• Textile Coloration and Finishing
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• v.6 no.2
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• pp.17-23
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• 1994

Carboxylic acid group gradient surface where the density of carboxylic acid groups changes gradually along the sample length was prepared. Carboxylic acid group gradient surface was produced by the treatment of low density polyethylene sheet using a corona with gradually increasing power, followed by the grad polymerization of acrylic acid. The prepared gradient surface was characterized by the measurement of water contact angle, Fourier-transform infrared spectroscopy in the attenuated total reflectance mode, and electron spectroscopy for chemical analysis.

• Proceedings of the PSK Conference
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• 2002.10a
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• pp.409.1-409.1
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• 2002

For the development of a biocompatible nano-scale drug carrier. hydrophilic polysaccharide pullulan was hydrophobized by the conjugation with fatty acid. The synthesized polymers were characterized by the measurements of fourier transform infrared (FT -IR) spectroscopy and 1H -nuclear magnetic resonance (NMR) spectroscopy. In aqueous solution. hydrophobically modified puliulan was self-assembled and structured into the core-shell type nanoparticles. (omitted)

• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.675-696
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• 2023

Terpenoids, also referred to as terpenes, are a large family of naturally occurring chemical compounds present in the essential oils extracted from medicinal plants. In this study, a nondestructive methodology was created by combining ATR-FT-IR (attenuated total reflectance-Fourier transform infrared), and Raman spectroscopy for the terpenoids assessment in medicinal plants essential oils from ten different geographical locations. Partial least squares regression (PLSR) and support vector regression (SVR) were used as machine learning methodologies. However, a deep learning based model called as one-dimensional convolutional neural network (1D CNN) were also developed for models comparison. With a correlation coefficient (R²) of 0.999 and a lowest RMSEP (root mean squared error of prediction) of 0.006% for the prediction datasets, the SVR model created for FT-IR spectral data outperformed both the PLSR and 1 D CNN models. On the other hand, for the classification of essential oils derived from plants collected from various geographical regions, the created SVM (support vector machine) classification model for Raman spectroscopic data obtained an overall classification accuracy of 0.997% which was superior than the FT-IR (0.986%) data. Based on the results we propose that FT-IR spectroscopy, when coupled with the SVR model, has a significant potential for the non-destructive identification of terpenoids in essential oils compared with destructive chemical analysis methods.

• Journal of Animal Science and Technology
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• v.64 no.3
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• pp.531-538
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• 2022

In Italy, buffalo mozzarella is a largely sold and consumed dairy product. The fraudulent adulteration of buffalo milk with cheaper and more available milk of other species is very frequent. In the present study, Fourier transform infrared spectroscopy (FTIR), in combination with multivariate analysis by partial least square (PLS) regression, was applied to quantitatively detect the adulteration of buffalo milk with cow milk by using a fully automatic equipment dedicated to the routine analysis of the milk composition. To enhance the heterogeneity, cow and buffalo bulk milk was collected for a period of over three years from different dairy farms. A total of 119 samples were used for the analysis to generate 17 different concentrations of buffalo-cow milk mixtures. This procedure was used to enhance variability and to properly randomize the trials. The obtained calibration model showed an R² ≥ 0.99 (R² cal. = 0.99861; root mean square error of cross-validation [RMSEC] = 2.04; R² val. = 0.99803; root mean square error of prediction [RMSEP] = 2.84; root mean square error of cross-validation [RMSECV] = 2.44) suggesting that this method could be successfully applied in the routine analysis of buffalo milk composition, providing rapid screening for possible adulteration with cow's milk at no additional cost.

• Journal of Sensor Science and Technology
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• v.31 no.4
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• pp.255-259
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• 2022

In this study, we fabricated ZnS substrates with excellent transmittance in the mid-infrared region (3-5 ㎛) using hot pressing instead of conventional chemical vapor deposition (CVD). Diamond-like carbon (DLC) was coated on either one or both sides of the ZnS substrates to improve their mechanical properties and transmittance efficiency. To reduce the reflectance and further improve transmittance in the mid-infrared region, anti-reflection (AR) coating was designed for DLC/ZnS /AR and AR/ ZnS /AR structures. The coating structure, microstructure, and optical properties of the AR-coated ZnS substrates were subsequently investigated by employing energy dispersive X-ray spectroscopy, scanning electron microscopy, and Fourier-transform infrared (FTIR) spectroscopy. The FTIR spectroscopy results demonstrated that, in the mid-infrared region, the average transmittance of the samples with AR coating on one and both sides increased by approximately 18% and 27%, respectively. Thus, AR coating improved the transmittance of the ZnS substrates.

• Journal of the Korean Ceramic Society
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• v.55 no.3
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• pp.230-238
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• 2018

Superparamagnetic iron oxide nanoparticles (SPIONs) have been prepared without using surfactants to assess their stability at different time intervals. The synthesized particles were characterized by X-ray diffraction, Fourier-transform infrared spectroscopy, ultraviolet-visible-near infrared spectroscopy, and energy dispersive spectroscopy. Field emission scanning electron microscopy and high-resolution transmission electron microscopy images of the samples were also investigated. The average particle size was measured to be 12.7 nm even in the polydispersed form. The magnetic and dielectric characteristics of the $Fe_3O_4$ nanoparticles have also been studied and discussed in detail.

