Standoff detection of bacterial spores by field deployable coherent Raman spectroscopy.

Vibrational spectroscopies offer great potential for standoff detection of chemical and biological warfare agents, avoiding contamination to the operator and equipment. Among them, particularly promising is Coherent anti-Stokes Raman scattering (CARS) spectroscopy, using synchronized pump/Stokes laser pulses to set up a vibrational coherence of target molecules at a laser focus, which is read by further interaction with a probe pulse, resulting in the emission of a coherent beam detectable at a distance. CARS has previously demonstrated the capability to detect bacterial spores based on the Raman spectrum of the characteristic molecule calcium dipicolinate (CaDPA); however, a complex and bulky laser technology, which is only suitable for a laboratory environment, was employed. Here we develop a broadband CARS setup based on a compact, industrial grade ytterbium laser system. We demonstrate high signal-to-noise ratio detection of Bacillus atrophaeus spores at a concentration of 105 cfu/mm2, at a standoff distance of 1 m, and an acquisition time of 1 s. Our system, which combines chemical specificity and sensitivity along with improved ruggedness and portability, paves the way to a new generation of instruments for real-world standoff detection of chemical and biological threats.

Computational analyses of the vibrational spectra of fentanyl, carfentanil and remifentanil.

The infrared (IR) spectra of fentanyl, carfentanil and remifentanil, and protonated salts, are computed using quantum chemistry methods. New experimental FTIR spectra are also reported and compared to the calculations. The accuracy of two density functional theory methods, B3LYP and M06-2X, are tested against higher level theories (MP2) and the experimental data. Gas phase IR spectra are calculated for both the neutral and protonated molecules in order to compare with the experimental data measured for various salts of fentanyl and its analogues. Key vibrational modes are selected and studied in detail using a vibrational mode locality calculation. The main contributing atomic movements in these vibrational modes are identified.

Differentiation of bacterial spores via 2D-IR spectroscopy.

Ultrafast 2D-IR spectroscopy is a powerful tool for understanding the spectroscopy and dynamics of biological molecules in the solution phase. A number of recent studies have begun to explore the utility of the information-rich 2D-IR spectra for analytical applications. Here, we report the application of ultrafast 2D-IR spectroscopy for the detection and classification of bacterial spores. 2D-IR spectra of Bacillus atrophaeus and Bacillus thuringiensis spores as dry films on CaF2 windows were obtained. The sporulated nature of the bacteria was confirmed using 2D-IR diagonal and off-diagonal peaks arising from the calcium dipicolinate CaDP·3H2O biomarker for sporulation. Distinctive peaks, in the protein amide I region of the spectrum were used to differentiate the two types of spore. The identified marker modes demonstrate the potential for the use of 2D-IR methods as a direct means of spore classification. We discuss these new results in perspective with the current state of analytical 2D-IR measurements, showing that the potential exists to apply 2D-IR spectroscopy to detect the spores on surfaces and in suspensions as well as in dry films. The results demonstrate how applying 2D-IR screening methodologies to spores would enable the creation of a library of spectra for classification purposes.

Applications of compressive sensing in spatial frequency domain imaging.

SIGNIFICANCE: Spatial frequency domain imaging (SFDI) is an imaging modality that projects spatially modulated light patterns to determine optical property maps for absorption and reduced scattering of biological tissue via a pixel-by-pixel data acquisition and analysis procedure. Compressive sensing (CS) is a signal processing methodology which aims to reproduce the original signal with a reduced number of measurements, addressing the pixel-wise nature of SFDI. These methodologies have been combined for complex heterogenous data in both the image detection and data analysis stage in a compressive sensing SFDI (cs-SFDI) approach, showing reduction in both the data acquisition and overall computational time. AIM: Application of CS in SFDI data acquisition and image reconstruction significantly improves data collection and image recovery time without loss of quantitative accuracy. APPROACH: cs-SFDI has been applied to an increased heterogenic sample from the AppSFDI data set (back of the hand), highlighting the increased number of CS measurements required as compared to simple phantoms to accurately obtain optical property maps. A novel application of CS to the parameter recovery stage of image analysis has also been developed and validated. RESULTS: Dimensionality reduction has been demonstrated using the increased heterogenic sample at both the acquisition and analysis stages. A data reduction of 30% for the cs-SFDI and up to 80% for the parameter recover was achieved as compared to traditional SFDI, while maintaining an error of <10 % for the recovered optical property maps. CONCLUSION: The application of data reduction through CS demonstrates additional capabilities for multi- and hyperspectral SFDI, providing advanced optical and physiological property maps.

Fiber laser system for standoff coherent Raman spectroscopy.

