. 2ν3). All of these assigned bands are used to help interpret the measured reflectance spectra observed in Figures 1 through 3.
The combination bands ν3 + ν4 (band J in Figure 1) and ν1 + ν3 (band I in Figure 1) are observed around 2100 and 2440 -1 cm , respectively. The doubly peaked band (band H in Figure 1), which corresponds to 2ν3, becomes unsaturated for the finer grain sizes and shows two troughs around 2852 and 2765 cm-1. These spectral positions agree well with the measured spectrum by Gadzhiev and co-workers.11 Due to the stronger absorption coefficient for these three bands, the spectral contrast increases as the particle size is reduced. An expanded plot from 2000-600 cm-1 is shown in Figure 2 for all six size fractions where both volume and surface
150 MUSTARD AND HAYS scattering contribute so that both minima (bands C-E) and maxima (bands A-B) are observed in the reflectance spectra.
80 0-45 microns E 45-90 microns 90-180 microns 180-250 microns 60 250-500 microns 500+ microns B D A 40 Reflectance (%) 20
C
0 2000 1800 1600 1400 1200 1000 Wavenumber (cm-1)
Figure 2. Hemispherical IR reflectance spectra from 2000-600 cm-1 for ground and sieved samples of sodium nitrate for six grain sizes: 0-45 μm (black trace), 45-90 μm (red trace),(b) 90-180 μm (green trace), 180-250 μm (blue trace), 250-500 μm (a) (cyan trace), and > 500 μm (magenta trace). See text for explanation of bands A-E.
The strong fundamental molecular vibration, ν3, results in a reststrahlena band, which is the broad upward-going peak Figure 25: (a) Reflectance of an olivinerepresented sample as band as aA in function the IR reflectance of particle spectra shown diameters in Figure 2.a The< 25dip µin m;the reststrahlen repro- band at 1447 cm-1 is -1 duced from Figure 4 of [120]. (b): Reflectanceattributed to 2ν4.of The a reststrahlen sodium featurenitrate has sample its maximum as aaround function 1434 cm ofand particle is shifted to slightly shorter wavelengths than the peak in the absorption spectrum, which is around 1378 cm-1; this shift is typical for features that size; reproduced from Figure 2 of [112].primarily result from surface scattering phenomena since the reflectance depends on both the absorption coefficient as well the index of refraction.1 Reststrahlen features arise when the absorption coefficient is large so that Fresnel reflection is high and most of the incident radiation is reflected from the first surface; thus, a peak is observed in the reflectance spectrum. Photons that do penetrate the surface are absorbed due to the large absorption coefficient so the rays that do 3.2 Extrinsic Factors
3.2.1FIG. 4. Reflectance Particle spectra over the extended Size wavelength range Effects of 0.3 to 25.0 em of the olivine size separates. Note the changes, with particle Proc. of SPIE Vol. 9088 908809-4 size, in the crystal field absorptions (A), restrahlen bands (B), and transparency feature (C). Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx In the case of solid particulate media, there is a large body of literature on the variation of spectral signatures with particle size [9, 110–128] and how the spectra of particulate versus bulk samples of the same substance differ [129–132]. The underlying physics that qualitatively determine these variations was essentially captured by the discussion on stacks of multiple planar slabs connected to Figure 6 in §2. Given the three-dimensional geometry, irregularities in particle shape, and parti- cles being packed densely enough to be within each other’s near-field scattering zone [which alters the effective scattering properties of each particle; e.g., 133], the quantitative details are much more complex here relative to §2. However, qualitatively the strength of scattering at each parti- cle interface relative to the amount of absorption experienced within each particle’s volume still remain the primary factors that generate the observed spectral signature trends with particle size [e.g., see 134, 135, with the caveats that their description of scattering in terms of ”specular” and ”volume” components does not cleanly map to the underlying physical principles of the problem and that their developed theoretical model is not a quantitatively correct first-principles treatment for scattering in particulate media]. Figure 25 provides two examples of typical reflectance spectra variations with particle size. Again, these mirror very closely the trends observed in Figure 6. Figure 25a shows the reflectance of a silicate (olivine) for extremely fine size-separate ranges (< 25 µm particle diameters). For λ . 3 µm, the samples’ overall reflectance increases and the strength of the large absorption fea- ture at λ ≈ 1 µm decreases with decreasing particle diameter, a. The overall reflectance increase is consistent with the increased scattering expected as more particle boundaries per unit sample thickness are encountered with decreasing a. The decreasing spectral contrast is indicative that the combination of a and κ are such that the particles are optically thin across the entire band. For larger particles, this may not be the case and the possibility for feature-strength evolution with a that is not monotonic could arise. The evolution of the λ ≈ 1 µm feature in the pyroxene silicates enstatite and diopside reported in Mancarella et al. [113] shows an increase in feature strength with
20 138 B.H.N. Horgan et al. / Icarus 234 (2014) 132–154
Fig. 5. FigureTwo component 26: mixture Reflectance spectra of OPX–CPX spectra type-B of mixtures two-component for two different intimate endmember sets: mixtures (a and b) hypersthene of the orthopyroxene and endiopside, and (c enstatite and d) enstatite and diopside. Mixtures in (a) and (c) made at 0–45 lm and 10 wt.% intervals; (b) and (d) at 90–180 lm and 20 wt.% intervals. Note that while the hypersthene/endiposide mixture linearly(OPX) transitions and between clinopyroxene the two endmembers, diopside the enstatite/diopside (CPX-B) mixture with does different not. The enstatite lines dominatesshowing the relative spectrum much weight like in increments mixtures of OPX with of olivine or glass (Figs. 4 and 6), in all cases due to the greater absorption strength of the OPX relative to the other endmembers. Narrow 1.4 and 2.2 lm absorption bands present in some spectra10 and are due 20% to minor for alteration. the 0-45 SeeµTablesm and A4 and 90-180 A5 for sampleµm information. sized particles, respectively. The reflectances are scaled and shifted for clarity. Reproduced from Figure 5 of [111]. present in a given spectrum. This is useful because the index will many also give positive values for OLINDEX2 and LCPINDEX. Spec- give adecreasing value greatera thanover zero the evenrange ina low≈ 50–500 spectral contrastµm for or bothtral minerals. indices for This CPX type-A would are indicate indistinguishable that for from olivine, those for the dusty scenes or, in theory, even when the targeted mineral is pres- olivines. As expected based on the shape of the spectrum, pyrrho- ent asif part larger of a particlesmixture. Thus, had the been value included of an index in for the a given sample,tite a non-monotonic also tends to give positive evolution values in for the HCPINDEX 1 µm ( band0.99). spectrumwould is not likely as critical be observed. as the combination For λ of& indices3 µm, that a give reversal inOne the drawback overall of reflectance spectral indices versus is that itparticle-size is difficult to formu- positivebehavior values for begins that spectrum. to appear: as λ increases, the highestlate an reflectance index that could corresponds consistently identify to larger iron-bearinga. This glass, in Ideally, a given ferrous mineral would only produce a positive part due to the variation in glass spectral shapes (Fig. 2). This is valuebehavior, for its associated which spectral was index not exploredbut not the quantitativelyother two. This indemonstrated§2, is consistent in the existing with CRISM expected indices, behavior as most but for not all is generallyλ & a true,. In but this not regime, in every case, closely and the packed spectral particles indices of- withglassesa and give separations positive values smaller for OLINDEX2. than Thisλ present is a potential an prob- ten give positive values for other minerals as well. Fig. 7 shows the lem because even after inspection of the relevant spectra, some of CRISMincreasingly ferrous spectral homogeneous indices of all olivine, medium pyroxene, to the and EM-waves, glass these decreasing glasses could scattering easily be misidentified efficiency. as olivine based on their spectra in our sample set. In some ways, the olivines are the lack of a strong 2 lm band. Glass is a significant component of both best-behavedFigure mineral 25b shows group, as the all ofreflectance the olivines give of apositive series val- of sodiumimpact and nitrate volcanic samples deposits, with so anothera ranging method isfrom clearly< needed ues for45 OLINDEX2µm to > but500 not HCPINDEXµm [112]. nor LCPINDEX Again, the (Fig. overall 7b). How- reflectancethat can more of these uniquely samples identify increasesglass on a planetary for smaller surface. ever, OLINDEX2a is also positive for the majority of the≈ iron-bearing −1Fig. 8 shows the effects of mixtures on CRISM spectral indices. minerals, except in our full in sample the region set, with between the exceptionν of all1300-1500 of the OPX cmMixtures. Over of CPX, this olivine, particle and glass size tend range, to produce the various relatively linear −1 spectra,bands less than exhibited half of theshow glass several spectra, different and two of behaviors. the three Thevariations 1901 in cm the spectralfeature indices; shows however, evidence OPX causes of non- highly non- hematitemonotonic spectra (c1jb129 spectral and contrast cbcc17). So, variations while OLINDEX2 with changingis of- lineara. On trends, the for other several hand, reasons. the 1798 As discussed cm−1 above,feature, OPX is a ten strongest in olivines, it also functions as a general spectral in- stronger absorber than the other minerals, so the LCPINDEX re- dex forwhich ferrous is (and expected some ferric) to be minerals a stronger (e.g. Bishop absorption et al., 2008, bandmains [136], high shows even atincreasing lesser abundances spectral of OPX.contrast Some with of the non- 2013bsmaller). Thus, ana elevatedfor the OLINDEX2 entire particle-size does not signify range, a unique indicatinglinearity the is center also due of to usingthe band the 1.08 remainslm channel optically to detect the detection of olivine (Salvatore et al., 2010a ), even when the other 1 lm band in both≈ the HCPINDEX and− LCPINDEX.1 This channel is indicesthick are not even elevated. at the smallest used. The peak reflectancelocated in so the farν from1300-1500 the center of cm the OPXis a absorption so-called band at Pyroxenesreststrahlen have more feature complicated produced effects by on the the spectral large κ indi--value0.9 ofl them that molecule’s adding any primary phase with vibration a longer-wavelength band. In 1 lm ces. Allother of the words, OPX spectra the absorption give positive valuesin this for region LCPINDEX is so-large and band that (CPX, even olivine,the smallest glass) particles increases the essentially absorption act at this negative values for OLINDEX2 (below the range of Fig. 7c), but channel and the value of the index. This effect can be seen in the manyas of the semi-infinite OPX, particularly media the more and iron-rich only the OPX, first-surface also give po- interfaceOPX–olivine contributes mixtures in Fig. tothe 8e, in scattering. which the HCPINDEX At these increases sitivewavelength values for HCPINDEX ranges, (Fig. the 7a). condition While most that of then CPX type-Bκ assumedas the in § proportion2 does not of necessarily olivine increases, hold. even As though such theno CPX is spectradetailed give positive shape values of the forreflectance HCPINDEX, several peak do in not, this andν-regionpresent could in the depend system. Finally, on both the sensitivitythe n and ofκ thevalues HCPINDEX to there. See Myers et al. [112] for a discussion of the features near 1097 and 1540 cm−1.
3.2.2 Optically Thin Samples in Mixtures
Samples containing optically thin components in proximity to other materials (e.g., small parti- cles of two or more substances in a physical mixture, small particles on substrates, thin films on substrates) can have their spectral signatures modified by the presence of the proximate media. Put another way, the spectral signature of an optically thin sample in many contexts can change
21 336 K.M. Stack, R.E. Milliken / Icarus 250 (2015) 332–356
PLA 5 - 2KRAFTETAL.:EFFECTSOFSILICACOATINGSONTHERMALEMISSIONSPECTRA
3.2. Spectra of Silica-Coated Basalt 1 [10]Insilica-coatedCRBspectra,1120cmÀ and 1 470 cmÀ silica absorptions deepen as coating thickness increases (Figure 2). Elsewhere, the spectral contrast is reduced as coating thickness increases. These effects are similar to thermal emission spectra of rocks coated by clay-rich rock varnish and airfall-deposited dust, which progressively reduce spectral contrast of substrate features and introduce absorption features of the coating as coating thickness increases [Christensen and Harrison,1993; Johnson et al., 2002]. In spectra of CRB with 0.5 to 1.6-mm-thick coatings, a local emissivity maximum occurs 336 336 K.M. Stack, R.E. Milliken / Icarus 250 (2015) 332–356K.M. Stack, R.E. Milliken / Icarus 250 (2015) 332–3561 1000–1100 cmÀ . [11]Thetrendsofincreasingdepthofsilicaabsorptionand 1 decreasing contrast of basalt absorptions (e.g., at 550 cmÀ 1 Figure 1. Thermal emission spectra of silicate glasses and and 1010 cmÀ ) can be used to estimate the extent to which clay minerals used in mineralogical models of ST2 silica spectrally obscures the substrate. Emissivity differ- compared to spectra of opal and synthetic silica. Spectra ences e1010 e1120 and e550 e470 for silica-coated CRB are offset for clarity. each measureÀ decreasing CRBÀ and increasing silica contri- bution to the spectra (Figure 3). By comparing the emissivity differences to the values from the synthetic silica spectrum, Harrison,1993;Ruff et al.,1997].Spectrawereattainedat 1 1 we estimate that a silica coating 7–10 mm thick would 2cmÀ sampling resolution over the range 200–2000 cmÀ spectrally mask a silicate substrate, in good agreement with from 1–2 cm diameter sampling areas. the 10 mm estimate made by Crisp et al. [1990] for natural [7] Opal-A and opal-CT were investigated in conjunction silica coatings. This is thinner than the 50 mmand 50– with Michalski et al. [2003] who describe these samples in 100 mmcoatingthicknessestimatedtospectrallymask more detail. The synthetic silica used in our experiments was substrates with rock varnish or airfall-deposited dust, respec- precipitated onto a spectrally featureless sample holder to a tively [Christensen and Harrison,1993;Johnson et al., thickness >20 mm so that its spectrum could be measured. 2002], although this difference is due, in part, to the discon- [8] Silica-coated basalt samples were prepared in the tinuous nature of rock varnish and airfall dust coatings. laboratory. Sample geometry, coating chemistry and [12]Spectraofsilica-coatedCRBweremodeledusinga mineralogy are variable in natural silica-coated rocks, which linear deconvolution algorithm that applies a linear best-fit make the TIR impacts of silica coatings difficult to con- model of end-member spectra to the spectrum of interest strain. Using synthetic samples, we attained coatings with over a specified wave number range and assigns percent constant chemical and mineralogical characteristics, near- abundance of those spectral end-members [cf. Ramsey and constant thickness, and approximately planar coating-rock interfaces. Polished slabs of Columbia River Basalt (CRB) were coated using a solution of 40 mol% colloidal SiO 336 K.M. Stack, R.E. Milliken / Icarus 250 (2015) 332–3562 (Alfa Aesar #43110) with a reported 0.02 mmcolloidsize. The solution was diluted in distilled water, applied to polished CRB surfaces as a fine mist, and evaporated at 50°C to precipitate silica. Coatings were constructed by repeating this process. Targeted thicknesses were achieved with a set number of iterations derived from calibration runs. Coatings measured in electron backscatter images had thicknesses of 1.0, 1.6, 3.1, and 6.3 mm (±45%). Thinner coatings were estimated to be 0.25 and 0.5 mm thick (±45%) based on the calibration. Thinner coatings may have been somewhat discontinuous on rock surfaces.
