• 한국진공학회:학술대회논문집
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• 한국진공학회 2012년도 제42회 동계 정기 학술대회 초록집
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• pp.566-566
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• 2012

그래핀(Graphene)은 모든 탄소 동소체의 기본구성 요소로 2 차원 결정구조를 가지며, 양자홀 효과(quantum Hall effect), 뛰어난 열 전도도, 고 탄성, 광학적 투과성 등과 같은 탁월한 물리적 성질을 보이는 물질이다. 이러한 그래핀의 우수한 특성은 전계 효과 트랜지스터(field effect transistor), 화학/바이오 센서, 투명 전극(transparent electrode) 등의 다양한 전자소자를 개발하는 응용 가능하다. 그 중, 그래핀 투명전극의 제조는 가장 응용가능성이 높은 분야이다. 현재 투명전극 물질로는 인듐-주석 산화물(indium tin oxide; ITO)가 널리 이용되고 있으나, 인듐의 고갈로 인한 공급부족 문제 및 고 생산비용, 휘어지지 않는 취성 등의 단점을 지니고 있다. 따라서, 우수한 광학적 투과성과 전기전도성을 지닌 그래핀이 ITO의 대체 물질로서 각광받고 있다.[1-5] 본 연구에서는 그래핀의 투명전도필름의 응용을 위해 면저항을 낮추기 위한 방법으로 화학적 도핑(doping)을 이용하였다. 그래핀은 구리(copper; Cu) 호일을 촉매로 사용하여 열 화학증착법(Thermal Chemical Vapor Deposition)을 이용하여 합성하였다. 합성된 그래핀은 PMMA(Poly(methyl methacrylate)) 전사법을 이용하여 산화실리콘(SiO2) 기판에 전사 후, 염화은(AgCl)과 클로로벤젠(C6H5Cl)으로 만든 콜로이드(colloid) 용액에 디핑(dipping)하여 그래핀에 은 입자를 도핑 하였다. 그 결과, 은 입자 도핑 농도에 따라 면저항이 감소하는 양상을 보였다. 제작된 그래핀 투명전도성 필름의 투과도는 자외선-가시광선-근적외선 분광법(UV-Vis-NIR spectroscopy)를 이용하여 측정하였고, 라만 분광법(Raman spectroscopy)을 통해 그래핀 필름의 질적 우수성과 성장 균일도를 조사하였다.

• Applied Biological Chemistry
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• 제41권2호
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• pp.153-159
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• 1998

국내산 후지 사과의 주요 내부 품질 요인인 당도, 수분 함량, 경도 및 산 함량을 근적외 분광분석법에 의해 동시에 신속, 정확하게 비파괴 측정할 수 있는지의 가능성을 조사하였다. 굴절당도계에 의한 당도, 동결 건조법에 의한 수분 함량, texture analyzer에 의한 경도 및 알칼리 적정법에 의해 얻어진 산 함량 데이터와 근적외 영역의 흡광도 데이터 사이에 각각 중회귀분석을 행한 결과, 당도, 수분 함량, 경도 및 산 함량의 측정 오차(SEP)는 각각 $0.50^{\circ}Brix,\;0.64%,\;0.14kg/cm^2$ 및 0.07%이었다. 이로서 근적외 분광 분석법을 응용하여 사과의 당도와 수분 함량은 비파괴적으로 신속, 정확하게 측정 가능함을 알 수 있었으나, 경도와 산 함량의 측정 정확도는 다소 낮은 편이었다.

• 농업과학연구
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• 제39권4호
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• pp.603-612
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• 2012

In this research, the feasibility of non-destructive measurement technique of pungency measurement was investigated for the red-pepper powders produced in different domestic areas in South Korea. The near-infrared absorption spectra in the range of 1100 nm~2300 nm was used to measure capsaicinoids content in red-pepper powders by using a NIR spectroscopy equipped with Acousto-optic tunable filters (AOTF). Fourth three different red-pepper powders from 14 different locations were collected and separated in three different particle size (below 0.425 mm, 0.425~0.71 mm, 0.71~1.4 mm) for the spectral measurements. The partial least square regression (PLSR) models to predict the capsaicinoids content depends on particle size were developed with the measured spectra. The determinant coefficients and standard errors of the developed models for the red-pepper powders of below 0.425 mm, 0.425~0.71 mm, and 0.71~1.4 mm were in the range of 0.859~0.887 and 12.90~12.99 mg/100 g, respectively. The PLS model with the pretreatment of Standard Normal Variate (SNV) for the red-pepper powders below 1.4 mm particle size showed the best performance with the determinant coefficient of 0.844 and the standard error of 14.63 mg/100 g.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1041-1041
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• 2001

