• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.4
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• pp.374-381
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• 2021

Raman spectrometers are studied and developed for the military purposes because of their nondestructive inspection capability to capture unique spectral features induced by molecular structures of colorless and odorless chemical warfare agents(CWAs) in any phase. Raman spectrometers often suffer from random noise caused by their detector inherent noise, background signal, etc. Thus, reducing the random noise in a measured Raman spectrum can help detection algorithms to find spectral features of CWAs and effectively detect them. In this paper, we propose a denoising autoencoder for Raman spectra with a loss function for sample efficient learning using noisy dataset. We conduct experiments to compare its effect on the measured spectra and detection performance with several existing noise reduction algorithms. The experimental results show that the denoising autoencoder is the most effective noise reduction algorithm among existing noise reduction algorithms for Raman spectrum based standoff detection of CWAs.

• Analytical Science and Technology
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• v.6 no.2
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• pp.1071-1080
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• 1993

• Polymer Science and Technology
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• v.6 no.1
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• pp.53-63
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• 1995

• Bulletin of the Korean Chemical Society
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• v.19 no.3
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• pp.372-375
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• 1998

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.32-39
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• 2018

Raman spectra exhibit differences in intensity depending on the measuring equipment and environmental conditions even for the same material. This restricts the pattern recognition approach of Raman spectroscopy and is an issue that must be solved for the sake of its practical application, so as to enable the reusability of the Raman database and interoperability between Raman devices. To this end, previous studies assumed the existence of a transfer function between the measurement devices to obtain a direct spectral correction. However, this method cannot cope with other conditions that cause various intensity distortions. Therefore, we propose a classification method using linear intensity calibration which can deal with various measurement conditions more flexibly. In order to evaluate the performance of the proposed method, a Raman library containing 14033 chemical substances was used for identification. Ten kinds of chemical Raman spectra measured using three different Raman spectroscopes were used as the experimental data. The experimental results show that the proposed method achieves 100% discrimination performance against the intensity-distorted spectra and shows a high correlation score for the identified material, thus making it a useful tool for the identification of chemical substances.

• Korean Journal of Optics and Photonics
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• v.28 no.3
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• pp.116-121
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• 2017

In this paper, a Raman spectrometer is designed to detect chemicals contaminating the ground. The system is based on Raman spectroscopy, which is spectral analysis of scattered light from chemicals, induced by a laser. The system consists of a transmitting-optics module with a laser to induce Raman-scattered light from the sample, a receiving-optics module to collect the scattered light, and a spectrograph to separate the collected light into a wavelength spectrum. The telescope, a part of the receiving-optics module, is designed to produce a focal spot in the same position for variable measurement distances using the code V simulator, considering the distance change between the system and the road. The Raman spectra of 12 chemicals on a glass surface and on a concrete sample were measured. Intensity differences between the Raman spectra acquired on a glass surface and on a concrete sample were observed, but the characteristics of the spectra according to the chemicals on them were similar. Additionally, the Raman spectrum of PTFE (polytetrafluoroethylene) was measured at various distances. The measured and simulated optical throughputs were similar. In conclusion, it is confirmed that with this system the Raman spectrum can be measured, irrespective of the distance change.

• Korean Journal of Optics and Photonics
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• v.33 no.6
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• pp.331-337
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• 2022

Raman spectroscopy is an optical technique that can identify molecules in a label-free manner, and is therefore heavily investigated in various areas ranging from biomedical engineering to materials science. Probe-based Raman spectroscopy can perform minimally invasive chemical analysis, and thus has potential as a real-time diagnostic tool during surgery. In this study, Raman experimentation was calibrated by examining the Raman shifts with respect to the concentrations of chemical substances. Raman signal characteristics, targeted for normal mice and cerebral tissues of the 5xFAD dementia mutant model with accumulated amyloid beta plaques, were measured and analyzed to explore the possibility of diagnosis of Alzheimer's disease. The application to the diagnosis of dementia was cross-validated by measuring Raman signals of amyloid beta. The results suggest the potential of Raman spectroscopy as a diagnostic tool that may be useful in various areas of application.

• Journal of Photoscience
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• v.9 no.2
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• pp.521-523
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• 2002

5-aminolevulinic acid (ALA) has been used to stimulate endogenous protoporphyrin IX (PpIX) in tumor and then initiate PDT. Recently, ALA-Hexyl ester (He-ALA) was found much effective than ALA on producing PpIX in cancer cells. To clarify the transportation mechanism of ALA and He-ALA, the detection of them is the important step. ALA and its derivatives all don't emit fluorescence, so the Raman spectroscopy was used here for the direct detection of ALA and He-ALA. The results showed that ALA and He-ALA have the common strong Raman peaks at 2930, 2950 CM$\^$-1/, due to the CH$_2$ vibration. The peak 3050 CM$\^$-1/ appeared in ALA spectrum can be attributed to OH vibration, while the peaks of 2860, 2900 CM$\^$-1/ in He-ALA spectrum were assigned as the modes of CH$_3$. This Raman spectral characteristic is consistence with the structure difference of He-ALA and ALA. Thus, Raman spectroscopy provides a new way to detect and distinguish ALA and He-ALA, and could be explored further in biology system.

• Bulletin of the Korean Chemical Society
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• v.31 no.5
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• pp.1215-1218
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• 2010

We demonstrate the possible application of the sandwich type surface-enhanced Raman scattering (SERS) immunoassay using antigen-antibody binding for detection of prostate-specific antigen (PSA) in cancer cells. In this sandwich type of SERS immunoassay, to capture antigens onto the immobilized layer of antibodies on the gold substrate we prepared the monolayer of gold nanoparticles on the APTMS-derivatized surface of a glass slide by using the SAM technique. This sandwich type of SERS immunoassay in which antigens on the substrate specifically capture antibodies on a Raman reporter (DSNB coated gold nanoparticles with R6G) could successfully detect PSA at low levels. A strong SERS spectrum of Raman reporter was observed only with a substrate in which PSA is present.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.21 no.6
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• pp.493-498
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• 2008

This Paper describes the Raman scattering characteristics of polycrystalline (Poly) 3C-SiC thin films, in which they were deposited on AlN buffer layer by APCVD using hexamethyldisilane (MHDS) and carrier gases (Ar+$H_2$). When the Raman spectra of SiC films deposited on the AlN layer of before and after annealing were worked according to growth temperature, D and G bands of graphite were measured. It can be explained that poly 3C-SiC films admixe with nanoparticle graphite and its C/Si rate is higher than ($C/Si\;{\approx}\;3$) that of the conventional SiC, which has no D and G bands related to graphite. From the Raman shifts of 3C-SiC films deposited at $1180^{\circ}C$ on the AlN layer of after annealing, the biaxial stress of poly 3C-SiC films was obtained as 896 MPa.