A fiber laser system for standoff detection of chemical and biological species by coherent anti-Stokes Raman scattering is presented. The system is based on an ytterbium fiber laser and a hollow-core photonic crystal fiber for generation of broadband pump/Stokes pulses. High-resolution Raman spectra encompassing the fingerprint region (600-1600cm-1) are obtained for toluene, and two simulants of chemical and biological warfare agents, specifically dimethyl methylphosphonate and sodium dipicolinate. The system is operated at standoff distances of 2 m and integration times of 8 ms. The fiber technology makes the approach suitable for implementation as a compact standoff detection and identification system.

Machine learning utilising spectral derivative data improves cellular health classification through hyperspectral infra-red spectroscopy.

The objective differentiation of facets of cellular metabolism is important for several clinical applications, including accurate definition of tumour boundaries and targeted wound debridement. To this end, spectral biomarkers to differentiate live and necrotic/apoptotic cells have been defined using in vitro methods. The delineation of different cellular states using spectroscopic methods is difficult due to the complex nature of these biological processes. Sophisticated, objective classification methods will therefore be important for such differentiation. In this study, spectral data from healthy/traumatised cell samples using hyperspectral imaging between 2500-3500 nm were collected using a portable prototype device. Machine learning algorithms, in the form of clustering, have been performed on a variety of pre-processing data types including 'raw' unprocessed, smoothed resampling, background subtracted and spectral derivative. The resulting clusters were utilised as a diagnostic tool for the assessment of cellular health and quantified using both sensitivity and specificity to compare the different analysis methods. The raw data exhibited differences for one of the three different trauma types applied, although unable to accurately cluster all the traumatised samples due to signal contamination from the chemical insult. The background subtracted and smoothed data sets reduced the accuracy further, due to the apparent removal of key spectral features which exhibit cellular health. However, the spectral derivative data-types significantly improved the accuracy of clustering compared to other data types, with both sensitivity and specificity for the background subtracted data set being >94% highlighting its utility to account for unknown signal contamination while maintaining important cellular spectral features.

Nonlinear pulse compression to 22 fs at 15.6 µJ by an all-solid-state multipass approach.

We demonstrate nonlinear compression of pulses at 1.03 µm and repetition rate of 200 kHz generated by a ytterbium fiber laser using two cascaded all-solid-state multipass cells. The pulse duration has been compressed from 460 to 22 fs, corresponding to a compression factor of ∼21. The compressed pulse energy is 15.6 µJ, corresponding to an average power of 3.1 W, and the overall transmission of the two compression stages is 76%. The output beam quality factor is M2 ∼1.2 and the excess intensity noise introduced by nonlinear broadening is below 0.05%. These results show that nonlinear pulse compression down to ultrashort durations can be achieved with an all-solid-state approach, at pulse energies much higher than previously reported, while preserving the spatial characteristics of the laser.

Dynamics of Photo-Induced Surface Oxygen Vacancies in Metal-Oxide Semiconductors Studied Under Ambient Conditions.

Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical technique commonly used in the detection of traces of organic molecules. The mechanism of SERS is of a dual nature, with Raman scattering enhancements due to a combination of electromagnetic (EM) and chemical contributions. In conventional SERS, the EM component is largely responsible for the enhancement, with the chemical contribution playing a less significant role. An alternative technique, called photo-induced enhanced Raman spectroscopy (PIERS) has been recently developed, using a photo-activated semiconductor substrate to give additional chemical enhancement of Raman bands over traditional SERS. This enhancement is assigned to surface oxygen vacancies (V o) formed upon pre-irradiation of the substrate. In this work, the exceptional chemical contribution in PIERS allows for the evaluation of atomic V o dynamics in metal oxide surfaces. This technique is applied to study the formation and healing rates of surface-active V o in archetypical metal-oxide semiconductors, namely, TiO2, WO3, and ZnO. Contrary to conventional analytical tools, PIERS provides intuitive and valuable information about surface stability of atomic defects at ambient pressure and under operando conditions, which has important implications in a wide range of applications including catalysis and energy storage materials.

Broadband Fourier-transform coherent Raman spectroscopy with an ytterbium fiber laser.

We demonstrate a Fourier transform (FT) coherent anti-Stokes Raman scattering (CARS) spectroscopy system based on fiber technology with ultra-broad spectral coverage and high-sensitivity. A femtosecond ytterbium fiber oscillator is amplified and spectrally broadened in a photonic crystal fiber to synthesize pulses with energy of 14 nJ at 1040 nm, that are compressed to durations below 20 fs. The resulting pulse train is coupled to a FT-CARS interferometer enabling measurement of high-quality CARS spectra with Raman shifts of ~3000 cm-1 and signal to noise ratio up to 240 and 690 with acetonitrile and polystyrene samples, respectively, for observation times of 160 µs; a detection limit of one part per thousand is demonstrated with a cyanide/water solution. The system has the potential to detect trace contaminants in water as well as other broadband high-sensitivity CARS spectroscopy applications.