3. Results 3.1. Silica Spectra [9]Opalineandsyntheticsilicaallhavesimilarspectral shape (Figure 1). Each spectrum has a broad absorption 1 feature centered at 1120 cmÀ resulting from Si-O-Si stretch- 1 ing. An O-Si-O bending feature is centered at 470 cmÀ . Silica spectral shape and feature positions are similar to the spectrum of SiO2 glass. Silica spectra are generally similar in shape to the spectrum of high-K silica glass and to the clay Figure 2. Thermal emission spectra of CRB, synthetic mineral spectra used by Wyatt and McSween [2002], although silica, and silica-coated CRB. Coating thickness is given on 1 the clay spectra have a doublet 450–540 cmÀ .The the graph in micrometers. Y-axis is emissivity in increments Fig. 2. NIR diffuse reflectance spectra of all mixtures andpositions endmember of(a) absorption componentsfeatures differ among acquired these materials. withof an 0.05. FTIR Spectra spectrometer. are offset for(b) clarity. Each spectrum represents the average of three spectra (each representing 200 scans) acquired at different locations on the surface of each powder mixture or endmember. Figure 27: (a): Intimate mixtures of epsomite and a montmorillonite clay with composition expressed in clay mass fractions; reproduced from Figure 2 of [138]. (b): Emissivity of amorphous silicate thin layers (thickness specified in the plot in µm) on basalt; reproduced from Figure 2 of [139]. 3.2. Analysis of band depths and band minima 3.3. Linear (checkerboard) and nonlinear (intimate) spectral unmixing depending on its surroundings. We saw an example of this for the one-dimensional planar slab in Wavelength positions of true local band minima (maximum To perform nonlinear intimate spectral unmixing, all reflectance Figure 5 where a change in substrate material altered the slab’s R single-interface reflectance. absorption strength) were identified for each reflectance spectrum mixture spectra12 were first converted to SSA using Eq. (2). Backscat- Similar effects are present when media interfaces are in each other’s near-field scattering zone, at the 1.4 lm (OH vibration associated with the clay cation-OH ter was assumed to be negligible (B(g) = 0), a reasonable assump- leading to changes in individual media scattering properties [133, 137]. bond), 1.45 lm (clay and epsomite H2O stretch overtones), tion given the phase angles of the spectral measurements, and it 1.9 and 1.95 lm (clay and epsomite H2O vibrations), and 2.2– was assumed that the fine-grained mixtures were composed of iso- Fig. 2. NIR diffuse reflectance spectra of all mixtures and endmember componentsThe typical acquired reflectance with an FTIR signature spectrometer. phenomenology Each spectrum in represents these optically-thin the average of mixturesthree spectra is for the com- 2.4Fig.l 2.mNIR (clay diffuse cation-OH reflectancebined spectra vibration) reflectance of all mixtures wavelength spectra and endmember to evolve regions components between (Bishop the acquired mixture’stropic with anscatterers individual FTIR spectrometer. (p components’(g) = 1). Each Though spectrum spectra the representsas latter a may the average not be of truethree in spectra the (each representing 200 scans) acquired at different(each locations representing on the 200 surface scans) acquiredof each powder at different mixture locations or endmember. on the surface of each powder mixture or endmember. et al., 1995b). Band minimafunction positions of mixing were fraction. then However, plotted this against evolutionstrictest oftentimes sense, exhibits it is a likely significantly a small non-linear source of uncertainty when com- measured clay mass fractiondependence (Fig. on 3) component to assess mixing changes fraction in band [140–143].paring This results should for not differentbe surprising mixtures given that because all spectra were position as a functionthe of planar clay sample content. case To exhibits analyze an changes exponential in dependenceacquired on with slab an thickness identical when viewingκ =6 0. geometry. Fig- In addition, exact 3.2. Analysis of band depths and bandabsorption3.2. minima Analysis band of band strength depthsure 26in and each provides band mixture3.3. minima an Linear example—for series (checkerboard) as a functionthe case and of ofnonlinear a mixturephase3.3. (intimate) Linear of function the (checkerboard) pyroxene spectral values unmixingminerals for and the nonlinear enstatite clay and and (intimate) sulfate endmembers spectral unmixing used the mixtureFig. 2. compositionNIR diffuse reflectancediopside—of (Fig. spectra 4), of a all spectral the mixtures non-linear and continuum endmember evolution components was and defined acquired spectra with morphology anhere FTIR spectrometer. have changes not Each been spectrum that previously represents can occur the average reported. in so-called of three spectra (each representing 200 scans) acquired at different locations on the surface of each powder mixture or endmember. Wavelength positions of true localfor eachWavelength band reflectance minima positions (maximum spectrumintimate of true overmixtures local theTo of entire bandperform small 1.25–2.6minima particles. nonlinear (maximumlm The intimate wave- depth of spectral the λClayTo≈ unmixing, perform1 and.0 µm epsomite enstatite nonlinear all reflectance endmember (marked intimate as spectralOPX spectral for unmixing, weighting all coefficients reflectance absorption strength) were identifiedlength forabsorption each range reflectance strength) using the spectrum wereorthopyroxene) ENVI identified continuummixture forfeature removaleach spectra in reflectance these routine were figures firstspectrum in is which non-linearconvertedwere inmixture to enstatite SSA modeled using spectra mass Eq. forfraction were(2) each. Backscat- first [111]. mixture converted Additionally, from to SSA reflectance using Eq. (checkerboard(2). Backscat- at the 1.4 lm (OH vibration associateda convex with hull the fit clay is cation-OH defined by straight-lineter was assumed segments to connectingbe negligible (Bmixing(g) = 0), model, a reasonable Eq. (1) assump-) and SSA (intimate mixing model, Eq. (4)) at the 1.43.2. Analysislm (OH of band vibrationthe depths combination and associated band minima of the with enstatite the clay and cation-OH diopside3.3. 1.0 Linearµmter (checkerboard) features, was assumed which and nonlinear are to shiftedbe negligible(intimate) relative spectral (B to(g each unmixing) = 0), a reasonable assump- bond), 1.45 lm (clay and epsomitelocal H maxima.2O stretch After overtones), continuum removaltion given over the the phase entire angles wave- of the spectralspectra usingmeasurements, linear least and squares it inversion with a constraint of bond), 1.45 lm (clayother, and results epsomite in an evolution H2O stretch of the band overtones), position and morphologytion given the in the phase mixtures. angles The of reflectances the spectral measurements, and it 1.9 and 1.95 lm (clay and epsomitelength H2O range, vibrations),Wavelength the band and positions depths 2.2– of true ofwas the local assumed true band local minima that minima (maximum the fine-grained at 1.4, To perform mixturesnon-negativity nonlinear were intimate composed implemented spectral of unmixing,iso- in MATLAB all reflectance using the lsqnonneg func- 1.9 and 1.95 lm (clayin this and figure epsomite are scaled H2O and vibrations), shifted, which and 2.2– obviouslywas hides assumed the details that of the the fine-grained relative reflectance mixtures were composed of iso- absorption strength) were identified for each reflectancep spectrumg mixture spectra were first converted to SSA using Eq. (2). Backscat- 2.4 lm (clay cation-OH vibration)1.45,2.4 wavelengthm 1.9, (clay 1.95, regions cation-OH and 2.2–2.4 (Bishop vibration)lm weretropic wavelength calculated scatterers for regions ( each( ) = mixture1). (Bishop Though thetiontropic latter (www.mathworks.com/help/optim/ug/lsqnonneg.html scatterers may not be(p(g true) = 1). in Thoughthe the latter may not be true). in Lin- the l at the 1.4 lm (OHevolution. vibration associated with the clay cation-OH ter was assumed to be negligible (B(g) = 0), a reasonable assump- et al., 1995b). Band minima positionsusing were the then method plotted of Clark against and Roushstrictest (1984) sense,: it is likely a small sourceear of least uncertainty squares when was performed com- for each mixture using the et al., 1995bbond),). Band1.45 lm minima (clay and positions epsomite were H2O stretch then plotted overtones), againsttion givenstrictest the phase sense, angles it of is the likely spectral a small measurements, source andof uncertainty it when com- measured clay mass fraction (Fig. 3) to assess changes inFigure band 27a [139]paring provides results one for example different of a sequencemixturesmeasured of because intimate mixture all mixture spectra spectrum spectra were on and an absolutean input matrix containing the measured1.9 clay and mass1.95 l fractionm (clay and (Fig. epsomite 3) to H2 assessO vibrations), changes and 2.2– in bandwas assumedparing that the results fine-grained for different mixtures were mixtures composed because of iso- all spectra were position as a function of clay content.Db 1 To2.4 analyzeRbl=mRc (clay changes cation-OHreflectance in vibration) scale.acquired wavelength The mixtures with regions an in identical this (Bishop case are13 viewingtropic of a scatterers montmorillonitepure geometry. clay (p(g) and = 1).In epsomite Thoughclay addition, and the epsomite latterendmember exact may (a not hydrated be spectra true in the of that series and lines position¼ Àð as aÞð function of clay content. To analyze changes inÞ acquired with an identical viewing geometry. In addition, exact absorption band strength in each mixture serieset al., as 1995b a function). Bandsulfate). minima of Of positionsphase particular were functionnote then plotted in values this against example for thestrictest is clay the andof fact sense, positive sulfate that it isthe likely endmembersand reflectances a small negative source of of used slope. the uncertainty intermediate The when additional com- sloped lines were absorptionmeasured band claystrength mass fraction in each (Fig. mixture 3) to assess series changes as a in function band paring of resultsphase for function different values mixtures for because the clay all spectra and sulfate were endmembers used the mixture composition (Fig. 4), a spectralwhere continuumD is band was depth, definedmixturesR is the are nothere reflectance bounded have not definedby thebeen pure-material at previously the band reflectances. reported.included This to is allow by no the means model a special to account case—at for phase behavior and the mixturebposition composition as a function (Fig.b of 4 clay), a spectralcontent. To continuum analyze changes was definedin acquiredhere with havean identical not been viewing previously geometry. In reported. addition, exact for each reflectance spectrum over the entire 1.25–2.6 lmleast wave- several of theClay mixtures and epsomite examined endmember in [111] exhibit spectral similar weighting behavior coefficients in absolute reflectances. center,for each andabsorption reflectanceRc is the band spectrum reflectance strength in over each of the mixturethe defined entire series 1.25–2.6 ascontinuum a functionlm of at wave- thephase functionwavelength-dependentClay values and for epsomite the clay and endmember scattering sulfate endmembers effects spectral used not weighting accounted coefficients for by length range using the ENVI continuum removal routine in which were modeled for each mixture from reflectance (checkerboard bandlength center. rangethe mixture using composition theWe ENVI are (Fig. continuum not, 4), however, a spectral removal continuum in a position routine was defined to incomment whichhere authoritatively havethewere not mineral been modeled previously on endmembers the for underlying reported. each (mixtureCombe physical et from causesal., 2008 reflectance). The inversions (checkerboard were a convex hull fit is defined by straight-line segmentsfor each reflectance connecting spectrum overmixing the entire model, 1.25–2.6 Eq.lm(1) wave-) and SSAClay (intimate and epsomite mixing endmember model, spectral Eq. (4) weighting) coefficients a convex hull fit is definedof this by behavior. straight-line The models segments typically connecting used to interpretmixing particulate model, mixture Eq. (1)) spectra and SSA [7, (intimate 144] are mixing model, Eq. (4)) local maxima. After continuum removal overlength the range entire using wave- the ENVI continuumspectra removal using routine linear in leastwhich squareswere modeled inversion for each with mixture a constraint from reflectance of (checkerboard local maxima.a convex After hull fit continuumphenomenological is defined by straight-line removal in nature over segments and the connecting do entire not predict wave-mixing such unboundedmodel,spectra Eq. using(1) mixture) and linear SSA spectra, (intimate least whilesquares mixing appropriate model, inversion Eq. (4)) with a constraint of length range, the band depths of the true local minima at 1.4, non-negativity implemented in MATLAB using the lsqnonneg func- length range,local maxima. the band After depths continuum of removal the true over local the entire minima wave- at 1.4,spectra usingnon-negativity linear least squares implemented inversion with in MATLAB a constraint using of the lsqnonneg func- 1.45, 1.9, 1.95, and 2.2–2.4 lm were calculatedlength for range, each the mixture band depths oftion the ( truewww.mathworks.com/help/optim/ug/lsqnonneg.html local minima at 1.4, non-negativity implemented in MATLAB). using Lin- the lsqnonneg func- 1.45, 1.9, 1.95, and 2.2–2.4 lm were calculated for each mixture22 tion (www.mathworks.com/help/optim/ug/lsqnonneg.html). Lin- using the method of Clark and Roush (1984):1.45, 1.9, 1.95, and 2.2–2.4 lm wereear calculated least squares for each was mixture performedtion (www.mathworks.com/help/optim/ug/lsqnonneg.html for each mixture using the ). Lin- using theusing method the method of Clark of Clark and and Roush Roush (1984) (1984): : ear leastear squares least was squares performed was for performed each mixture for using each the mixture using the measured mixture spectrum and an input matrix containing the measuredmeasured mixture spectrum mixture and spectrum an input matrix and containing an input the matrix containing the Db 1 Rb=Rc Db 1 Rb=Rc 13 pure clay and epsomite13 endmemberpure clay spectra and epsomite of that endmember series and spectra lines of that series and lines ¼ Àð ÞðDb 1 R¼b=RÀðc ÞðÞ Þ 13 pure clay and epsomite endmember spectra of that series and lines ¼ Àð Þðof positive and negative slope.ofÞ positive The additional and negative sloped slope. The lines additional were sloped lines were of positive and negative slope. The additional sloped lines were where Db is band depth, Rb is the reflectance defined at the band included to allow the model to account for phase behavior and where Db is band depth, Rb is the reflectance defined at the band included to allow the model to account for phase behavior and where Dcenter,is band and R depth,c is theR reflectanceis the ofreflectance the defined defined continuum at at the the bandwavelength-dependentincluded to scattering allow the effects model not to accounted account for for by phase behavior and center, and R is the reflectance of the definedb continuum at theb wavelength-dependent scattering effects not accounted for by c center, andbandR center.is the reflectance of the defined continuum at thethe mineralwavelength-dependent endmembers (Combe et al., 2008 scattering). The inversions effects were not accounted for by band center. c the mineral endmembers (Combe et al., 2008). The inversions were band center. the mineral endmembers (Combe et al., 2008). The inversions were first-principles EM-scattering methods [e.g. 133, 145] have not been applied to this problem in sufficient detail to provide a clear physical picture of how unbounded mixture spectra can arise. Figure 27b provides an example of a thin film of amorphous silicate on a basalt substrate showing emissivity as a function of silicate layer thickness [138]. These authors again find the mixture spectra to depend on the component abundances (in this case, measured by layer thickness) in a non-linear manner. It is worth noting that thin film coatings are a spontaneously generated context in which coherent interference effects may likely impact spectral signatures. Awareness of this possibility is necessary for proper interpretation of spectra in cases where coherence effects could appear [146].
