Single-Shot Standoff Hyperspectral Raman Imaging of a Chemical Warfare Agent Simulant

Abstract

We demonstrate single-shot standoff hyperspectral Raman imaging of liquid diisopropyl methylphosphonate at a standoff distance of 1 m using two different techniques: multi-bandpass filter imaging (MBFI) and fiber-bundle imaging spectroscopy (FBIS). We find that MBFI has good spatial resolution, but poor spectral resolution, due to the limitations of commercially available bandpass filters. On the other hand, we find FBIS to have excellent spectral resolution, but limited spatial resolution due to the relatively small number of fibers in a bundle. For FBIS, we also determine, for a 1 m standoff distance, a minimum pump fluence of 10 mJ/cm² to obtain good single-shot spectra.

Keywords

Raman spectroscopy Raman imaging remote sensing standoff spectroscopy

Introduction

The prompt defeat of chemical warfare agents (CWAs) using explosives is expected to lead to the puncturing of containers and subsequent formation of aerosolized material and mixtures of liquid with the environment. In theory, the CWA would then be neutralized via pyrolysis or combustion¹ from the high temperatures inside of the fireball. However, given the complexity of such events, ensuring complete destruction is not a given, and further characterizations are needed to confirm the successful defeat. One aspect to be considered is the ejection of liquid agents from punctured containers. The few diagnostics that are available to study such events have determined only general spray characteristics (e.g., spray velocity and spray angle) via high-speed video. Additional information is needed to improve and validate computational fluid dynamics and fast-running models for various scenarios of container types and impact conditions. This need requires the development of advanced diagnostics to temporally and spatially determine properties in a rapidly changing extreme environment.

The most promising technique for such characterization is standoff Raman spectroscopy,² which can also be extended using imaging for standoff hyperspectral Raman imaging (SHRI). Standoff Raman spectroscopy is a widely used technique in which a laser remotely probes the Raman spectrum of a target area with the scattered light collected by a telescopic lens. Typically, this technique uses the basic Raman detection technique (i.e., pump laser scatters off a sample and the light is collected into a notch-filtered spectrometer to produce a spectrum), although more advanced techniques have been utilized including heterodyne detection,^3–5 random Raman lasing,⁶ coherent Raman spectroscopy,^7–9 and hyperspectral Raman imaging.^10–13 Regardless of the detection technique, the goal of all these approaches is almost always to identify hazardous materials in a target area such as explosives,^9,12–18 CWAs and their simulates,^3,14,16,19 narcotics and their precursors,²⁰ atmospheric pollutants,^8,21 bacterial spores,⁷ and other various hazardous organic and inorganic compounds.^6,22,23 Additionally, it has been used in planetary exploration^24,25 to identify compounds on extraterrestrial surfaces.

In each of these applications, i.e., hazardous material identification and planetary exploration, the targets are relatively time-invariant and spectral/imaging acquisitions of several seconds or longer are not problematic. However, for our proposed application characterizing chemical reactions with SHRI during an explosion, these time scales are far too long as the chemical reactions of interest typically occur on the sub-millisecond time scale.²⁶ To characterize these reactions we need to perform single-shot SHRI (S³HRI) over multiple pulses in a “short”’ timescale to obtain spatially resolved Raman spectra as a function of time during a reaction. At present, there is only one report on single-shot non-imaging Raman spectroscopy by Misra et al.,²³ who performed single-shot Raman spectral measurements of various chemicals at 120 m, and to our knowledge there are no reports on S³HRI.

To address the need for a technique with both spatial and spectral resolution we have developed two proof-of-concept approaches to achieve S³HRI. The first technique, which we call multi-bandpass imaging (MBI), utilizes multiple intensified charge-coupled devices (ICCDs), image-splitting optics, and bandpass filters to obtain both spatial and spectral resolution. The second technique, fiber-bundle imaging spectroscopy (FBIS), maps an image from a telescopic lens onto a round-to-linear fiber bundle which is imaged by a spectrometer.

In this report, we demonstrate both techniques for S³HRI of liquid diisopropyl methylphosphonate (DIMP) at a standoff distance of 1 m. We characterize both techniques’ spatial and spectral resolution as well as consider the effect of monochromator design and pump fluence on the performance of the FBIS system.

