33 research outputs found
Stand-off identification of aerosols using mid-infrared backscattering fourier-transform spectroscopy
Femtosecond-laser pumped CdSiP<sub>2</sub> optical parametric oscillator producing 100 MHz pulses centered at 6.2 μm
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
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
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
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
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 (Vo) formed upon pre‐irradiation of the substrate. In this work, the exceptional chemical contribution in PIERS allows for the evaluation of atomic Vo dynamics in metal oxide surfaces. This technique is applied to study the formation and healing rates of surface‐active Vo 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
Sensing of bacterial spores with 2D-IR spectroscopy
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