3.2.3 Other Sample Morphology Effects
Besides particle size in the case of a particulate medium, a sample’s morphological properties can, more generally, influence its spectral signature. A readily available example is sintered polyte- trafluoroethylene (PTFE) that is used as a reflectance standard that provides an R ≈ 0.99 across the visible and near-infrared (VNIR). PTFE however is a non-absorptive material with an n = 1.35 across this range of the spectrum; i.e., a homogeneous thin slab PTFE would be essentially trans- parent. The key here is that sintered PTFE is not a homogeneous material, but has significant porous microstructure on ∼ 1-10 µm spatial scale [e.g., 147]. This produces significant scattering for most λ in the VNIR that combined with a sufficiently thick PTFE sample results in a nearly spectrally flat, R ≈ 1 reflectance. Moroz et al. [121] provides another example of internal structural impacts. They synthesized palagocite glasses through several pathways, one of which introduced significant porosity into the resulting samples. The high-porosity samples tended to have higher reflectances and show lower spectral contrast than the other glasses. The impact of particle-shape on individual particle scattering properties has a large body of associ- ated theoretical literature [e.g., 148–163]. However most of this work is focused on the impact of particle shape on the geometry of the scattered fields off a single-particle. Making the connection between these properties and how they impact a sample’s spectral characteristics, even in the case of a single particle, remains an unfinished task. A few notable exceptions here include Kleiber et al. [164] who provide one example of how particle shape variations impact spectra, showing that relatively significant shifts in extinction peak locations can occur with variations in aspect ra- tios of spheroidal particles. Kiomarsipour et al. [165] describe the effect particle shapes have on the reflectance properties of zinc oxide powder based pigments. In particular, the particle-shape influences overall reflectance levels, some aspects of the spectra’s general shape, and the strength of spectral features. In addition, Mishchenko [166] provides an example of theoretical effort to connect individual particle-shape effects (amongst other relevant particle properties) to the overall radiative transfer properties of a bulk particulate layer. For bulk surface interfaces, surface roughness can influence spectral signatures. Kirkland et al. [167] compared the emissivity of limestone samples with smooth versus roughened surfaces. The roughened surface reduces the emissivity contrast in the limestone absorption bands and introduces an additional kink in the two bands present. Osterloo et al. [168] conducted a similar study but on a sample of 12 different natural rock surfaces and considering a range of surface roughness. Again, a trend of decreasing spectral contrast with increasing surface roughness was observed. Other studies have noticed the same trends in the case of carbonates [169] and chert [170].
23 Figure'2' 3.2.4 Illumination and Viewing Angles: Sample BRDF
a)' b)' As demonstrated in §2, the quantitative details of a sample’s spectrum vary with changing illumination and viewing angle. In the idealized case presented there, the reflection is exclusively specular—that is, the reflected light is directed at an angle from the surface normal equal to the angle of incidence. At angles other than this specular angle, no reflected signal would be observed. In less idealized situations, both surface and interior sample inhomogeneities lead to so-called diffuse scattering in non-specular directions. The distribution of scattered light intensity as a function of incident and viewing angles is described by Figure 28: The BRDF of a medium’s bidirectional reflectance distribution function (BRDF). For a roughened aluminum real surfaces, the BRDF can be very complex (e.g., Figure 28). surface. Reproduced Because of this complexity, direct measurement is the preferred method from [171]. of capturing a medium’s BRDF. However, this isn’t always feasible, and more general situations need to be explored and various first-principles, descriptive, or empirical BRDF models are often employed [172]. Fundamentally, the BRDF captures light-matter interactions which strongly depend on the size of in-medium inhomogeneities relative to λ. As such, BRDF models are typically valid only over specific λ-ranges. Of such models, there are several that are particularly relevant in the IR spectral region, both descriptive [173–175] and theoretical [176–181]. Of media morphological properties, surface roughness plays an important role in setting the BRDF [e.g., 182, 183] and is a primary parameter in several of the theoretical models [e.g., 174, 178, 179]. In the near-IR, several additional BRDF models developed for particulate media are widely employed [7, 184]. Additionally, the Beard-Maxwell [178] and Ashikhmin [174] models are understood to provide reasonable representations of a painted surface BRDF (e.g., painted automobile surfaces). Both the specular and diffuse reflectance components should vary with λ given the considerations in §2 and those given here. However, there is not a large body of literature explicitly documenting variations in BRDF with λ, which would be exhibited most directly by a medium’s spectral shape and/or contrast being illumination and/or viewing geometry dependent. Suter et al. [185] provide examples of such angle-variant spectra in the case of explosive residues coating a surface. BRDF λ-dependence has also been documented to a lesser-or-greater degree in the case of VNIR mea- surements of grass-covered surfaces [186], asphalts and concretes [187], various sands [188], and snow [189]. In the IR, several studies have reported λ-dependent BRDF effects in the emissivity of quartz, both in particulate and polished slab geometries [129, 190]. In both cases, the quartz ab- sorption feature depth increased with increasing look angle (that is opposite the trend in decreasing feature depth seen in reflectance of planar slabs in §2).
24 4 Spectral Signatures of Example Explosive and Chemi- cal Warfare Agent Related Compounds
In this section, we highlight information in the literature concerning the spectral signatures of compounds that are either used as, or are related to, explosive materials and chemical warfare agents. The detection and identification of such compounds at trace abundance is of obvious interest from a public safety/security perspective.
Ethylene Glycol Dinitrate
Ethylene glycol dinitrate (EGDN) has similar properties to nitroglycerin and has been used in the manufacturing and testing of explosives including dynamite and plastic explosives such as Semtex. Recent work by Macleod et al. [191] measured the transmission spectra of EGDN in vapor phase. Their mid-IR measure- ment is shown in Figure 29 and compared to the condensedFig. phase 4. (a) (in Gravimetric this case, calibration liquid-phase) of a pure EGDN permeation source. (b) Transmission measurement takenspectra used from for across-section database calculation, of explo- and Figurecompared 29: with Transmission condensed-phase spectra EGDN. of EGDN in vapor sive materials maintained by the University of and condensed phase. Reproduced from [191]. Rhode4. IslandStandoff (http://expdb.chm.uri.edu). measurements and results It is readily4.1 apparent Narrow fromband absorbers Figure 29 that there are significant differences between spectral band posi- tions andIn a shapesprevious between work, we the focused condense on standoff and vapor detection phase formsof narrow of EGDN. band absorbers using a DFB- QCL as the spectroscopic source [3]. ACLaS standoff detection of water vapor, methane, hydrogen peroxide, and nitrous oxide was demonstrated. For comparison, the widely tunable PentaerythritolEC-QCL-based Tetranitrate ACLaS was first tested on narrow band absorbers such as nitrous oxide and, inevitably, water vapor. To do so, the EC-QCL was wavelength scanned over its entire range Pentaerythritolin 60 s, and tetranitrate 3000 spectral (PETN) pointsis per a powerfulscan were explosiverecorded. material and is similar in structure to nitroglycerin.Firstly, In a [192]spectrum, the variabilityshown in Fig. in the5(a), spectral without signatureany controlled and detectionchemical in limits the line of PETNof sight was was recorded. The black dots in the upper panel are the experimental points. The narrow studied as a function of angular dependence between source-target and target-detector, substrate absorption features observed were found to be solely due to atmospheric water vapor. The type, andexperimental loading surfacedata was concentration. fitted using the The OEM spectra algorithm were recorded(red curve) at with a stand-off a priori distance information of 1 m − over thefor range the differentν =700–4000 state vector cm 1parameters.. Two substrates For all were the considered:fittings in this anodized work, a and 50% polished relative alu- minum.uncertainty The differences was chosen between for the the a twopriori substrates mixing ratio influenced values, and the reflectance100% for the spectra three baseline in multiple ways.parameters Figures 30a describing and 30b the show laser the power PETN modulation. reflectance The at returned a normal H view-angle2O mixing ratio vs. is surface 4952 ± con- centration55 ppm. on theThe polished fit residual and shown anodized in the substrates, lower panel respectively. is not fully Stark random differences but rather can exhibits be observed a −1 betweenspurious the reflectance standing wave spectra with of a PETN free spectral on the range two substrates. of 1.7 cm For. This example, was consistently in the case observed of the 200 and−2 most likely originates from residual standing waves within the QCL gain chip or within µg cmlensessamples inside (Figurethe external 30a solid,cavity. Figure Further 30b nonrandom outlined) contributions the spectral peaksto the areresidual almost stem completely from invertedmodel between errors thein the two vicinity substrates of water (additionally vapor lines. providing Indeed, alaser particularly chirp rate dramatic variations example internal ofto the importancethe frequency of the surroundingsweep were observed environment and are in thenot caseaccounted of optically for in the thin model. target The samples). transmitted Addi- tionally,power the modulation reflectance inherent spectra to vary the frequency wildly as scan a function was accounted of PETN for concentration by a quadratic inbaseline the case in of the anodizedmost cases. substrate, whereas on the polished surface there is simply a shift in magnitude in the reflectivityA gas as acell, function filled with of concentration. 1 ± 1 Torr of pure The N authors2O and made also exploredup to atmospheric the limit pressure of detection (757 ± as a 1 Torr) using laboratory air, was subsequently introduced into the line of sight. The functioncorresponding of source-to-target ACLaS spectrum and target-to-detector is shown in Fig. angles. 5(b). It Again,covers thealmost trends the full between R branch the polishedand a small portion of the P branch of N2O. Retrieved mixing ratios from the processing algorithm were 2081 ± 12 ppm for N2O and 8005 ± 116 ppm for water. The detection sensitivity -1/2 normalized to the plume length (0.19 m) and25 to 1 s measurement time is 17.8 ppm.m.Hz for N2O. Estimating the noise of the ACLaS signal as the standard deviation of the residual, the experimental spectrum from Fig. 5(b) exhibits an SNR of ~40. This is considerably less than when the EC-QCL is operated at a fixed frequency (SNR ~300). Clearly, the laser frequency scan produces a large amount of excess noise in the laser source which is detrimental to the detection sensitivity. By comparison, using a DFB-QCL and current tuning, the SNR over a spectrum of N2O was ~380. This degradation propagates down to the one sigma error in
#228991 - $15.00 USD Received 4 Dec 2014; revised 7 Jan 2015; accepted 10 Jan 2015; published 15 Jan 2015 (C) 2015 OSA 26 Jan 2015 | Vol. 23, No. 2 | DOI:10.1364/OE.23.000912 | OPTICS EXPRESS 920
deposition of 10 μg/cm2 showed these features. This made possible to generate of chemometrics models to obtain limit of detection (LOD) values at the different surface studied.