Multi-Bandpass Imaging

The first S³HRI technique we investigated is MBI. The MBI instrument (shown schematically in Figure 1) consists of a telescopic lens connected to a Cairn Research Split Cam, two Princeton Instruments PI Max 4 ICCDs (1024i, SB Phosphor), and three bandpass filters (Thorlabs FBH550-10, FBH560-10, and FBH580-10). The split cam first splits an incoming image into two legs which are then further split to produce two images on a single charge-coupled device (CCD), with each image having its own bandpass filter. In this way, the split cam is able to image four separate spectral bands simultaneously. For our measurements, we used three bandpass filters and one unfiltered channel for spatial alignment. Note that for both the MBI and FBIS measurements, we used a frequency-doubled Nd:YAG laser (Quantel Q-smart, 10 Hz, 6 ns, 532 nm, linewidth $< 1.4$ cm⁻¹) for excitation. Also, the DIMP sample used in both sets of experiments consisted of a standard 1 cm quartz cuvette filled with DIMP.

The three bandpass filters were chosen to correspond to different peaks in the Raman spectra of DIMP, with Figure 2 showing the Raman spectra of DIMP (measured using a standard Raman spectroscopy system) as well as the transmission curves of the chosen bandpass filters. Note that the bandpass filters were off-the-shelf filters with non-optimized centers and a bandwidth of 10 nm (347 cm⁻¹). Ideally, filters would be used with centers corresponding to specific peaks and having narrow linewidths. Unfortunately, such custom filters are currently uneconomical to obtain.

With the Raman spectra of DIMP and the bandpass filter transmission curves presented, we next consider an example set of bandpass-filtered images taken during a typical experiment, with Figure 3 showing the images. These images were obtained from the MBI system for a single laser pulse incident on the cuvette filled with DIMP with an average fluence of 90 mJ/cm². From Figure 3, we find that the largest intensity is observed for the filter centered at 616 cm⁻¹, which includes the most intense Raman peak of DIMP (714 cm⁻¹). The next brightest image is for the 940 cm⁻¹ filter, which corresponds to a number of less intense peaks, and the final image corresponds to 1556 cm⁻¹ filter for which we do not observe any noticeable intensity.

Based on the images in Figure 3, it is evident that the MBI technique can obtain good spatial resolution for S³HRI of DIMP, but it has very poor spectral resolution. In theory, this spectral resolution can be improved by using custom bandpass filters, but this would be prohibitively expensive. Additionally, using bandpass filters will make it difficult to remove any background or contaminate signals that may be present. We therefore conclude that while the MBI technique has a good spatial resolution, it is unlikely to obtain the spectral resolution needed for probing chemical reactions of CWA simulants inside of explosive fireballs.

For instance, the CWA simulant in this study, DIMP, is known to thermally decompose into a number of products including propene, methylphosphonic acid (MPA), and isopropyl methylphosphate (IMP).²⁶ While DIMP and each of these products has multiple Raman peaks, their most intense peaks ( $< 2000$ cm⁻¹) are 718 cm⁻¹for DIMP, 774 cm⁻¹for MPA,²⁷ 782 cm⁻¹for IMP,²⁷ and 920 cm⁻¹for propene.²⁸ Therefore, if we want to probe signal from each of these materials it is ideal to have bandpass filters that can resolve each of these peaks. Assuming no overlap between peaks (which is a poor assumption), the narrowest filter would need to have an 8 cm⁻¹(0.24 nm) bandwidth to differentiate MPA from IMP, while a 33 cm⁻¹(1 nm) bandwidth would be sufficient for the other materials. However, in reality, there will be an overlap in peaks, which cannot be accounted for by bandpass filters alone. To truly resolve these different materials, we need to take Raman spectra.

Fiber-Bundle Imaging Spectroscopy

Given the difficulties of bandpass-filtered imaging to obtain a good spectral resolution, we next tested the FBIS technique for S³HRI. FBIS is a technique that images the output of a telescopic lens onto a 2D fiber bundle that is then converted into a linear array for dispersion by an imaging monochromator. This technique treats each fiber in the bundle as an imaging “pixel”, which is spectrally resolved by the monochromator.^29–37 Note that converting the linear data back into a 2D image requires a mapped fiber bundle in which the relationship between the 2D bundle and linear array is known. Unfortunately, the fiber bundles available for this study were not mapped and therefore we cannot currently produce a clear image. However, these fiber bundles work for a proof-of-concept device. We plan to utilize a mapped fiber bundle in a future effort.

The general structure of the FBIS setup is shown in Figure 4. It consists of the same sampling hardware as the MBI (with the telescopic lens now coupled into a fiber bundle), a monochromator, and a camera. The fiber bundle used for these experiments consisted of 19 200 $μ$ m fibers in a round-to-linear geometry and was purchased from Princeton Instruments. During our experiments, we used two different cameras and monochromators, with the cameras being a Princeton Instruments PI Max 4 ICCD (1024i, SB Phosphor) and Blaze CCD (400-B), and the monochromators being an Acton Spectrapro 2500i (1200 g/mm, 500 nm blaze, 200 $μ$ m slit, 9.3 cm⁻¹ resolution) and an Isoplane 320 (1200 g/mm, 500 nm blaze, 200 $μ$ m slit, 14 cm⁻¹resolution). Note that the PI Max 4 has a pixel size of 12.4 $μ$ m and the Blaze has a pixel size of 20 $μ$ m.

