Detection of hazardous chemical using dual-wavelength Raman spectroscopy in the ultraviolet region

Lee, Jae‐Hwan; Jeong, Young‐Su; Young-jin, Koh; Kim, Jongseon; Nam, Hyunwoo; Son, Hyungbin; Choi, Sunkyung

doi:10.1016/j.saa.2022.122061

Cited by 3 publications

(1 citation statement)

References 28 publications

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“…Standoff DUV Raman detection can be a valuable tool for forensic and homeland security, process analysis in industry, and other applications requiring quick non-contact sensing. [1][2][3][4][5][6][7] The ultraviolet (UV) resonance Raman effect enables detection of the enhanced chemical species at trace levels within complex environments. Due to high sensitivity and selectivity, a UV resonance Raman (UVRR) spectrometer scanning habitable environments with Raman and luminescence for organics and chemicals (SHERLOC) is utilized onboard the Perseverance Mars rover to search for signs of ancient life and to identify samples for return to Earth.…”

Section: Introductionmentioning

confidence: 99%

Standoff Deep Ultraviolet Raman Spectrometer for Trace Detection

Bykov,

Asher

2024

Appl Spectrosc

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We developed a state-of-the-art, high-sensitivity, low-stray-light standoff deep-ultraviolet (DUV) Raman spectrometer for the trace detection of resonance Raman-enhanced chemical species. As an excitation source for Raman measurements, we utilized our recently developed, second-generation, miniaturized, diode-pumped, solid-state neodymium-doped gadolinium orthovanadate (Nd:GdVO4) laser that generates quasi-continuous wave 228 nm light. This 228 nm excitation enhances the Raman intensities of vibrations of NOx groups in explosive molecules, aromatic groups in biological molecules, and various aromatic hydrocarbons. Our DUV Raman spectrograph utilizes a custom DUV f/8 Cassegrain telescope with an ∼200 mm diameter primary mirror, high-efficiency DUV transmission gratings, custom DUV mirrors, and a custom 228 nm Rayleigh rejection filter. We utilized our new standoff DUV Raman spectrometer to measure high signal-to-noise ratio spectra of ∼50 μg/cm2 drop-cast explosives: ammonium nitrate (AN), trinitrotoluene, pentaerythritol tetranitrate as well as aromatic biological molecules: lysozyme, tryptophan, tyrosine, deoxycytidine monophosphate, deoxyadenosine monophosphate at an ∼3 m distance within 10–30 s accumulation times. We roughly estimate the average ultraviolet resonance Raman (UVRR) detection limits for the relatively homogeneous drop-cast films of explosives and biological molecules to be ∼1 μg/cm2 when utilizing a continuous raster scanning that averages Raman signal over ∼1 cm2 sample area to avoid quick analyte depletion due to ultraviolet (UV) photolysis. We determined 3 m standoff UVRR detection limits for drop-cast AN films and identified factors impacting UVRR detection limits such as analyte photochemistry and analyte morphology. We found a detection limit of ∼0.5 μg/cm2 for drop-cast AN films on glass substrates when the Raman signal is averaged over ∼0.5 cm2 of sample surface using a continuous raster scan. For a step raster scan, when the probed sample area is limited to the laser spot size, the detection limit is approximately tenfold higher (∼5 μg/cm2) due to the impact of UV photochemistry.

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Section: Introductionmentioning

confidence: 99%

Standoff Deep Ultraviolet Raman Spectrometer for Trace Detection

Bykov,

Asher

2024

Appl Spectrosc

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Enhancing substance identification by Raman spectroscopy using deep neural convolutional networks with an attention mechanism

Xie,

Wang,

Chen

et al. 2024

Anal. Methods

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Generating Synthetic Raman Spectra of DMMP and 2-CEES by Mathematical Transforms and Deep Generative Models

Park,

Jeong,

Kim

2024

J. KIMS Technol

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To build an automated system detecting toxic chemicals from Raman spectra, we have to obtain sufficient data of toxic chemicals. However, it usually costs high to gather Raman spectra of toxic chemicals in diverse situations. Tackling this problem, we develop methods to generate synthetic Raman spectra of DMMP and 2-CEES without actual experiments. First, we propose certain mathematical transforms to augment few original Raman spectra. Then, we train deep generative models to generate more realistic and diverse data. Analyzing synthetic Raman spectra of toxic chemicals generated by our methods through visualization, we qualitatively verify that the data are sufficiently similar to original data and diverse. For conclusion, we obtain a synthetic dataset of DMMP and 2-CEES with the proposed algorithm.

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Detection of hazardous chemical using dual-wavelength Raman spectroscopy in the ultraviolet region

Cited by 3 publications

References 28 publications

Standoff Deep Ultraviolet Raman Spectrometer for Trace Detection

Standoff Deep Ultraviolet Raman Spectrometer for Trace Detection

Enhancing substance identification by Raman spectroscopy using deep neural convolutional networks with an attention mechanism

Generating Synthetic Raman Spectra of DMMP and 2-CEES by Mathematical Transforms and Deep Generative Models

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