°Smooth Al
I`i A, -A noisized Al
2 deposition of 10 μg/cm showed these features. This made possible to generate of chemometrics models to obtain limit ,--'-''-`---..,._. of detection (LOD) values at the different surface studied. _I-A- 300 900 1000 1100 12(10 1300 1400 Wavenumber / cm-'
2 Figure 2. MIR spectra of PETN deposited on the differenA. Banast Al et al.surfaces / Vibrational at Spectroscopy 200 μg/cm 51 (2009) at 168–176 zero degree relative to normal surfaces.175
°Smooth Al
I`i A, -A noisized Al -200 pg cm.2 '''----,,, o ,--'-''-`---..,._. 100 pg cn.2 á _I-A- ---'~`'~^ °a 0 0/ :m7 300 900 1000 1100 12(10 1300 1400 number / cm-' Wave ° 00 900 1000 1100 120 0 1300 1400 2 90 Figure 2. MIR spectra of PETN deposited on the different Al surfaces at 200 μg/cm at zero degree relative to normal surfaces. Wavenum ber / c - -Optimize(i 80 Without optimization (b) -200 pg/cm2 70 --r -2 Regions > Optim ized -100 Nglcm2 -r 2 Regions > without optimization--50 Nglcm2 60 10 Nglcm2 7-11, MI `.....s
I:: 0 O J 30 -200 pg cm.2 '''----,,, o 100 pg cn.2 0 0/ á ---'~`'~^ °a 20 A A :m7 ...... 10..._.-----`-`---_
° 00 900 1000 1100 120 0 1300 00 900 1000 1100 120 0 1300 1400 1400 5 10 15 20 25 30 40 Wave number I cm-1 Wavenum ber / c Degree
Figure 3. MIR spectra of PETN deposited on the different Al substrate with 10, 50, 100 and 200 μg/cm2 at zero degree relative to Figure 4. LOD for PETN on polished aluminum from zero to 45 (b)degree relatiive to normal surface. (b) -200(a) pg/cm2 normal; (a) Polished aluminum surface; (b) spectra on anodized Al substrate. Fig. 6. FTIR spectra of material taken from plastic ‘‘foam’’ and pure TNT. Plastic ‘‘foam’’ as shown in the inset, was used as a sample catcher during a high-strength explosion -100 Nglcm2 120 90 --50 Nglcm2 with TNT. - -Optirnized - -Optimize(i 10 Nglcm2 80 Nith out optimization Without optimization `.....s 100 -y -2 Re,gions Optimized 70 --r -2 Regions > Optim ized Table 4 411- satisfactorily measured with the Globar source. However, when Comparisons of hit quality results for the spectra of residues collected after gions without -r 2 Regions > without optimization the samples are very small or dilute, then it becomes necessary to 60 80 . Proc. of SPIE Vol. 8734/ 87340R-4 nization 7-11, controlled explosions with the reference spectra of pure explosive materials./ MI / use synchrotron radiation (SR) as an infrared source. The super- Downloaded From: http://proceedings.spiedigitallibrary.org/"E on 08/11/2015 Terms of Use:/ http://spiedigitallibrary.org/ss/TermsOfUse.aspxN. Name off..i the sample C-4 PETN/ TNT A A 0) 60 . iority of synchrotron radiation infrared as compared to the Globar I:: Z / 0 W in terms of the flux advantage in the far infrared and the brilliance O ..._.-----`-`---_ Aluminum0 plate from C-4 blast 0.0785 1.2894 1.2511 O J 30 Plastic cover-I from40 . PETN blast 1.2603 0.0912 1.4905 advantage over the whole spectrum is well known [35]. - - 00 900 1000 1100 120 0 1300 1400 Plastic foam from TNT blast 1.1792 1.5093 0.4497 -- - - - 20 As a demonstration,- Fig. 7 presents an example of an ...... Wave number I cm-1 , 20 I A experiment carried out on a very dilute RDX sample in transmis- 10 Figure 3. MIR spectra of PETN deposited on the different Al substrate with 10, 50, 100 and 200 μg/cm2 at zero degree relative to sion mode by means of the infrared microscope with slits set to normal; (a) Polished aluminum surface; (b) spectra on anodized Al substrate. I 5 10 15 20 25 30 40 were revealed0 with infrared technique endorsing the viability of 7 mm 5 mm. It can be seen that only the use of SR guarantees the o 5 10 15 Â 20 Degree the methodology presented. Degree collection of FTIR spectra with well resolved peaks while spectra
It is worth saying that in the case of the present study of post- collected using the Globar source have very low SNR which leads to Figure 4. LOD for PETN on polished aluminum from zero to 45 (c)degree relatiive to normal surface.Figure 5. LOD for PETN on anodized aluminum from zero to 25 degree relatiive to normal surface. blast residues of explosives, most of the samples(d) could be the loss of all information about peaks belonging to analyzed 120 - -Optirnized Proc. of SPIE Vol. 8734 87340R-4 4. CONCLUSIONS AND FUTURE WORRK Figure 30: Mid-IR reflectance spectraNith ofoutPETN optimization on polished (a) and anodized (b) aluminum substrates. 100 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/11/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx-y -2 Re,gionsA Optimized standoff technique using an FTIR spectrometer has been demonstrated in experiments designed to obtain spectral Limit of detection (LOD) as a function411- ofinformation incident of solid angle PETN forsamples polished deposited on (c)polished and aluminu anodizedm and anodiz (d)eed aluminum aluminum surfaces. High quality gionsmeasuremen without ts were achieved by using a highly sensitive photoconductive cryo-cooled MCT detector. Standoff detection substrates.80 . Reproduced from/ [192]. nization / / "E / N. f..i / 0) 60 . Z / W (Figure0 30c) and anodized (Figure 30d) substrates show a marked difference (which the authors O Proc. of SPIE Vol. 8734 87340R-7 -I 40 . were not able to completely understand or-- - - explain). - - - Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/11/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx , - 20 I A
I Cyclotrimethylene0 Trinitramine o 5 10 15 20 Degree
Figure 5. LOD for PETN on anodized aluminum from zero to 25 degree relatiive to normal surface. Cyclotrimethylene trinitramine (RDX) serves as a base for a number of military explosives including Semtex and 4. CONCLUSIONS AND FUTURE WORRK mixtures of RDX and TNT (e.g., Cyclotol, HBX, H-6, A standoff technique using an FTIR spectrometer has been demonstrated in experiments designed to obtain spectral information ofetc.). solid PET FigureN samples de 31posited shows on polished a reference aluminum and anodiz absorbanceeed aluminum surfaces. spectrum High quality measurements were achieved by using a highly sensitive photoconductive cryo-cooled MCT detector. Standoff detection of RDX; note that as pointed out in [194], the features −1 between ν ≈ 1250—1700 cm lie in strong H2O vapor absorption bands and will not be readily seen in stand- Proc. of SPIE Vol. 8734 87340R-7 off detection scenarios. Liu et al. [195] exploredFig. 7. theFTIR spectra re- of very dilute sample of RDX in KBr pellet measured by means of Globar (red line), and SR source (green line), in transmission mode with usage of Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/11/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx microscope: slits were set to 7Figuremm 5 mm. Dark blue 31: line presents Absorbance FTIR spectrum for RDX (reference of spectrum). RDX. (For interpretation Repro- of the references to color in this figure flectance spectra of surface adsorbed RDX on stainless  legend, the reader is referred toduced the web version from of the article.). [193]. steel. Figures 32a and 32b show optical images and re- flectance spectra, respectively, of freshly deposited RDX. While Figure 32 shows that there is variability in the intensity of the reflectance spectra measured from different spots (due to inhomogeneity of the deposition), the spectral peaks are all aligned.
26
452 X. Liu et al. / Sensors and Actuators B 191 (2014) 450–456
(e)$
Figure 32: FTIR measurements of RDX - Figure 33: Reflectance spectra of RDX at 0 (a), (a) Optical microscopy images of fresh RDX 5 (b), and 40 (c) along with the absorption spec- patches by droplet evaporation, Red squares trum (d) over the same spectral band, (e) an opti- are 50 x 50 microns, (b) FTIR reflectance cal microscope image of the RDX region demon-
spectra of fresh patches, (c) Optical mi- strating the surface texture of the sample on a car
Fig. 2. FTIR measurementscroscopyand ab initio calculations imagesof the mid-IR spectra of 1-dayof RDX. (a) Optical agedmicroscope images RDXof fresh RDX patches,patches by droplet evaporation. Red squaresdoor. Reproduced from [185].
are the 50 m by 50 m areas for FTIR microscope measurements in reflection mode. (b) FTIR reflectance spectra of the fresh RDX patches shown in (a) and the simulated
spectra of -phase AAA conformation of RDX. (c) Optical microscope images of 1 day aged RDX patches with further crystallization. Red squares are the 50 m by 50 m
areas for FTIR microscope(d)measurements FTIRin reflection reflectancemode. (d) FTIR reflectance spectra spectraof 1 day aged RDX ofpatches 1-dayshown in (c) and the agedsimulated spectra of twist AA’E
conformation of RDX. (e) Conformers of RDX. The global minimum of RDX molecule is related to the stable ␣-phase RDX solid, which takes chair AAE conformation for the
heterocycle ring and two of the nitro groups take axial direction (A) while the other one takes equatorial direction (E). The RDX molecules in the metastable -phase solid
resemble its vaporpatches.and liquid phase structure. ReproducedThe IR spectra of the fresh RDX patches fromon a stainless [195].steel surface shown in (b) can be simulated by this -phase chair AAA
conformer. The aged RDX patches can be simulated by the twist AA’E conformer which is 0.2 kcal/mol less stable than ␣-phase chair AAA conformer, indicating the slow
conformation conversion on the surface.(For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
at 100 kHz. The analog composite waveform was digitized by a to obtain spectra from various locations within the explosive patch.
7 1
12-bit data acquisition card which operated at 10 samples per All spectra were recorded with a spectral resolution of 2 cm− and
second sampling rate (National Instrument PCI-6115), collecting the results of 100 scans were averaged.
100 dataThispoints for each howeverlaser pulse cycle. In a changestypical experiment, drasticallyThe geometries and vibrational forfrequencies the RDXof the RDX, TNT, spectraand that are a day old (Fig. 32c and 32d) with
7
the external cavity of a QCL is scanned within 1.5 s and 1.5 10 PETN molecules were calculated using the hybrid density func-
×
data points were collected during the entire scan. Fast Fourier tional theory (B3LYP) with the standard basis set of 6-311+G**
transformtwowas then ofperformed thefor each spots50,000-point exhibitingsection of [24,25]. It has nonebeen justified ofthat the density spectralfunctional theory (DFT) features visible in the fresh samples, which the
the raw data to extract the intensity of the 100 kHz component methods can provide reliable results for mid-size organic molecules
in order authorsto produce 300 points attributeas a continuous scan tospectrum a molecular[26,27]. The harmonic conformationalfrequency analysis was performed in changeorder in the crystal structure based on existing ab
showing the intensity of the laser pulses as a function of the laser to identify the stationary points as local minima. The calculated
wave number. harmonic frequencies were also scaled by 0.99 for a better com-
To confirminitiothe resultscalculationsfrom the QCL standoff detection ofand RDXparison equilibrium with the experimental spectra. molecularThe IR absorbance spectra geometry energetics.
provide benchmark spectra for the surface adsorbed explosives, were simulated by assigning a Lorentzian line shape with a half-
1
the reflectance spectra of the explosive residues on the stainless width at half-height of 5 cm− to the calculated dipole strength. All
steel surface were recorded using a Thermo Nicolet Continum the calculations were carried out using the Gaussian 09 program
FTIR microscopeSutersystem. etA 50 al.m by 50 [185]m IR beam spot exploredwas used package [28] the. angular dependence of the spectral signature of RDX at standoff distance of 2 meters using an external cavity quantum cascade laser. For these experiments the samples were sprayed onto a car door with a standard automotive finish of a white paint with clear coat. The reflectance data for RDX at a concentration of 81 µg cm−2 is shown in Fig. 33 for angles of 0, 5, and 40 degrees. The specular reflection spectrum (Fig. 33a) differs significantly from the two diffuse reflectance spectra, with the diffuse reflectance spectra resembling most closely the laboratory absorbance spectra. The specular reflectance, on the other hand, bears little resemblance to the laboratory measurements.
Thiodiglycol
Thiodiglycol (TDG) is a solvent used in a variety of industrial applications, but can also be used in the manufacture of chemical weapons (mustard gas). Because it can be obtained in small quantities, it is commonly used as a chemical warfare agent simulant. Reid et al. [196] measured the mid- infrared reflectance spectra of TDG using a broadband femtosecond optical parametric oscillator as the illumination source. They measured reflectance spectra for TDG deposited on concrete (Figure 34a) and black anodized aluminum (Figure 34b). Figure 34 clearly demonstrates not only a shift in the peak of the spectral band position, but also a change in shape of the spectral features between the two measurements. The dual peak is present in the reference spectrum and TDG on concrete but is clearly absent for TDG on the black anodized aluminum surface. It is important to note that the authors attribute the differences in the reference and measured spectra to a normalization error (not, e.g., to substraten ˜ dfferences).
27
3.4 Standoff detection of TDG liquid drops We then applied a small drop of thiodiglycol (TDG), a chemical warfare agent (CWA) simulant, to a concrete surface and a black anodized aluminum plate. The reflectance spectra measured at a stand-off distance of 2 m, are shown for concrete in Fig. 5 and for aluminum in Fig. 6, together with a reference TDG reflectance spectrum [21] (dashed line). The data show that, for both concrete and aluminum, the absorption features of TDG can be detected. The small discrepancies between the measured and reference spectral data arise from imperfect normalization of the scattered idler spectrum with respect to the incident spectrum.
3.4 Standoff detection of TDG liquid drops We then applied a small drop of thiodiglycol (TDG), a chemical warfare agent (CWA) simulant, to a concrete surface and a black anodized aluminum plate. The reflectance spectra measured at a stand-off distance of .52 m, are shown for concrete in Fig. 5 and for aluminum in Fig. 6, together with a reference TDG reflectance spectrum2700 [21] (dashed2800 line).2900 3000 3100 3200 The data show that, for both concrete and aluminum, the absorption features of TDG can be detected. TheWavenumber small (cm-1) discrepancies between the measured and reference spectral data ariseFig. from 5 Reflectance imperfect spectrum normali ofzation a TDG of drop the (inset)scattered on concrete, idler measured at a stand-off distance of 2 m (solid line) and spectrum with respect to the incident spectrum. comparison with a TDG reference spectrum (dashed line). The experimental spectral resolution was 8 cm-1.
0.0
/
.5 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2700 2800 2900 3000 3100 3200 2700 2800 2900 3000 3100 3200 Wavenumber (cm-1) Wavenumber (cm'')
Fig. 5 Reflectance spectrum of a TDG drop (inset) on concrete, measuredFig. at 6 a Reflectance stand-off distance spectrum of of2 ma TDG(solid drop line) (inset) and on a black anodized aluminum surface, measured at a stand-off distance comparison with a TDG reference spectrum (dashed line). (a)The experimentalof 2 m (solidspectral line) resolution and comparison was 8 cm with-1. a TDG reference spectrum(b) (dashed line). The experimental spectral resolution was 8 cm-1.
Figure 34: Reflectance spectra of TDG measured on concrete (a) and black anodized aluminum (b) at a standoff0.0 distance of 2 m (blue solid line) and a reference spectrum (red dashed line). Reproduced from [196].
Tetryl Proc. of SPIE Vol. 9073 907302-5 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/11/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx 2,4,6-trinitrophenylmethylnitramine/ (tetryl) is an explosive compound used primarily now for det-
onators and4 boosters.1 1 1 1 1 1 1 The1 1 1 1 absorption1 1 1 1 1 1 1 1 1 spectra1 1 1 1 of tetryl across the IR is shown in Figure 35 [194]. 2700 2800 2900 3000 3100 3200 As with RDX, the mostWavenumber prominant (cm'') spectral features occur in the λ ≈ 6–8µm (ν ≈ 1250–1670 −1 Fig. 6 Reflectance spectrumcm of) a range TDG drop where (inset) on H a2 blackO absorption anodized aluminum is strong. surface, measured As such, at a stand-off stand-off distance detection of tetryl may also be of 2 m (solid line) and comparison with a TDG reference spectrum (dashed line). The experimental spectral resolution was 8 cm-1. challenging due to significant atmospheric absorption [194]. Suter et al. [185] explored the angular dependence of tetryl’s reflectance spectral signature. Similar to their results for RDX, the specular reflectance component (Figure 36a) does not contain strong spectral features whereas the diffuse reflectance component over a large angular range (shown in Figure 36b and 36c) mimics the main absorption bands seen in the laboratory reference spectrum (Figure 36d).
Proc. of SPIE Vol. 9073 907302-5 Downloaded From: http://proceedings.spiedigitallibrary.org/Trinitrotoluene on 08/11/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
Trinitrotoluene (TNT) is a commonly used explosive material. TNT reflectance spectra were mea- sured by Suter et al. [185] using the same methodology as discussed above for RDX (Figure 33) and tetryl (Figure 36). While TNTs specular reflectance component (Figure 37a) doesn’t exhibit the expected spectral features (similar to the RDX and tetryl results), the TNT diffuse spectral component has a different dependence due to sample morphology effects. Figure 37e shows that the TNT surface coverage is very homogeneous and smooth as compared to the RDX and tetryl residue morphologies (Figures 33e and 36e), resulting in a much smaller diffuse reflectance com- ponent which limits the SNR at larger angles. Fuchs et al. [197] considered the reflectance spectra of TNT deposited on different substrates. Their results further demonstrate the impact of substrate properties on optically-thin target sample signatures, as already seen in the cases of TDG and PETN discussed above. In the Fuchs et al. [197] results, the substrate’s influence on the TNT reflectance signature is particularly dramatic as seen in Figure 38, which shows the reflectance spectra of TNT on aluminum and car paint. There is a clear inversion in the spectra between the two cases due to the relative absorbance of the two substrates compared to the TNT sample.
28
contained in a human fingerprint,6 our approach falls somewhere between trace and bulk detection, based upon sensitivity, but may find use in applications that screen for evidence of explosives handling. This spectroscopic imaging approach requires no special sample preparation, contact with the sample surface, or a cooperative target. It does not depend on the vapor pressure of the explosive and is capable of modest stand-off distances. There is a trade-off between sensitivity and stand-off distance that depends on the quantity of residue present, laser illumination power, magnification and resolution of the imaging system, and the pixel density of the focal plane array.