We initially started with the PI Max 4 camera connected to the Spectrapro 2500i monochromator, but found that the combination could not properly resolve the fiber bundle, with adjacent fibers smearing together (see Figure 5a for an example fiber bundle image). After discussions with Princeton Instruments, we learned that this is a known limitation of the Czerny–Turner design and that their IsoPlane monochromators (which use a Schmidt–Czerny–Turner³⁸) design provide superior spatial resolution. We therefore next tested the PI Max 4 with an IsoPlane monochromator and found improved resolution (see Figure 5b for an example fiber bundle image). However, there is still some blurring between channels due to the design of an ICCD camera. Inside an ICCD, there is a phosphorescent screen that is coupled by a fiber bundle to a CCD. Due to this design, there is some cross-talk between adjacent pixels which limits the resolution of the detector.

Given the challenges associated with the PI Max 4 we next switched to a Blaze CCD camera, which does not have an intensifier, and produced superior imaging resolution (see Figure 5c for an example fiber bundle image). As a final comparison of the three combinations, we took a line profile across the fiber bundle images, with the resulting profiles shown in Figure 5d. From Figure 5d, we find that the Blaze/Isoplane combination produces high contrast peaks, while the contrast is significantly reduced for the PI Max 4/Isoplane combination, and is all but absent for the PI Max 4/Spectrapro combination. This demonstrates that distinct fiber channels are resolved for the Blaze/IsoPlane combination, while the PI Max 4 combinations have blending between channels, which limits their spatial resolution.

Based on the results in Figure 5 one would assume that the Blaze camera is the superior camera for FBIS, which is the case in a lab setting. However, in a real-world scenario where there is unavoidable background light, the Blaze camera’s minimum exposure time will allow a significant amount of background light to interfere with the Raman signal from a single-shot spectrum. On the other hand, an ICCD gated exposure can be used for capturing data only during the laser pulse (e.g., an exposure time of $\sim$ 6 ns), which will minimize background. Therefore in the remainder of this paper, we will discuss both cameras with the recognition that in real-world applications, an ICCD is needed. However, this implementation will either require different engineering of the ICCD or a fiber bundle with greater spacing between fibers to minimize blurring. Note that for the measurements in the remainder of this paper, we set the Blaze exposure to 1 ms and the ICCD’s gate width to 50 ns (which covers the full 6 ns laser pulse).

With the imaging resolutions of the different camera/monochromator pairs compared we next consider sample data obtained from single-shot measurements of liquid DIMP. Figure 6 shows an example fiber spectral images for a fluence of 109 mJ/cm² for both the PI Max 4 (Figure 6a) and Blaze (Figure 6b) cameras using the Isoplane monochromator. From Figure 6b, we see a significant Raman signal at five distinct fiber channels for the Blaze camera, while the PI Max 4 image in Figure 6a does not show distinct channels with the intensity smeared out over adjacent pixels.

Using the spectral images from Figure 6, we next extract the spectra for the five brightest fibers by taking line profiles across the images with a vertical integration width of $Δ y = 0.6 mm$ for the PI Max 4 camera and $Δ y = 0.2 mm$ (the width of a single fiber) for the Blaze camera. The larger integration width for the PI Max 4 was used to account for the smearing between channels discussed above. Figures 7a and 7b show the resulting spectra for the PI Max 4 and Blaze camera, respectively. From Figure 7, we observe the expected Raman spectra for DIMP from each fiber with four of the fibers having similar intensity, while the fiber at 3.54 mm is the brightest. Most likely this fiber is mapped fully into the pump spot, while the other fibers include both pumped and and unpumped regions. We can estimate this arrangement using the pump spot size and imaging properties of the telescopic lens to show the overlap of the pump spot and the mapped fiber bundle, which is shown in Figure 8 with each 200 $μ$ m fiber being mapped to a 3 mm diameter region in the object plane. Based on this estimated mapping, it is clear that one fiber will be significantly brighter than the other four, which have similar intensities.