• Atmosphere
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• v.19 no.4
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• pp.319-329
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• 2009

The intensive dust observation experiment has been performed at Korea Global Atmosphere Watch Center (KGAW) in Anmyeon, Korea during each spring season from 2007 to 2009. Downward and upward hyper-spectral spectrums over the dust condition were measured to understand the hyper-spectral properties of Asian dust using both ground-based Fourier Transform Infrared Spectroscopy (FT-IR) and space-borne AIRS/Aqua. To understand the impact of the Asian dust, a Line-by-Line radiative transfer model runs to calculate the high resolution infrared spectrum over the wave number range of $500-500cm^{-1}$. Furthermore, the radiosonde, a $PM_{10}$ Sampler, a Micro Pulse Lidar (MPL), and an Aerodynamic Particle Sizer (APS) are used to understand the vertical profile of temperature and humidity and the properties of Asian dust like concentration, altitude of dust layer, and size distribution. In this study, we found the Asian dust distributed from surface up to 3-4 km and volume concentration is increased at the size range between 2 and $8{\mu}m$ The observed dust spectrums are larger than the calculated clear sky spectrums by 15~60K for downward and lower by around 2~6K for upward in the wave number range of $800-1200cm^{-1}$. For the characteristics of the spectrum during the Asian dust, the downward spectrum is revealed a positive slope for $800-1000cm^{-1}$ region and negative slope over $1100-1200cm^{-1}$ region. In the upward spectrum, slopes are opposed to the downward one. It is inferred that the difference between measured and calculated spectrum is mostly due to the contribution of emission and/or absorption of the dust particles by the aerosol amount, size distribution, altitude, and composition.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1257-1257
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• 2001

Fourier transform near infrared (FT-NIR) spectroscopy was used as a rapid method to measure the $^{o}Brix$ content and to discriminate between different must samples in terms of their fee amino nitrogen (FAN) values. FT-NIR spectroscopy was also used as a rapid method to discriminate between Chardonnay wine samples in terms of the status of the male-lactic fermentation (MLF). This was done by monitoring the conversion of malic to lactic acid and thereby determining whether MLF has started, is underway or has been completed followed by classification of the samples. Furthermore, FT-NIR spectroscopy was applied as a rapid method to discriminate between table wine samples in terms of the ethyl carbamate (EC) content. EC in wine can pose a health threat and need to be monitored by determining the EC content in relation to the regulatory limits set by the authorities. For each of the above mentioned parameters, $QUANT+^{TM}$ methods were built and calibrations derived and it was found that a very strong correlation existed in the sample set for the FT-NIR spectroscopic predictions of $^{o}Brix$ (r = 0.99, SECV = 0.306), but the correlations for the FAN (r = 0.61, SECV = 272.1), malic acid (r = 0.58, SECV = 1.06), lactic acid (r = 0.51, SECV = 1.14) and EC predictions (r = 0.47, SECV = 3.67) were not as good. Soft Independent Modeling by Class Analogy (SIMCA) diagnostics and validation was applied as a sophisticated discrimination method. The must samples could be classified in terms of their FAN values when SIMCA was applied, obtaining results with recognition rates exceeding 80%. When SIMCA diagnostics and validation were applied to determine the progress of conversion of malic to lactic acid and the EC content, again results with recognition rates exceeding 80% were obtained. The evaluation of the applicability of FT-NIR spectroscopy measurement of FAN, $^{o}Brix$ values, malic acid, lactic acid and EC content in must and wine shows considerable promise. FT-NIR spectroscopy has the potential to reduce the analytical times considerably in a range of measurements commonly used during the wine making process. Where conventional FT-NIR calibrations are not effective, SIMCA methods can be used as a discriminative method for rapid classification of samples. SIMCA can replace expensive, time-consuming, quantitative analytical methods, if not completely, at least to some extent, because in many processes it is only needed to know whether a specific cut off point has been reach or not or whether a sample belongs to a certain class or not.

• Polymer(Korea)
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• v.36 no.3
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• pp.372-379
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• 2012

In this study, we treated silica nanoparticles with bis[3-(trimethoxysilyl)propyl]amine (BTMA) silane coupling agent to modify their surfaces. We investigated the effects of BTMA hydrolysis time, BTMA concentration and BTMA treatment time on the degree of silanization reaction of silica nanoparticles. We used Fourier transform infrared spectroscopy (FTIR), elemental analysis (EA) and solid state cross-polarization magic angle spinning (CP/MAS) nuclear magnetic resonance spectroscopy (NMR) to obtain quantitative data. We found the decrease of isolated Si-OH peak intensity at 3747 $cm^{-1}$ and the increase of $-CH_2 $stretching and bending peaks with increasing hydrolysis time, concentration and treatment time of BTMA. EA analysis results also supported this trend. We found a strong effect of BTMA concentration on the degree of silanization of the silica particles, but weak effects of the hydrolysis time and the treatment time.

• Journal of Biosystems Engineering
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• v.38 no.4
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• pp.312-317
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• 2013

Purpose: Conventional methods used to evaluate seeds viability are destructive, time consuming, and require the use of chemicals, which are not feasible to implement to process plant in seed industry. In this study, the effectiveness of Fourier transform near infrared (FT-NIR) spectroscopy to differentiate between viable and nonviable watermelon seeds was investigated. Methods: FT-NIR reflectance spectra of both viable and non-viable (aging) seeds were collected in the range of 4,000 - 10,000 $cm^{-1}$ (1,000 - 2,500 nm). To differentiate between viable and non-viable seeds, a multivariate classification model was developed with partial least square discrimination analysis (PLS-DA). Results: The calibration and validation set derived from the PLS-DA model classified viable and non-viable seeds with 100% accuracy. The beta coefficient of PLS-DA, which represented spectral difference between viable and non-viable seeds, showed that change in the chemical component of the seed membrane (such as lipids and proteins) might be responsible for the germination ability of the seeds. Conclusions: The results demonstrate the possibility of using FT-NIR spectroscopy to separate seeds based on viability, which could be used in the development of an online sorting technique.