2. EXPERIMENTAL APPROACH Infrared absorption spectra for RDX and Tetryl measured by researchers at Pacific Northwest National Laboratory7 are shown in Fig. 1. From these two spectra one can see that numerous absorption features exist that can be probed with various mid-infrared laser technologies. In our work, a pair of tunable CO2 lasers was used to illuminate the explosives samples, on- and off-absorption, in the wavelength region between 9.2 and 10.6 µm. But as has been demonstrated in Ref. 5, illumination could have been accomplished as well with an external cavity tunable QCL, optical parametric oscillator (OPO),8 or with discrete wavelength QCLs judiciously selected to highlight targeted absorption contrasted with background features.9
0 6 S 10 12 14 Figure'6'
(e)'
0 S 10 12 14 pm Fig. 1. Absorption spectra for RDX, and Tetryl from 5 to 15 µm. Note the prominent features that lie between 6 and 8 µm. Absorption unitsFigure are arbitrary 35: thus the absoluteIR absorption absorption magnitude between spectra the different explosivesFigure cannot be 36: Reflectance spectra of a tetryl sample compared as theof sample Tetryl. quantities were Reproduced uncalibrated. Thus, these spectra from were used [194]. to locate regions of interestapplied within to a car door at 0◦ (a), 5◦ (b), 40◦ (c) and the tuning range of our illumination lasers. reference absorption spectrum (d); (e) an optical A schematic of the experimental setup used for illumination and imaging is shown in Fig. 2. The tunablemicroscope CO2 laser image of the tetryl sample on a car 10 outputs (Access Laser LASY-4G) are guided to a flip mirror that is used to select either on- ordoor. off-absorption Reproduced from [185]. illumination wavelengths. The selected beam is then caused to diverge by an off-axis parabolic (OAP) mirror, and directed towards the sample surface by a galvanometer mirror. The galvanometer is used to dither the illumination beam while simultaneously averaging multiple images to reduce the effects of diffraction, speckle and interference on the acquired images. An example of diffraction and its effects due to an opaque object along with the improved image
resultingFigure'7' from dithering the illuminating beam are shown in Fig.(a) and (b), respectively. By dithering the illuminationFigure'8' beam and averaging multiple images to wash out diffraction and interference effects, a much improved image can be obtained. This technique will not, however, reduce any interference or diffraction effects that occur in the optical path from the sample surface to the camera focal plane. The strongest lines emitted by these lasers have approximately
(e)'
Proc. of SPIE Vol. 6945 694517-2
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Figure 37: Reflectance spectra of a TNT sample on a Figure 38: Reflectance of TNT at car door at 0◦ (a), 5◦ (b), 30◦ (c) and reference absorp- a concentration of 120 µg cm−2 tion spectrum (d); (e) an optical microscope image of the on aluminum (blue line) and car TNT sample on a car door. Reproduced from [185]. metal paint (black line). Repro- duced from [197].
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30 Appendix A Planar Slab Reflectance: Definitions, Nota- tion, and Derivation
Here we provide the basic notation and develop the expressions required for the analysis of the incoherent spectral reflectance of a planar layer of finite thickness on an semi-infinite substrate, the essential geometry of which is shown in Figure 1 in §2. Consider a plane electromagnetic wave with electric field vector E(t,x) = E exp(iωt − ik0 · x) incident on the the sample (medium 1) at an angle θ0 relative to the surface normal. Here E, ω, and k0 are the radiation’s vector amplitude, frequency, and wave vector, respectively, and t, x indicate time and spatial position; the wave vector k0 = (ω/c)sˆ = k0sˆ where sˆ is the unit vector along the wave’s propagation direction and c is the speed of light. The wavelength in medium 0 is then given by λ0 = 2π/k0 = 2πc/ω. −1 −1 This wave’s Poynting vector (i.e., energy flux with dimensions [energy area time ]) is S0 = 1/2 2 1/2 2 ∗ ∗ n0ε0 |E | /(2µ0 )sˆ, where |E | = EE and E denotes the complex conjugate of E . For the calculation of reflectance, we will be interested in the components of S normal to the sample interface. We denote these interface-normal components of the incident, reflected, and transmitted flux vectors as I0, IR, and IT . These interface-normal components depend on the wave’s interface- parallel field components. For a wave incidence angle, θ0 =6 0, these in turn depend on whether E is in or perpendicular to the plane of incidence (also designated as p-polarized and s-polarized waves, respectively).
The expressions for reflectance, R ≡ IR/I0, and transmittance, T ≡ IT /I0, resulting for the two polarization state cases can be written in a unified manner in terms of the so-called tilted optical admittances η j of the involved media [e.g., 11]:
( n˜ j for p-polarization, cosθ j η j = (3) n˜ j cosθ j for s-polarization.
The θ-quantities in two media j and k are related by Snell’s law:
n˜ j sinθ j = n˜k sinθk , (4) and are, generally speaking, complex quantities. With the assumption that κ0 = 0, the cosθ j ≡ a j −ib j for j =(1, 2) may be calculated in terms of θ0 explicitly as [following the notation in 198]: v v uq uq u p2 + q2 + p u p2 + q2 − p t j j j t j j j a − ib = − i (5) j j 2 2 where !2 2 2 n0 sinθ0 p j = 1 + κ j − n j 2 2 , (6) n j + κ j and !2 n0 sinθ0 q j = −2n jκ j 2 2 . (7) n j + κ j
31 0 R01 T10
T 01 R 1 10 R12
T12 2
Figure A-1: Graphical representation of the single interface intensity reflectance and transmittance coefficients used to derive R and T.
It will be useful in the following to cast the expressions for R and T in terms of the single-interface field-amplitude reflection, ρ jk, and transmission, τ jk, coefficients. which provide the ratio between the incident, reflected, and transmitted parallel-component of E at an interface of two media with refractive indicesn ˜ j andn ˜k. Specifically [11]:
η j − ηk ρ jk = , (8) η j + ηk and 2η j τ jk = . (9) η j + ηk
Both ρ jk and τ jk are generally complex quantities. The first and second subscripts on both quanti- ties refers to the media on the incident and transmitting side of the interface, respectively.
Referring to Figure A-1, at the interface between media j and k, a fraction R jk of an incident wave’s intensity is reflected and a fraction Tjk is transmitted. These single-interface intensity coefficients are given in terms of the corresponding amplitude coefficients [11]: 2 R jk = |ρ jk| , (10) and ℜ{ηk} 2 Tjk = |τ jk| , (11) ℜ{η j} where ℜ designates the real part of a quantity. The Tjk can also be written in terms of ρ jk: ℜ{ ∗ − ∗ } 2 η j (ρ jk ρ jk) Tjk = 1 − |ρ jk| + (12) ℜ{η j}
For κ1 =6 0, we must take account of the energy absorption within the sample. Across the sample’s thickness, there is a shift in the wave’s complex phase equal to 2πn˜ φ˜ = 1 d cosθ . (13) λ 1 The imaginary part of φ˜, which we will denote as α, determines the wave’s attenuation while traversing the sample and is given by: 4π α = (κ1a1 + n1b1) . (14) λ0
32 The attenuation factor experienced by a wave over one transit of the sample is e−αd, as indicated in Figure A-1. Finally, the incoherent R and T can be calculated most directly by summing over the path of an imaginary ray experiencing an infinite number of reflections within medium-1. Skipping the details, this produces the following expressions:
R + R e−2αd T T − R2 R 01 12 01 10 01 = −2αd , (15) 1 − R01R12e and T T e−αd T 01 12 = −2αd . (16) 1 − R01R12e In the case κ1 = 0, we have T01 = T10 = 1 − R01 and Equation (1) reduces to the usual expression for R, namely R = (R01 + R12 − 2R01R12)/(1 − R01R12).
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34 References
[1] J. M. Ziman, Principles of the Theory of Solids, 2nd ed. Cambridge, UK: Cambridge University Press, 1972.
[2] G. M. Hale and M. R. Querry, “Optical Constants of Water in the 200-nm to 200-microm Wavelength Region.” Appl. Opt., vol. 12, no. 3, pp. 555–563, 1973.
[3] S. G. Warren and R. E. Brandt, “Optical constants of ice from the ultraviolet to the microwave: A revised compilation,” J. Geophys. Res. Atmos., vol. 113, p. D14220, 2008.
[4] Y. Sarov, S. Sainov, and V. Marinova, “Refractive index of ferroelectric Pb2ScTaO6 single crystals around the phase transition,” Mater. Sci. Eng. B, vol. 83, pp. 231–234, 2001.
[5] M. Zakerhamidi and H. Rahimzadeh, “Order parameters and refractive indices of some cyano-benzoate nematic liquid crystals with high transition temperatures,” J. Mol. Liq., vol. 172, pp. 41–45, 2012.
[6] C. F. Bohren and D. R. Huffman, Absorption and Scattering of Light by Small Particles. Wienheim: Wiley- VCH Verlag GmbH, 2004.
[7] B. Hapke, Theory of Reflectance and Emittance Spectroscopy. Cambridge: Cambridge University Press, 1993.
[8] T. Mooney and R. F. Knacke, “Optical constants of chlorite and serpentine between 2.5 and 50 µm,” Icarus, vol. 64, no. 3, pp. 493–502, Dec. 1985.
[9] M. L. Wenrich and P. R. Christensen, “Optical constants of minerals derived from emission spectroscopy: Application to quartz,” J. Geophys. Res., vol. 101, no. B7, pp. 15 921–15 931, Jun. 1996.
[10] T. D. Glotch and G. R. Rossman, “Mid-infrared reflectance spectra and optical constants of six iron oxide/oxyhydroxide phases,” Icarus, vol. 204, no. 2, pp. 663–671, Dec. 2009.
[11] H. A. Macleod, Thin-Film Optical Filters, 3rd ed. New York, NY: Taylor & Francis Group, 2001.
[12] R. Hudson, P. Gerakines, and M. Moore, “Infrared spectra and optical constants of astronomical ices: II. Ethane and ethylene,” Icarus, vol. 243, pp. 148–157, Nov. 2014.
[13] A. Einstein, “Strahlungs-Emission und Absorption nach der Quantentheorie,” Dtsch. Phys. Gesellschaft, 1916.
[14]M. Simeˇ ckovˇ a,´ D. Jacquemart, L. S. Rothman, R. R. Gamache, and A. Goldman, “Einstein A-coefficients and statistical weights for molecular absorption transitions in the HITRAN database,” J. Quant. Spectrosc. Radiat. Transf., vol. 98, no. 1, pp. 130–155, Mar. 2006.
[15] C. Joblin, L. D’Hendrecourt, A. Leger,´ and D. Defourneau,´ “Infrared spectroscopy of gas-phase PAH molecules I. Role of the physical environment,” Astron. Astrophys., vol. 281, pp. 923–936, 1994.
[16] H. R. Zelsmann, “Temperature dependence of the optical constants for liquid H2O and D2O in the far IR region,” J. Mol. Struct., vol. 350, no. 2, pp. 95–114, 1995.
[17] C. Girardet, J. Humbert, and P. Hoang, “Theoretical approach of the infrared profile of molecular adsorbates on clean surfaces: inhomogeneous broadening,” Chem. Phys., vol. 230, no. 1, pp. 67–81, Apr. 1998.
[18] W. Grundy and B. Schmitt, “The temperature-dependent near-infrared absorption spectrum of hexagonal H2O ice,” J. Geophys. Res., vol. 103, no. E11, pp. 809–822, 1998.
[19] Y. Wu, F. Meersman, K. Heremans, and Y. Ozaki, “Hybrid two-dimensional correlation infrared study on the temperature- and pressure-induced concentration dynamics and structural variations of poly(N-isopropylacrylamide),” J. Mol. Struct., vol. 799, pp. 134–140, Nov. 2006.
[20] P. Majewska, M. Rospenk, B. Czarnik-Matusewicz, A. Kochel, L. Sobczyk, and R. Dbrowski, “Structure and polarized IR spectra of 4-isothiocyanatophenyl 4-heptylbenzoate (7TPB),” Chem. Phys., vol. 354, pp. 186–195, Dec. 2008.
35 [21] R. Hudson, M. Moore, and L. Raines, “Ethane ices in the outer Solar System: Spectroscopy and chemistry,” Icarus, vol. 203, no. 2, pp. 677–680, Oct. 2009.
[22] C. Marcott, G. M. Story, A. E. Dowrey, J. T. Grothaus, D. C. Oertel, I. Noda, E. Margalith, and L. Nguyen, “Mining the information content buried in infrared and nearinfrared band shapes by temporal, spatial, and other perturbations,” Appl. Spectrosc., vol. 63, no. 12, p. 346A, 2009.
[23] M. M. Bishop, R. S. Chellappa, Z. Liu, D. N. Preston, M. M. Sandstrom, D. M. Dattelbaum, Y. K. Vohra, and N. Velisavljevic, “High pressure-temperature polymorphism of 1,1-diamino-2,2-dinitroethylene,” J. Phys. Conf. Ser., vol. 500, p. 052005, 2014.
[24] H. Ozbek, S. Ustunel, E. Kutlu, and M. Cetinkaya, “A simple method to determine high-accuracy refractive indices of liquid crystals and the temperature behavior of the related optical parameters via high-resolution birefringence data,” J. Mol. Liq., vol. 199, pp. 275–286, 2014.
[25] G. Boer, I. Sokolik, and S. Martin, “Infrared optical constants of aqueous sulfate nitrate ammonium multicomponent tropospheric aerosols from attenuated total reflectance measurements, Part I: Results and analysis of spectral absorbing features,” J. Quant. Spectrosc. Radiat. Transf., vol. 108, pp. 17–38, Nov. 2007.
[26] C. Arean, M. Delgado, R. Bulanek,´ and K. Frolich, “Combined microcalorimetric and IR spectroscopic study on carbon dioxide adsorption in H-MCM-22,” Appl. Surf. Sci., vol. 316, pp. 532–536, Oct. 2014.
[27] J. R. Schoonover, D. M. Dattelbaum, J. C. Osborn, J. S. Bridgewater, and J. W. Kenney, “Pressure-dependent Fourier transform infrared spectroscopy of a poly (ester urethane),” Spectrochim. Acta Part A Mol. Biomol. Spectrosc., vol. 59, pp. 309–319, Jan. 2003.
[28] E. D. Emmons, R. G. Kraus, S. S. Duvvuri, J. S. Thompson, and A. M. Covington, “High-pressure infrared absorption spectroscopy of poly(methyl methacrylate),” J. Polym. Sci. Part B Polym. Phys., vol. 45, no. 3, pp. 358–367, Feb. 2007.
[29] Y. Tsuchida and T. Yagi, “New pressure-induced transformations of silica at room temperature,” Nature, vol. 347, no. 6290, pp. 267–269, Sep. 1990.
[30] O. Mishima and H. E. Stanley, “Decompression-induced melting of ice IV and the liquidliquid transition in water,” Nature, vol. 392, no. 6672, pp. 164–168, Mar. 1998.