With the spatial resolution of the FBIS demonstrated, we next consider its spectral resolution, which is directly related to the properties of the imaging monochromator and the gratings used. For these experiments, we used a 200 $μ$ m slit width (to collect the full fiber and a 1200 g/mm grating (500 nm blaze) for the Blaze camera and 600 g/mm grating (500 nm blaze) for the PI Max 4. These settings resulted in the Blaze-based FBIS system having a spectral resolution of 14.4 cm⁻¹(0.44 nm) and a spectral range of 150–2000 cm⁻¹ and the PI Max 4-based system having a spectral resolution of 29.7 cm⁻¹ and a spectral range of 100–2000 cm⁻¹. Note that we chose these settings to collect all the light from the fibers and to take single-shot measurements that would cover the 200–2000 cm⁻¹ range. If better resolution is needed (such as to differentiate between MPA and IMP), a higher resolution grating and narrower slit width can be used. For instance, a 25 $μ$ m slit width and 1800 g/mm grating will give a resolution of 1.27 cm⁻¹, which is approximately the linewidth of the laser used ( $< 1.4$ cm⁻¹). Note that narrower linewidth frequency-doubled Nd:YAG lasers are available with linewidths on the order of 0.01 cm⁻¹.

Having demonstrated the FBIS capability to spatially and spectrally resolve liquid DIMP’s Raman spectra (using a pump fluence of 109 mJ/cm²), we next characterized the Raman spectra’s dependence on pump fluence to identify a “minimum” fluence needed to obtain an adequate spectrum. Figure 9 shows the spectra measured at different pump fluences for the brightest fiber in the bundle (for both cameras) with the insets in Figure 9 showing the 718 cm⁻¹ peak intensity as a function of pump fluence with a linear fit. From Figure 9, we find that—for both the PI Max 4 and Blaze cameras—we are able to obtain reasonable single-shot spectra for fluences as low as 10 mJ/cm² for a 1 m standoff distance. For our current configuration, this corresponds to a pulse energy of $\approx 2$ mJ. Note that the minimum pulse energy required to obtain a good signal will depend on the standoff distance,³⁹ which we intend to explore under a future effort.

Conclusion

In this study, we have demonstrated and evaluated two different S³HRI techniques: MBFI (MBI) and FBIS. We find that MBI has good spatial resolution, but poor spectral resolution, while FBIS has good spectral resolution, but limited spatial resolution due to the number of fibers available in a fiber bundle. Based on these results, we conclude that FBIS is the most promising approach due to the superior spectral resolution.

Building off of these proof-of-concept lab-scale results, we are planning future field-scale experiments using a mapped fiber bundle with a square 7 $\times$ 7 array of 50 $μ$ m diameter fibers, telescopic lens, and standoff distances up to 100 m. The number and size of fibers are chosen such that the linear array side of the bundle will have an inter-fiber spacing of 150 $μ$ m between fibers. This will allow us to resolve individual fibers using the PI Max 4 ICCD. We will test the functionality of the FBIS system at different standoff distances to characterize the minimum pump fluence needed as well as the spatial resolution of the fiber array at different standoff distances. Additionally, we plan on investigating the possibility of using deep-ultaviolet (DUV) excitation for these measurements as it has been previously shown that using a wavelength near 250 nm increases the signal of DIMP’s Raman spectrum by a factor of 34.5 $\times$ compared to green light.⁴⁰ This improvement is both due to the Raman intensity depending on $λ^{- 4}$ and resonance effects as DIMP absorbs in the DUV.⁴¹ While using DUV is beneficial at first glance, there are experimental factors to consider such as the spectral response of the fiber bundle, telescopic lens, monochromator, and detector, as well as possible absorption by air at standoff distances.

Supplemental Material

sj-docx-1-asp-10.1177_00037028241258105 - Supplemental material for Single-Shot Standoff Hyperspectral Raman Imaging of a Chemical Warfare Agent Simulant

Supplemental material, sj-docx-1-asp-10.1177_00037028241258105 for Single-Shot Standoff Hyperspectral Raman Imaging of a Chemical Warfare Agent Simulant by Benjamin R Anderson and Hergen Eilers in Applied Spectroscopy

Footnotes

Acknowledgments

We would like to thank Natalie Gese for help with sample preparation. Additionally, we would like to thank Princeton Instruments (and in particular Colin Ingram) for insightful discussions about the imaging capabilities of the two monochromators.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

ORCID iD

Benjamin R. Anderson

Data Availability Statement

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The project or effort depicted was or is sponsored by the Department of the Defense, Defense Threat Reduction Agency under the Materials Science in Extreme Environments University Research Alliance, HDTRA1-20-2-0001. The content of the information does not necessarily reflect the position or the policy of the federal government, and no official endorsement should be inferred.

Supplemental Material

All supplemental material mentioned in the text is available in the online version of the journal.

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