Systematic spectral shifts in the mid-infrared spectroscopy of aerosols.

Infrared spectroscopy in the spectral fingerprint region from 6.5 to 20 µm has been applied for decades to identify vapor- and condensed-phase chemicals with high confidence. By employing a unique broadband laser operating from 7.2- to 11.5-µm we show that, in this region, wavelength-dependent Mie-scattering effects substantially modulate the underlying chemical absorption signature, undermining the ability of conventional infrared absorption spectroscopy to identify aerosolized liquids and solids. In the aerosol studied, Mie theory predicts that the positions of spectroscopic features will blue-shift by up to 200 nm, and this behavior is confirmed by experiment, illustrating the critical importance of considering Mie contributions to aerosol spectroscopy in the mid infrared. By examining the spectroscopy of light scattered from an aerosol of the chemical diethyl phthalate, we demonstrate excellent agreement with a Mie-scattering model informed by direct measurements of the particle-size-distribution and complex refractive index.

Fiber-format dual-comb coherent Raman spectrometer.

We demonstrate a fiber-format system for dual-comb coherent anti-Stokes Raman scattering spectroscopy. The system is based on two ytterbium fiber (Yb) femtosecond lasers at repetition frequencies of 94 MHz, a Yb amplifier, and a photonic crystal fiber for spectral broadening and generation of pulses with a central wavelength of 1040 nm and durations in the sub-20-fs regime. We observed Raman spectra of acetonitrile and ethyl acetate with spectral coverage from 100 to 1300 cm-1, resolution of 8 cm-1, and a signal-to-noise ratio of around 100, when averaging over 10 acquisitions. The design is suitable for implementing portable dual-comb coherent Raman spectrometers.

Stand-off identification of aerosols using mid-infrared backscattering Fourier-transform spectroscopy.

We show that it is possible to identify the chemical composition of an aerosol by using Fourier-transform spectroscopy of backscattered mid-infrared light at a range of 0.2 m. An ultrafast mid-infrared optical parametric oscillator provides the illumination source for the measurement across a wavelength range from 3.2-3.55 µm containing characteristic optical absorption features for two different chemicals. Normalized detection sensitivity below 10 ppm m-1 Hz-1/2 is obtained.

Active FTIR-based stand-off spectroscopy using a femtosecond optical parametric oscillator.

We presented the first demonstration of stand-off Fourier transform infrared (FTIR) spectroscopy using a broadband mid-infrared optical parametric oscillator, with spectral coverage over 2700-3200 cm⁻¹. For vapor-phase water and nitromethane (NM), stand-off spectra was recorded using a concrete target at from 1-m to 2-m range and showed good agreement with reference spectra, and in NM a normalized detection sensitivity of 15 ppm·m·Hz(-1/2) was obtained. Spectra from 50-µL droplets of liquid thiodiglycol were detected at a stand-off distance of 2 m from aluminum, concrete and painted metal surfaces. Our results imply that OPO-based active FTIR stand-off spectroscopy is a promising new technique for the detection of industrial pollutants and the identification of chemical agents, explosives or other hazardous materials.

Femtosecond-laser pumped CdSiP2 optical parametric oscillator producing 100 MHz pulses centered at 6.2 µm.

We report the first, to the best of our knowledge, femtosecond-laser-pumped optical parametric oscillator (OPO) based on the newly developed nonlinear crystal, CdSiP2. The OPO was synchronously pumped by a mode-locked Yb:KYW/Yb:fiber master-oscillator power amplifier, providing 1.053 µm pump pulses with durations of 130 fs at a repetition rate of 100 MHz. The 0.5-mm-thick CdSiP2 crystal was cut for a type-I noncritical interaction, providing a broad phase-matching bandwidth and ensuring excellent temporal overlap among the pump, signal, and idler pulses. The OPO generated signal pulses with a spectral coverage over 1260-1310 nm and mid-infrared idler pulses with a broad spectral coverage at 5.8-6.6 µm (6.2 THz). With a 2% output coupler (OC), the threshold pump power was 600 mW. At the maximum pump power of 1.6 W, 0.55 W was absorbed due to two-photon absorption and residual linear absorption in the CdSiP2 crystal, 0.75 W was transmitted, and 53 mW signal power was extracted through the OC. We estimate that the generated idler power was 24 mW.