[31] Q. Williams and R. Jeanloz, “Spectroscopic Evidence for Pressure-Induced Coordination Changes in Silicate Glasses and Melts,” Science, vol. 239, no. 4842, pp. 902–905, Feb. 1988.
[32] M. Pravica, M. Galley, E. Kim, P. Weck, and Z. Liu, “A far- and mid-infrared study of HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) under high pressure,” Chem. Phys. Lett., vol. 500, no. 1-3, pp. 28–34, Nov. 2010.
[33] F. Goetz, T. B. Brill, and J. R. Ferraro, “Pressure dependence of the Raman and infrared spectra of α-, β-, γ-, and δ-octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine,” J. Phys. Chem., vol. 82, no. 17, pp. 1912–1917, Aug. 1978.
[34] G. D. Saraiva, M. Maczka, P. T. C. Freire, J. Mendes Filho, F. E. A. Melo, J. Hanuza, Y. Morioka, and A. G. Souza Filho, “Pressure-induced irreversible phase transition in KSc(MoO4),” Phys. Rev. B, vol. 67, no. 22, p. 224108, Jun. 2003.
[35] Z. A. Dreger and Y. M. Gupta, “Phase Diagram of Hexahydro-1,3,5-trinitro-1,3,5-triazine Crystals at High Pressures and Temperatures,” J. Phys. Chem. A, vol. 114, no. 31, pp. 8099–8105, Aug. 2010.
[36] C. Joblin, P. Boissel, a. Leger, L. D’Hendecourt, and D. Defourneau, “Infrared spectroscopy of gas-phase PAH molecules II. Role of the temperature,” Astron. Astrophys., vol. 299, pp. 835–846, 1995.
36 [37] A. Politano, G. Chiarello, G. Benedek, E. Chulkov, and P. Echenique, “Vibrational spectroscopy and theory of alkali metal adsorption and co-adsorption on single-crystal surfaces,” Surf. Sci. Rep., vol. 68, no. 3-4, pp. 305–389, Nov. 2013.
[38] R. Hudson, R. Ferrante, and M. Moore, “Infrared spectra and optical constants of astronomical ices: I. Amorphous and crystalline acetylene,” Icarus, vol. 228, pp. 276–287, Jan. 2014.
[39] S. T. Martin, D. Salcedo, L. T. Molina, and M. J. Molina, “Phase Transformations of Micron-Sized H2SO4/H2O Particles Studied by Infrared Spectroscopy,” J. Phys. Chem. B, vol. 101, no. 27, pp. 5307–5313, Jul. 1997.
[40] L. Colangeli, V. Mennella, and E. Bussoletti, “Temperature dependence of infrared bands produced by polycyclic aromatic hydrocarbons,” Astrophys. J., vol. 385, p. 577, Feb. 1992.
[41] H. Foerstendorf, N. Jordan, and K. Heim, “Probing the surface speciation of uranium (VI) on iron (hydr)oxides by in situ ATR FT-IR spectroscopy,” J. Colloid Interface Sci., vol. 416, pp. 133–138, Feb. 2014.
[42] E. Carrasco, A. Aumer, M. A. Brown, R. Dowler, I. Palacio, S. Song, and M. Sterrer, “Infrared spectra of high coverage CO adsorption structures on Pt(111),” Surf. Sci., vol. 604, no. 15-16, pp. 1320–1325, Aug. 2010.
[43] G. Spoto, E. N. Gribov, G. Ricchiardi, A. Damin, D. Scarano, S. Bordiga, C. Lamberti, and A. Zecchina, “Carbon monoxide MgO from dispersed solids to single crystals: A review and new advances,” Prog. Surf. Sci., vol. 76, no. 3-5, pp. 71–146, 2004.
[44] T. Fornaro, J. R. Brucato, E. Pace, M. C. Guidi, S. Branciamore, and A. Pucci, “Infrared spectral investigations of UV irradiated nucleobases adsorbed on mineral surfaces,” Icarus, vol. 226, no. 1, pp. 1068–1085, 2013.
[45] H. Foerstendorf, K. Heim, and A. Rossberg, “The complexation of uranium(VI) and atmospherically derived CO2 at the ferrihydrite-water interface probed by time-resolved vibrational spectroscopy,” J. Colloid Interface Sci., vol. 377, no. 1, pp. 299–306, Jul. 2012.
[46] J. D. Fox, “Infrared vibrational spectra of tert-butyl halides in low-aluminum H-Y Faujasite: Vibrational excitation exchange and other effects of guesthost interactions,” Chem. Phys., vol. 325, no. 2-3, pp. 265–277, Jun. 2006.
[47] J. Chowdhury, J. Sarkar, R. De, M. Ghosh, and G. Talapatra, “Adsorption of 2-amino-6-methylbenzothiazole on colloidal silver particles: Quantum chemical calculations and surface enhanced Raman scattering study,” Chem. Phys., vol. 330, no. 1-2, pp. 172–183, Nov. 2006.
[48] H. Zorgati, C. Ramseyer, and C. Girardet, “Heterogeneous against homogeneous spectral response of polar molecules adsorbed on a real surface,” Chem. Phys., vol. 362, no. 1-2, pp. 41–57, Jul. 2009.
[49] M. Moskovits, “Surface selection rules,” J. Chem. Phys., vol. 77, no. 9, p. 4408, 1982.
[50] J. Creighton, “Surface raman electromagnetic enhancement factors for molecules at the surface of small isolated metal spheres: The determination of adsorbate orientation from sers relative intensities,” Surf. Sci., vol. 124, no. 1, pp. 209–219, Jan. 1983.
[51] T. Yamada, K. Shirasaka, A. Takano, and M. Kawai, “Adsorption of cytosine, thymine, guanine and adenine on Cu(1 1 0) studied by infrared reflection absorption spectroscopy,” Surf. Sci., vol. 561, no. 2-3, pp. 233–247, 2004.
[52] E. Mateo-Mart´ı, C. Briones, C. Rogero, C. Gomez-Navarro, C. Methivier, C. Pradier, and J. Mart´ın-Gago, “Nucleic acid interactions with pyrite surfaces,” Chem. Phys., vol. 352, no. 1-3, pp. 11–18, Sep. 2008.
[53] A. Lopez, T. Heller, T. Bitzer, and N. V. Richardson, “A vibrational study of the adsorption of glycine on clean and Na modified Si-21 surfaces,” Chem. Phys., vol. 277, no. 1, pp. 1–8, Mar. 2002.
37 [54] F. Boccuzzi, A. Chiorino, and E. Guglielminotti, “Effects of structural defects and alloying on the FTIR spectra of CO adsorbed onnPt/ZnO,” Surf. Sci., vol. 368, no. 1-3, pp. 264–269, Dec. 1996.
[55] J. D. Fox and A. Meenakshi, “Effects of tert-butyl halide molecular siting in crystalline NaX faujasite on the infrared vibrational spectra.” J. Phys. Chem. B, vol. 109, no. 20, pp. 9917–26, May 2005.
[56] A. Garnier, S. Sall, F. Garin, M. Chetcuti, and C. Petit, “Site effects in the adsorption of carbon monoxide on real 1.8nm Pt nanoparticles: An Infrared investigation in time and temperature,” J. Mol. Catal. A Chem., vol. 373, pp. 127–134, Jul. 2013.
[57] C. D. Zeinalipour-Yazdi, D. J. Willock, L. Thomas, K. Wilson, and A. F. Lee, “CO adsorption over Pd nanoparticles: A general framework for IR simulations on nanoparticles,” Surf. Sci., Jul. 2015.
[58] M. Buchholz, M. Xu, H. Noei, P. Weidler, A. Nefedov, K. Fink, Y. Wang, and C. Woll,¨ “Interaction of carboxylic acids with rutile TiO2(110): IR-investigations of terephthalic and benzoic acid adsorbed on a single crystal substrate,” Surf. Sci., Aug. 2015.
[59] Y. Takeshita, E. Becker, S. Sakata, T. Miwa, and T. Sawada, “States of water absorbed in water-borne urethane/epoxy coatings,” Polymer, vol. 55, no. 10, pp. 2505–2513, May 2014.
[60] M. Van Thiel, E. D. Becker, and G. C. Pimentel, “Infrared Studies of Hydrogen Bonding of Water by the Matrix Isolation Technique,” J. Chem. Phys., vol. 27, no. 2, p. 486, Aug. 1957.
[61] K. Buijs and G. R. Choppin, “Near-Infrared Studies of the Structure of Water. I. Pure Water,” J. Chem. Phys., vol. 39, no. 8, p. 2035, Jun. 1963.
[62] J. Tennyson, P. F. Bernath, L. R. Brown, A. Campargue, A. G. Csasz´ ar,´ L. Daumont, R. R. Gamache, J. T. Hodges, O. V. Naumenko, O. L. Polyansky, L. S. Rothman, A. C. Vandaele, N. F. Zobov, A. R. Al Derzi, C. Fabri,´ A. Z. Fazliev, T. Furtenbacher, I. E. Gordon, L. Lodi, and I. I. Mizus, “IUPAC critical evaluation of 16 the rotational-vibrational spectra of water vapor, Part III: Energy levels and transition wavenumbers for H2 O,” J. Quant. Spectrosc. Radiat. Transf., vol. 117, pp. 29–58, 2013.
[63] D. Eisenberg and W. Kauzmann, The structure and properties of water. London: Oxford University Press, 1969.
[64] J.-J. Max and C. Chapados, “Isotope effects in liquid water by infrared spectroscopy. III. H2O and D2O spectra from 6000 to 0 cm−1,” J. Chem. Phys., vol. 131, no. 18, p. 184505, Nov. 2009.
[65] N. Kitadai, T. Sawai, R. Tonoue, S. Nakashima, M. Katsura, and K. Fukushi, “Effects of Ions on the OH Stretching Band of Water as Revealed by ATR-IR Spectroscopy,” J. Solution Chem., vol. 43, no. 6, pp. 1055–1077, Jun. 2014.
[66] C. Sammon, C. Deng, and J. Yarwood, “Polymerwater interactions. Origin of perturbed infrared intensities of water in polymeric systems,” Polymer, vol. 44, no. 9, pp. 2669–2677, Apr. 2003.
[67] R. Mastrapa, M. Bernstein, S. Sandford, T. Roush, D. Cruikshank, and C. Ore, “Optical constants of amorphous and crystalline H2O-ice in the near infrared from 1.1 to 2.6 µm,” Icarus, vol. 197, no. 1, pp. 307–320, Sep. 2008.
[68] R. M. Mastrapa, S. a. Sandford, T. L. Roush, D. P. Cruikshank, and C. M. Dalle Ore, “Optical Constants of −1 Amorphous and Crystalline H2O-Ice: 2.5-22 µm (4000-455 cm ) Optical Constants of H2O-Ice,” Astrophys. J., vol. 701, no. 2, pp. 1347–1356, Aug. 2009.
[69] R. E. Milliken and J. F. Mustard, “Quantifying absolute water content of minerals using near-infrared reflectance spectroscopy,” J. Geophys. Res., vol. 110, no. E12, pp. 1–25, 2005.
[70] J. L. Bishop, “Infrared Spectroscopic Analyses on the Nature of Water in Montmorillonite,” Clays Clay Miner., vol. 42, no. 6, pp. 702–716, 1994.
38 [71] J. D. Russell and V. C. Farmer, “Infra-Red Spectroscopic Study of the Dehydration of Montmorillonite and Saponite,” Clay Miner., vol. 5, no. 32, pp. 443–464, 1964.
[72] G. Sposito, R. Prost, and J.-P. Gaultier, “Infrared Spectroscopic Study of Adsorbed Water on Reduced-Charge Na/Li-Montmorillonites,” Clays Clay Miner., vol. 31, no. 1, pp. 9–16, 1983.
[73] C. T. Johnston, G. Sposito, and C. Erickson, “Vibrational Probe Studies of Water Interactions with Montmorillonite,” Clays Clay Miner., vol. 40, no. 6, pp. 722–730, 1992.
[74] F. Cariati, L. Erre, G. Micera, P. Piu, and C. Gessa, “Polarization of Water Molecules in Phyllosilicates in Relation to Exchange Cations as Studied by near Infrared Spectroscopy,” Clays Clay Miner., vol. 31, no. 2, pp. 155–157, 1983.
[75] ——, “Effects of Layer Charge on the Near-Infrared Spectra of Water Molecules in Smectites and Vermiculites,” Clays Clay Miner., vol. 31, no. 6, pp. 447–449, 1983.
[76] J. A. Hockey and B. A. Pethica, “Surface hydration of silicas,” Trans. Faraday Soc., vol. 57, p. 2247, 1961.
[77] J. Anderson and K. Wickersheim, “Near infrared characterization of water and hydroxyl groups on silica surfaces,” Surf. Sci., vol. 2, pp. 252–260, Jan. 1964.
[78] T. W. Dijkstra, R. Duchateau, R. A. van Santen, A. Meetsma, and G. P. A. Yap, “Silsesquioxane Models for Geminal Silica Surface Silanol Sites. A Spectroscopic Investigation of Different Types of Silanols,” J. Am. Chem. Soc., vol. 124, no. 33, pp. 9856–9864, Aug. 2002.
[79] K. Langer and O. W. Florke, “Near infrared absorption spectra (4000-9000 1/cm) of opals and the role of water in these SiO2(nH2O) minerals.” Fortschritte der Mineral., vol. 52, p. 17, 1974.
[80] M. Rice, E. Cloutis, J. Bell, D. Bish, B. Horgan, S. Mertzman, M. Craig, R. Renaut, B. Gautason, and B. Mountain, “Reflectance spectra diversity of silica-rich materials: Sensitivity to environment and implications for detections on Mars,” Icarus, vol. 223, no. 1, pp. 499–533, Mar. 2013.
[81] Y. Maeda, M. Ide, and H. Kitano, “Vibrational spectroscopic study on the structure of water in polymer systems,” J. Mol. Liq., vol. 80, no. 2-3, pp. 149–163, May 1999.
[82] Z. Ping, Q. Nguyen, S. Chen, J. Zhou, and Y. Ding, “States of water in different hydrophilic polymers DSC and FTIR studies,” Polymer, vol. 42, no. 20, pp. 8461–8467, Sep. 2001.
[83] G. G. Zundel, Hydration and intermolecular interactions. New York: Academic Press, 1969.
[84] A. Lasagabaster,´ M. J. Abad, L. Barral, A. Ares, and R. Bouza, “Application of FTIR spectroscopy to determine transport properties and waterpolymer interactions in polypropylene (PP)/poly(ethylene-co-vinyl alcohol) (EVOH) blend films: Effect of poly(ethylene-co-vinyl alcohol) content and water activity,” Polymer, vol. 50, no. 13, pp. 2981–2989, Jun. 2009.
