Ultrafast 2D-IR spectroscopy has proved to be a powerful analytical tool for the detection and differentiation of Bacillus spores as dry films on surfaces. Here, we expand on these findings by employing 2D-IR spectroscopy to study spores from B. atrophaeus (BG) in aqueous solution. Specific vibrational modes attributable to the calcium dipicolinate trihydrate biomarker for spore formation were observed alongside distinctive off-diagonal spectral features that can be used to differentiate spores from different Bacillus species, indicating that 2D-IR has potential for use as a sensing platform with both solid and liquid phase samples. The ability of 2D-IR to enhance the protein amide I band relative to the overlapping water bending vibration was exploited to compare the nature of the protein component of spores to that of solution phase protein molecules. The vibrational lifetime for the amide I band of the BG spore in H2O was 1.4 ± 0.1 ps, longer than those reported for the proteins in H2O solution. The nature of a band at 1710 cm-1 was also investigated. Collectively these results show the potential advantages of 2D-IR spectroscopy, with successful detection and classification of spores under different conditions being based on detailed molecular understanding of the spore state.
A standoff biothreat detection and identification system for scanning large areas was designed, built and tested. The sensor is based on two wavelength ultraviolet light induced fluorescence (UVLIF) measured from a distance. The concept calls for multiple sensor modalities, fused to give the required overall performance. It makes use of multiple cameras, ambient light reflectance, high optical power and wavelength modulated UV LED illumination and synchronized fluorescence detection. A two-step operational mode is described along with results from independent demonstrations for each step. The first step is screening of the scene to recognize the surfaces that maximize the chances of biothreat detection and classification. This step used computer vision and artificial intelligence (semantic segmentation) for automation. The material constituting the surface is identified from color images. A second monochrome camera gives total “fluorescence” images excited with an intensity modulated 368nm UV illuminator. The second demonstration is scanning of slides (the “scene” in this case) from 1.2m away, threat detection (the spots on the slides) and classification via active multispectral fluorescence imaging at two different excitation wavelengths (280 and 368nm) and ambient light reflectance at up to 0.5m2/min. It is primarily the surface characteristics that drive the difficulty of the detection and classification of biological warfare agents (BWAs) on surfaces, along with the amount of BWA present on the surface. This presentation details the results obtained, the lessons learned and the envisioned way ahead.
A stand-off photothermal sensor platform has been developed which combines two laser technologies: an external cavity Quantum Cascade Laser (EC-QCL), and a near-infrared laser Doppler vibrometer (NIR-LDV). The former is used as a 'pump' to induce vibrations/acoustic waves in the sample, whereas the latter is used to 'probe' these photothermal (PT) effects as the pump wavelength is varied; yielding spectral information on the target analyte. The EC-QCL uses an acousto-optic deflector (AOD) to obtain single-mode mid-infrared light of high output power with up to 1.6 µm of wavelength tuning. Using this AO based approach allows ultra-fast scanning across the full spectral bandwidth of the QCL gain chip at MHz rates, thus facilitating high speed identification of hazards. Initial validation of this pump-probe platform is demonstrated for the detection of 1,3-dinitrobenzene (DNB) and nitrobenzene (NB) on an aluminium substrate at a distance of several metres.
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