[85] D. Cava, L. Cabedo, E. Gimenez, R. Gavara, and J. Lagaron, “The effect of ethylene content on the interaction between ethylenevinyl alcohol copolymers and water: (I) Application of FT-IR spectroscopy to determine transport properties and interactions in food packaging films,” Polym. Test., vol. 25, no. 2, pp. 254–261, Apr. 2006.
[86] S. Cotugno, D. Larobina, G. Mensitieri, P. Musto, and G. Ragosta, “A novel spectroscopic approach to investigate transport processes in polymers: the case of waterepoxy system,” Polymer, vol. 42, no. 15, pp. 6431–6438, Jul. 2001.
[87] M. Laporta, M. Pegoraro, and L. Zanderighi, “Perfluorosulfonated membrane (Nafion): FT-IR study of the state of water with increasing humidity,” Phys. Chem. Chem. Phys., vol. 1, no. 19, pp. 4619–4628, 1999.
39 [88] P. Musto, G. Mensitieri, M. Lavorgna, G. Scarinzi, and G. Scherillo, “Combining gravimetric and vibrational spectroscopy measurements to quantify first- and second-shell hydration layers in polyimides with different molecular architectures.” J. Phys. Chem. B, vol. 116, no. 4, pp. 1209–20, Feb. 2012.
[89] J. Mijovic´ and H. Zhang, “Local Dynamics and Molecular Origin of Polymer NetworkWater Interactions as Studied by Broadband Dielectric Relaxation Spectroscopy, FTIR, and Molecular Simulations,” Macromolecules, vol. 36, no. 4, pp. 1279–1288, Feb. 2003.
[90] H. X. Yang, M. Sun, and P. Zhou, “Investigation of water diffusion in poly(3-hydroxybutyrate-co-3- hydroxyhexanoate) by generalized two-dimensional correlation ATR-FTIR spectroscopy,” Polymer, vol. 50, no. 6, pp. 1533–1540, 2009.
[91] C. Frondel, “Structural hydroxyl in chalcedony (type B quartz).” Am. Mineral., vol. 67, no. 11-12, pp. 1248–1257, 1982.
[92] L. Philippe, C. Sammon, S. B. Lyon, and J. Yarwood, “An FTIR/ATR in situ study of sorption and transport in corrosion protective organic coatings,” Prog. Org. Coatings, vol. 49, no. 4, pp. 302–314, May 2004.
[93] J. R. Schoonover, W. P. Steckle, J. D. Cox, C. T. Johnston, Y. Wang, A. M. Gillikin, and R. A. Palmer, “Humidity-dependent dynamic infrared linear dichroism study of a poly(ester urethane),” Spectrochim. Acta Part A Mol. Biomol. Spectrosc., vol. 67, no. 1, pp. 208–213, May 2007.
[94] L.-M. Doppers,¨ C. Sammon, C. Breen, and J. Yarwood, “FTIR-ATR studies of the sorption and diffusion of acetone/water mixtures in poly(vinyl alcohol),” Polymer, vol. 47, no. 8, pp. 2714–2722, Apr. 2006.
[95] N. S. Schneider, J. L. Illinger, and F. E. Karasz, “The interaction of water with polyurethanes containing block copolymer soft segments,” J. Appl. Polym. Sci., vol. 47, no. 8, pp. 1419–1425, Feb. 1993.
[96] P. Pissis, L. Apekis, C. Christodoulides, M. Niaounakis, A. Kyritsis, and J. Nedbal, “Water effects in polyurethane block copolymers,” J. Polym. Sci. Part B Polym. Phys., vol. 34, no. 9, pp. 1529–1539, Jul. 1996.
[97] A. Wang and Y. Zhou, “Experimental comparison of the pathways and rates of the dehydration of Al-, Fe-, Mg- and Ca-sulfates under Mars relevant conditions,” Icarus, vol. 234, pp. 162–173, May 2014.
[98] G. Openhaim and E. Grushka, “Temperature-dependent refractive index issues using a UVvisible detector in high-performance liquid chromatography,” J. Chromatogr. A, vol. 942, no. 1-2, pp. 63–71, Jan. 2002.
[99] R. J. Rioboo,´ M. Philipp, M. a. Ramos, and J. K. Kruger,¨ “Concentration and temperature dependence of the refractive index of ethanol-water mixtures: Influence of intermolecular interactions,” Eur. Phys. J. E, vol. 30, no. 1, pp. 19–26, Sep. 2009.
[100] I. Bratu, R. Grecu, R. Constantinescu, and T. Iliescu, “Molecular relaxation processes of 2-bromopropane in solutions from IR ν(CBr) band shape analysis,” Spectrochim. Acta Part A Mol. Biomol. Spectrosc., vol. 54, no. 3, pp. 501–506, Mar. 1998.
[101] D. Yamini, V. Sasirekha, and V. Ramakrishnan, “Raman spectral studies on 2-hydroxyacetophenone in binary liquid mixtures,” Vib. Spectrosc., vol. 61, pp. 30–37, Jul. 2012.
[102] N. Tekin, C. Uyank, and S. K. Beyaz, “The Effects of Organic Solvents on the Frequency of C=O Stretching Vibration in Isophorone, 4-oxo-isophorone, and 2,6,6-trimethyl-4,4-(ethylenedioxy)cyclohex-2-en-1-one,” J. Appl. Spectrosc., vol. 81, no. 4, pp. 711–718, Sep. 2014.
[103] R. Nyquist, R. Streck, and G. Jeschek, “NMR and IR spectra-structure correlations for carbonyl containing compounds in various solvents,” J. Mol. Struct., vol. 377, no. 2, pp. 113–128, Mar. 1996.
[104] F. Khan and P. Sivagurunathan, “Infrared studies on hydrogen bonding interaction between acrylic esters with 1-dodeconal and phenol in carbon tetrachloride,” Phys. Chem. Liq., vol. 46, no. 5, pp. 504–509, Oct. 2008.
40 [105] Q. Liu, Y. Liu, H. Zhang, and Z. Wen, “Solvent effects on infrared spectroscopy of 17β-hydroxy-17-methyl-2- oxa-5α-androstan-3-one in single solvents,” Spectrochim. Acta Part A Mol. Biomol. Spectrosc., vol. 65, no. 1, pp. 164–168, Sep. 2006.
[106] B. Hernandez,´ J. M. Gavira-Vallejo, R. Navarro, and A. Hernanz, “Splitting of infrared bands of mononu- cleotides in aqueous solution,” J. Mol. Struct., vol. 565-566, pp. 259–263, 2001.
[107] A. Stolov, W. Herrebout, and B. van der Veken, “Solvent effect on vibrational frequencies: cryosolution experiments and density functional calculations,” J. Mol. Struct., vol. 480-481, pp. 499–503, May 1999.
[108] A. Zimniak, I. Oszczapowicz, A. Sikora, and I. Wawer, “Solvent-dependent conformational transitions in deacetylcephalothin investigated by 1H NMR and IR,” J. Mol. Struct., vol. 443, no. 1-3, pp. 115–121, Feb. 1998.
[109] J. S. Walker and C. A. Vause, “Reappearing Phases,” Sci. Am., vol. 256, no. 5, pp. 98–105, May 1987.
[110] A. Le Bras and S. Erard, “Reflectance spectra of regolith analogs in the mid-infrared: Effects of grain size,” Planet. Space Sci., vol. 51, no. 4-5, pp. 281–294, 2003.
[111] B. H. Horgan, E. A. Cloutis, P. Mann, and J. F. Bell, “Near-infrared spectra of ferrous mineral mixtures and methods for their identification in planetary surface spectra,” Icarus, vol. 234, pp. 132–154, May 2014.
[112] T. L. Myers, C. S. Brauer, Y.-F. Su, T. a. Blake, T. J. Johnson, and R. L. Richardson, “The influence of particle size on infrared reflectance spectra,” in Proc. SPIE, vol. 9088, 2014, p. 908809.
[113] F. Mancarella, V. Orofino, A. Blanco, M. D’Elia, and S. Fonti, “The role of particle size in the laboratory reflectance spectra of pyroxenes: The case of the 670-nm minor feature,” Planet. Space Sci., May 2015.
[114] Y.-F. Su, T. L. Myers, C. S. Brauer, T. a. Blake, B. M. Forland, J. E. Szecsody, and T. J. Johnson, “Infrared reflectance spectra: effects of particle size, provenance and preparation,” in Proc. SPIE, vol. 9253, 2014, p. 925304.
[115] V. E. Hamilton, R. V. Morris, J. E. Gruener, and S. a. Mertzman, “Visible, near-infrared, and middle infrared spectroscopy of altered basaltic tephras: Spectral signatures of phyllosilicates, sulfates, and other aqueous alteration products with application to the mineralogy of the Columbia Hills of Gusev Crater, Mars,” J. Geophys. Res. E Planets, vol. 113, no. 12, pp. 1–30, 2008.
[116] J. E. Moersch and P. R. Christensen, “Thermal emission from particulate surfaces: A comparison of scattering models with measured spectra,” J. Geophys. Res., vol. 100, no. E4, pp. 7465–7477, 1995.
[117] G. R. Hunt and L. M. Logan, “Variation of single particle mid-infrared emission spectrum with particle size.” Appl. Opt., vol. 11, no. 1, pp. 142–7, Jan. 1972.
[118] M. Lane and P. R. Christensen, “Thermal Infrared Emission Spectroscopy of Salt Minerals Predicted for Mars,” Icarus, vol. 135, no. 2, pp. 528–536, Oct. 1998.
[119] M. D. Lane, “Midinfrared optical constants of calcite and their relationship to particle size effects in thermal emission spectra of granular calcite,” J. Geophys. Res., vol. 104, no. E6, pp. 14 099–14 108, 1999.
[120] J. Mustard and J. Hays, “Effects of Hyperfine Particles on Reflectance Spectra from 0.3 to 25 µm,” Icarus, vol. 125, no. 1, pp. 145–163, Jan. 1997.
[121] L. Moroz, A. Basilevsky, T. Hiroi, S. Rout, D. Baither, C. van der Bogert, O. Yakovlev, A. Fisenko, L. Semjonova, V. Rusakov, D. Khramov, N. Zinovieva, G. Arnold, and C. Pieters, “Spectral properties of simulated impact glasses produced from martian soil analogue JSC Mars-1,” Icarus, vol. 202, no. 1, pp. 336–353, Jul. 2009.
[122] C. Cooper and J. Mustard, “Effects of Very Fine Particle Size on Reflectance Spectra of Smectite and Palagonitic Soil,” Icarus, vol. 142, no. 2, pp. 557–570, Dec. 1999.
41 [123] B. L. Cooper, “Midinfrared spectral features of rocks and their powders,” J. Geophys. Res., vol. 107, no. E4, pp. 1–1 – 1–17, 2002.
[124] M. Papini, “Study of the radiative properties of powdered and fibrous polymers,” Vib. Spectrosc., vol. 11, no. 1, pp. 61–68, Mar. 1996.
[125] S. Fonti, S. Montanaro, R. Politi, A. Blanco, a. C. Marra, G. a. Marzo, and V. Orofino, “Infrared reflectance spectra of particulate mixtures,” J. Geophys. Res., vol. 115, no. E6, Jun. 2010, E06003.
[126] J. R. Johnson, P. R. Christensen, and P. G. Lucey, “Dust coatings on basaltic rocks and implications for thermal infrared spectroscopy of Mars,” J. Geophys. Res., vol. 107, no. E6, 2002.
[127] P. G. Lucey, “Model near-infrared optical constants of olivine and pyroxene as a function of iron content,” J. Geophys. Res., vol. 103, no. E1, p. 1703, Jan. 1998.
[128] J. Salisbury and A. Wald, “The role of volume scattering in reducing spectral contrast of reststrahlen bands in spectra of powdered minerals,” Icarus, vol. 96, no. 1, pp. 121–128, Mar. 1992.
[129] A. E. Wald and J. W. Salisbury, “Thermal infrared directional emissivity of powdered quartz,” J. Geophys. Res., vol. 100, no. B12, p. 24665, 1995.
[130] A. Jurewicz, V. Orofino, A. C. Marra, and A. Blanco, “Optical constants of powdered limestone obtained by taking into account the grain shapes: Applicability to Martian studies,” Astron. Astrophys., vol. 410, no. 3, pp. 1055–1062, Nov. 2003.
[131] V. Orofino, A. Blanco, S. Fonti, R. Proce, and A. Rotundi, “The infrared optical constants of limestone particles and implications for the search of carbonates on Mars,” Planet. Space Sci., vol. 46, no. 11-12, pp. 1659–1669, Nov. 1998.
[132] L. Long, M. Querry, R. Bell, and R. Alexander, “Optical properties of calcite and gypsum in crystalline and powdered form in the infrared and far-infrared,” Infrared Phys., vol. 34, no. 2, pp. 191–201, Apr. 1993.
[133] V. P. Tishkovets, E. V. Petrova, and M. I. Mishchenko, “Scattering of electromagnetic waves by ensembles of particles and discrete random media,” J. Quant. Spectrosc. Radiat. Transf., vol. 112, no. 13, pp. 2095–2127, 2011.
[134] R. K. Vincent and G. R. Hunt, “Infrared reflectance from mat surfaces.” Appl. Opt., vol. 7, no. 1, pp. 53–9, Jan. 1968.
[135] G. R. Hunt and R. K. Vincent, “The Behavior of Spectral Features in the Infrared Emission from Particulate Surfaces of Various Grain Sizes,” J. Geophys. Res., vol. 73, no. 18, pp. 6039–6046, 1968.
[136] M. J. Harris, E. K. H. Salje, and B. K. Guttler, “An infrared spectroscopic study of the internal modes of sodium nitrate: implications for the structural phase transition,” J. Phys. Condens. Matter, vol. 2, no. 25, p. 5517, 1990.
[137] Y. Okada and A. Kokhanovsky, “Light scattering and absorption by densely packed groups of spherical particles,” J. Quant. Spectrosc. Radiat. Transf., vol. 110, no. 11, pp. 902–917, Jul. 2009.
[138] M. D. Kraft, “Effects of pure silica coatings on thermal emission spectra of basaltic rocks: Considerations for Martian surface mineralogy,” Geophys. Res. Lett., vol. 30, no. 24, p. 2288, 2003.
[139] K. Stack and R. Milliken, “Modeling near-infrared reflectance spectra of clay and sulfate mixtures and implications for Mars,” Icarus, vol. 250, pp. 332–356, Apr. 2015.
[140] T. Hiroi and C. M. Pieters, “Estimation of grain sizes and mixing ratios of fine powder mixtures of common geologic minerals,” J. Geophys. Res., vol. 99, no. E5, pp. 10 867–10 879, 1994.
42 [141] F. Poulet and S. Erard, “Nonlinear spectral mixing: Quantitative analysis of laboratory mineral mixtures,” J. Geophys. Res., vol. 109, no. E2, p. E02009, 2004.
[142] M. S. West, R. G. Resmini, and K. Manville, “Quantification of Constituents in Areal and Intimate Binary Mixtures of Particulate Materials,” Proc. SPIE, vol. 8040, no. 703, pp. 1–12, 2011.
[143] R. G. Resmini, R. S. Rand, D. W. Allen, and C. J. Deloye, “An analysis of the nonlinear spectral mixing of didymium and soda-lime glass beads using hyperspectral imagery (HSI) microscopy,” Proc. SPIE, vol. 9088, p. 90880Z, Jun. 2014.
[144] Y. Shkuratov, L. Starukhina, H. Hoffmann, and G. Arnold, “A Model of Spectral Albedo of Particulate Surfaces : Implications for Optical Properties of the Moon,” Icarus, vol. 137, pp. 235–246, 1999.
[145] M. I. Mishchenko, “Multiple scattering, radiative transfer, and weak localization in discrete random media: Unified microphysical approach,” Rev. Geophys., vol. 46, no. 2, pp. 1–33, Apr. 2008.
[146] B. Teolis, M. Loeffler, U. Raut, M. Fama,´ and R. Baragiola, “Infrared reflectance spectroscopy on thin films: Interference effects,” Icarus, vol. 190, no. 1, pp. 274–279, Sep. 2007.
[147] E. N. Brown and D. M. Dattelbaum, “The role of crystalline phase on fracture and microstructure evolution of polytetrafluoroethylene (PTFE),” Polymer (Guildf)., vol. 46, no. 9, pp. 3056–3068, Apr. 2005.
[148] Y. A. Eremin, J. C. Stover, and N. V. Grishina, “Discrete sources method for light scattering analysis from 3D asymmetrical features on a substrate,” J. Quant. Spectrosc. Radiat. Transf., vol. 70, no. 4-6, pp. 421–431, Aug. 2001.
[149] J. Hellmers and T. Wriedt, “Influence of particle shape models on T-matrix light scattering simulation,” J. Quant. Spectrosc. Radiat. Transf., vol. 89, no. 1-4, pp. 97–110, Nov. 2004.
[150] P. Yang, Q. Feng, G. Hong, G. Kattawar, W. WIiscombe, M. I. Mischenko, O. Dubovik, I. Laszlo, and I. Sokolik, “Modeling of the scattering and radiative properties of nonspherical dust-like aerosols,” J. Aerosol Sci., vol. 38, no. 10, pp. 995–1014, Oct. 2007.
[151] Z. Meng, P. Yang, G. W. Kattawar, L. Bi, K. Liou, and I. Laszlo, “Single-scattering properties of tri-axial ellipsoidal mineral dust aerosols: A database for application to radiative transfer calculations,” J. Aerosol Sci., vol. 41, no. 5, pp. 501–512, May 2010.
[152] F. Gruy, “Relationship between the morphology and the light scattering cross section of optically soft aggregates,” J. Quant. Spectrosc. Radiat. Transf., vol. 112, pp. 2609–2618, Jul. 2011.
[153] M. Kahnert, T. Nousiainen, and P. Mauno, “On the impact of non-sphericity and small-scale surface roughness on the optical properties of hematite aerosols,” J. Quant. Spectrosc. Radiat. Transf., vol. 112, pp. 1815–1824, Jan. 2011.
[154] T. Nousiainen, M. Kahnert, and H. Lindqvist, “Can particle shape information be retrieved from light-scattering observations using spheroidal model particles?” J. Quant. Spectrosc. Radiat. Transf., vol. 112, no. 13, pp. 2213–2225, Sep. 2011.
[155] E. V. Petrova and V. P. Tishkovets, “Light scattering by aggregates of varying porosity and the opposition phenomena observed in the low-albedo particulate media,” J. Quant. Spectrosc. Radiat. Transf., vol. 112, no. 13, pp. 2226–2233, Jan. 2011.
[156] R. Vilaplana, R. Luna, and D. Guirado, “The shape influence on the overall single scattering properties of a sample in random orientation,” J. Quant. Spectrosc. Radiat. Transf., vol. 112, no. 11, pp. 1838–1847, Jan. 2011.
[157] C. M. Sorensen, “Q-space analysis of scattering by particles: A review,” J. Quant. Spectrosc. Radiat. Transf., vol. 131, pp. 3–12, Dec. 2013.
43 [158] E. Zubko, K. Muinonen, O. Munoz,˜ T. Nousiainen, Y. Shkuratov, W. Sun, and G. Videen, “Light scattering by feldspar particles: Comparison of model agglomerate debris particles with laboratory samples,” J. Quant. Spectrosc. Radiat. Transf., vol. 131, pp. 175–187, Dec. 2013.
[159] E. Zubko, Y. Shkuratov, and G. Videen, “Effect of morphology on light scattering by agglomerates,” J. Quant. Spectrosc. Radiat. Transf., vol. 150, pp. 42–54, Jan. 2015.
[160] L. Bi and P. Yang, “Accurate simulation of the optical properties of atmospheric ice crystals with the invariant imbedding T-matrix method,” J. Quant. Spectrosc. Radiat. Transf., vol. 138, pp. 17–35, 2014.
[161] A. Doicu, Y. Eremin, D. S. Efremenko, and T. Trautmann, “Methods with discrete sources for electromagnetic scattering by large axisymmetric particles with extreme geometries,” J. Quant. Spectrosc. Radiat. Transf., vol. 164, pp. 137–146, Oct. 2015.
[162] Y. Wu, T. Cheng, L. Zheng, H. Chen, and H. Xu, “Single scattering properties of semi-embedded soot morphologies with intersecting and non-intersecting surfaces of absorbing spheres and non-absorbing host,” J. Quant. Spectrosc. Radiat. Transf., vol. 157, pp. 1–13, May 2015.
[163] O. Kemppinen, T. Nousiainen, and H. Lindqvist, “The impact of surface roughness on scattering by realistically shaped wavelength-scale dust particles,” J. Quant. Spectrosc. Radiat. Transf., vol. 150, pp. 55–67, Jan. 2015.
[164] P. D. Kleiber, V. H. Grassian, M. a. Young, and P. K. Hudson, “T -matrix studies of aerosol particle shape effects on IR resonance spectral line profiles and comparison with an experiment,” J. Geophys. Res., vol. 114, no. D21, pp. 1–10, Nov. 2009.
[165] N. Kiomarsipour, R. Shoja Razavi, K. Ghani, and M. Kioumarsipour, “Evaluation of shape and size effects on optical properties of ZnO pigment,” Appl. Surf. Sci., vol. 270, pp. 33–38, 2013.
[166] M. I. Mishchenko, “Bidirectional reflectance of flat, optically thick particulate layers: an efficient radiative transfer solution and applications to snow and soil surfaces,” J. Quant. Spectrosc. Radiat. Transf., vol. 63, no. 2-6, pp. 409–432, Sep. 1999.
[167] L. E. Kirkland, K. C. Herr, and P. M. Adams, “Infrared stealthy surfaces: Why TES and THEMIS may miss some substantial mineral deposits on Mars and implications for remote sensing of planetary surfaces,” J. Geophys. Res., vol. 108, no. E12, p. 5137, 2003.
[168] M. M. Osterloo, V. E. Hamilton, and F. S. Anderson, “A laboratory study of the effects of roughness on the thermal infrared spectra of rock surfaces,” Icarus, vol. 220, no. 2, pp. 404–426, 2012.
[169] M. D. Lane and P. R. Christensen, “Thermal infrared emission spectroscopy of anhydrous carbonates,” J. Geophys. Res., vol. 102, no. E11, p. 25581, Nov. 1997.
[170] J. Michalski, “Silicate alteration mineralogy of the martian surface from TES: Constraints from emission spec- troscopy of terrestrial materials.” Ph.D. Dissertation, Ariz. St. Univ, 2005.
[171] J. M. Palmer and B. G. Grant, The Art of Radiometry. Bellingham, WA: SPIE Press, 2009.
[172] C. Willers, Electro-Optical System Analysis and Design: A Radiometry Perspective. Society of Photo-Optical Instrumentation Engineers, 2013.
[173] J. A. Conant and M. A. LeCompte, “Signature Prediction and Modeling,” in Infrared Electro-Optical Syst. Handbook, Vol. 4, M. C. Dudzik, Ed. Bellingham, WA: SPIE Press & Environmental Research Institute of Michigan, 1993, ch. 6.
[174] M. Ashikhmin and P. Shirley, “An Anisotropic Phong BRDF Model,” J. Graph. Tools, vol. 5, no. 2, pp. 25–32, Jan. 2000.
44 [175] B. P. Sandford and D. C. Robertson, “Infrared Reflectance Properties of Aircraft Paints,” Philips Laboratory, Geophyiscs Directorate, Tech. Rep., 1994.
[176] R. G. Priest and T. a. Germer, “Polarimetric BRDF in the Microfacet Model: Theory and Measurements,” in Proc. 2000 Mil. Sens. Symp. Spec. Gr. Passiv. Sensors, vol. 1, 2002, pp. 169–181.
[177] K. Caillault, S. Fauqueux, C. Bourlier, and P. Simoneau, “Infrared multiscale sea surface modeling,” in Proc SPIE 6360, C. R. Bostater, Jr., X. Neyt, S. P. Mertikas, and M. Velez-Reyes,´ Eds., Sep. 2006, pp. 636 006–636 006–11.
[178] J. R. Maxwell, J. Beard, S. Weiner, D. Ladd, and S. Lass, “Bidirectional Reflectance Model Validation and Utilization,” Air Force Avianics Laboratory, AFAL-TR-73-303, Tech. Rep., 1973.
[179] K. E. Torrance and E. M. Sparrow, “Theory for Off-Specular Reflection From Roughened Surfaces,” J. Opt. Soc. Am., vol. 57, no. 9, p. 1105, Sep. 1967.
[180] R. L. Cook and K. E. Torrance, “A Reflectance Model for Computer Graphics,” ACM Trans. Graph., vol. 1, no. 1, pp. 7–24, Jan. 1982.
[181] W. C. Snyder and Z. Wan, “BRDF models to predict spectral reflectance and emissivity in the thermal infrared,” IEEE Trans. Geosci. Remote Sens., vol. 36, no. 1, pp. 214–225, 1998.
[182] J. Krc,ˇ M. Zeman, O. Kluth, F. Smole, and M. Topic,ˇ “Effect of surface roughness of ZnO:Al films on light scattering in hydrogenated amorphous silicon solar cells,” Thin Solid Films, vol. 426, no. 1-2, pp. 296–304, Feb. 2003.
[183] J. Naranen, S. Kaasalainen, J. Peltoniemi, S. Heikkila, M. Granvik, and V. Saarinen, “Laboratory photometry of planetary regolith analogs. II. Surface roughness and extremes of packing density,” Astron. Astrophys., vol. 426, no. 3, pp. 1103–1109, Nov. 2004.
[184] Y. Shkuratov, A. Ovcharenko, and E. Zubko, “The Opposition Effect and Negative Polarization of Structural Analogs for Planetary Regoliths,” Icarus, vol. 159, no. 2, pp. 396–416, 2002.
[185] J. D. Suter, B. Bernacki, and M. C. Phillips, “Spectral and angular dependence of mid-infrared diffuse scattering from explosives residues for standoff detection using external cavity quantum cascade lasers,” Appl. Phys. B, vol. 108, no. 4, pp. 965–974, 2012.
[186] S. Sandmeier and K. Itten, “A field goniometer system (FIGOS) for acquisition of hyperspectral BRDF data,” IEEE Trans. Geosci. Remote Sens., vol. 37, no. 2, pp. 978–986, Mar. 1999.
[187] E. Puttonen, J. Suomalainen, T. Hakala, and J. Peltoniemi, “Measurement of reflectance properties of asphalt surfaces and their usability as reference targets for aerial photos,” IEEE Trans. Geosci. Remote Sens., vol. 47, no. 7, pp. 2330–2339, 2009.
[188] C. M. Bachmann, W. Philpot, A. Abelev, and D. Korwan, “Phase angle dependence of sand density observable in hyperspectral reflectance,” Remote Sens. Environ., vol. 150, pp. 53–65, Jul. 2014.
[189] T. H. Painter, “Measurements of the hemispherical-directional reflectance of snow at fine spectral and angular resolution,” J. Geophys. Res., vol. 109, no. D18, p. D18115, 2004.
[190] C. J. Deloye, M. S. West, and J. M. Grossmann, “Changes in apparent emissivity as a function of viewing geometry,” in Proc SPIE 8040, G. C. Gilbreath and C. T. Hawley, Eds., May 2011, pp. 80 400J–80 400J–12.
[191] N. A. Macleod, F. Molero, and D. Weidmann, “Broadband standoff detection of large molecules by mid-infrared active coherent laser spectrometry,” Opt. Express, vol. 23, no. 2, p. 912, 2015.
[192] C. A. Ortega-Zuniga,˜ N. Y. Galan-Freyle,´ J. R. Castro-Suarez, J. Aparicio-Bolano,˜ L. C. Pacheco-Londono,˜ and S. P. Hernandez-Rivera,´ “Dependence of detection limits on angular alignment, substrate type and surface concentration in active mode standoff IR,” in Proc. SPIE, vol. 8734, 2013, p. 87340R.
45 [193] A. Banas, K. Banas, M. Bahou, H. Moser, L. Wen, P. Yang, Z. Li, M. Cholewa, S. Lim, and C. Lim, “Post-blast detection of traces of explosives by means of Fourier transform infrared spectroscopy,” Vib. Spectrosc., vol. 51, no. 2, pp. 168–176, Nov. 2009.
[194] B. E. Bernacki and N. Ho,ˆ “Differential spectroscopic imaging of particulate explosives residue,” in Proc. SPIE 6945, C. S. Halvorson, D. Lehrfeld, and T. T. Saito, Eds., Apr. 2008, pp. 694 517–694 517–8.
[195] X. Liu, C. W. Van Neste, M. Gupta, Y. Y. Tsui, S. Kim, and T. Thundat, “Standoff reflectionabsorption spectra of surface adsorbed explosives measured with pulsed quantum cascade lasers,” Sensors Actuators B Chem., vol. 191, pp. 450–456, Feb. 2014.
[196] D. T. Reid, Z. Zhang, and C. R. Howle, “Active FTIR-based standoff detection in the 3-4 micron region using broadband femtosecond optical parametric oscillators,” in Proc. SPIE, vol. 9073, 2014, p. 907302.
[197] F. Fuchs, S. Hugger, M. Kinzer, R. Aidam, W. Bronner, R. Losch, Q. Yang, K. Degreif, and F. Schnurer, “Imaging standoff detection of explosives using widely tunable midinfrared quantum cascade lasers,” Opt. Eng., vol. 49, no. 11, p. 111127, 2010.
[198] P. H. Berning, “Theory and Calculations of Optical Thin Films,” in Phys. Thin Film., G. Haas, Ed. Academic Press, 1963, pp. 69–121.
46