Removal of variability in spectra data before the application of chemometric modeling will generally result in simpler (and presumably more robust) models. Particularly for sparsely sampled data, such as typically encountered in diode array instruments, the use of Savitzky-Golay (S-G) derivatives offers an effective method to remove effects of shifting baselines and sloping or curving apparent baselines often observed with scattering samples. The application of these convolution functions is equivalent to fitting a selected polynomial to a number of points in the spectrum, usually 5 to 25 points. The value of the polynomial evaluated at its mid-point, or its derivative, is taken as the (smoothed) spectrum or its derivative at the mid-point of the wavelength window. The process is continued for successive windows along the spectrum. The original paper, published in 1964 [1] presented these convolution functions as integers to be used as multipliers for the spectral values at equal intervals in the window, with a normalization integer to divide the sum of the products, to determine the result for each point. Steinier et al. [2] published corrections to errors in the original presentation [1], and a vector formulation for obtaining the coefficients. The actual selection of the degree of polynomial and number of points in the window determines whether closely situated bands and shoulders are resolved in the derivatives. Furthermore, the actual noise reduction in the derivatives may be estimated from the square root of the sums of the coefficients, divided by the NORM value. A simple technique to evaluate the actual convolution factors employed in the calculation by the software will be presented. It has been found that some software packages do not properly account for the sampling interval of the spectral data (Equation Ⅶ in [1]). While this is not a problem in the construction and implementation of chemometric models, it may be noticed in comparing models at differing spectral resolutions. Also, the effects on parameters of PLS models of choosing various polynomials and numbers of points in the window will be presented.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1265-1265
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• 2001

The organic materials included in excreta of livestock are important resources for organic manure and for improving soil quality, although there is still far from effective using. One reason for this is still unclearly standard of quality for evaluation of manure made from excreta of livestock. Therefore, the objective of this study is to develop rapid and accurate analytical method for analyzing organic compositions of manure made from excreta of livestock, and to establish quality evaluation method based on the compositions predicted by near infrared reflectance spectroscopy (NIRS). Sixteen samples of manure, each eight samples prepared from two treatments, were used in this study. The manure samples were prepared by mixing 560 kg feces of swine,60 kg sawdust with moisture content was adjusted to be 65%. The mixture was then keep under two kinds of shelter, black and clear sheets, as a treatment on the effect of sunlight. Samples were taken in every week (form week-0 to 7) during the process of manure making. Samples were analyzed to determine neutral detergent fiber (NDF), acid detergent fiber (ADF) and acid detergent lignin (ADL) by detergent methods, and organic cell wall (OCW) and fibrous content of low digestibility in OCW (Ob) by enzymatic methods. Biological oxygen demand (BOD) was analyzed by coulometric respirometer method. These compositions were carbohydrateds and lignin that were hardly digested. Spectra of samples were scanned by NIR instrument model 6500 (Pacific Scientific) and read over the range of wavelength between 400 and 2500nm. Calibration equations were developed using eight manure samples collected from black sheet shelter, while prediction was conducted to the other eight samples from clear sheet shelter. Accuracy of NTRS prediction was evaluated by correlation coefficients (r), standard error of prediction (SEP) and ration of standard deviation of reference data in prediction sample set to SEP (RPD). The r, SEP and RPD value of forage were 0.99, 0.69 and 7.6 for ADL, 0.96, 1.03 and 4.1 for NDF, 0.98, 0.60 and 4.9 for ADF, 0.92, 1.24 and 2.6 for Ob, and 0.91, 1.02 and 7.3 for BOD, respectively. The results indicated that NIRS could be used to measure the organic composition of forage used in manure samples.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1617-1617
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• 2001

It is well known now that near infrared spectroscopy (NIRS) is a fast, no destructive, and inexpensive analytical technique that could be used to classify, identify, and authenticate a wide range of foods and food items. Therefore, the main aims of this study were to provide a new insight into the authentication of five strawberry (Fragaria x ananassa) varieties and to correlate them with geographical zones and the propagating methods used. Three weeks plants of five different strawberry varieties (F. x ananassa Duch. cv Camarosa, Seascape, Chandler, F. Chiloensis, and F. Virginiana) were cultivated in vitro first and then transferred to pots with special soil, and grown in a greenhouse at CINVESTAV, all varieties were acquired from California (USA). After 18 months, ten leaves from each variety were collected. Transmission spectra from each leave were recorded over a range of 10, 000-4, 000 cm$-^{1}$, 32 scans of each strawberry leave were collected using a resolution of 4 cm$-^{1}$ with a Paragon IdentiCheck FT-NIR System Spectrometer. Triplicates of each strawberry leave were used. All spectra were analyzed using principal component analysis (PCA) and soft independent modeling class analogy (SIMCA). The optimum number of components to be used in the regression was automatically determined by the software. Camarosa was the only variety grown from the same shoot but propagated by a different method (direct or in vitro). Five different classes (varieties) or clusters were observed among samples, however, larger inter class distances were presented by the two wildtype samples (F. Chiloensis and F. Virginiana). Camarosa direct and Camarosa in vitro displayed a small overlapping region between them. On the other hand, Seascape variety presented the smallest rejection percentage among all varieties (more similarities with the rest of the samples). Therefore, it can be concluded that the application of NIRS technique allowed the authentication of all strawberry varieties and geographical origin as well. It was also possible to form subclasses of the same materials. The results presented here demonstrate that NIRS is a very powerful and promising analytical tool since all materials were authenticated and classified based on their variety, origin, and treatment. This is of a tremendous relevance since the variety and origin of a plant material can be established even before it gives its typical fruit or flower.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1256-1256
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• 2001

The physico-chemical and texture characteristics of meat determine the nutritional, technological and sensory quality. However, the analysis of meat quality requires expensive, laborious and time consuming analytical methods. The objective of this study was to evaluate NIR spectroscopy using transmittance for determining the moisture, fat, protein and total pigment content, the water holding capacity (WHC) and the toughness of beef meat. A total of 318 spectra were recorded from ground beef samples by a Feed Analyzer 1265 of Infratec. The samples were obtained from the Longissimus muscle of the 10$^{th}$ rib of yearling bulls, ground with an electrical chopper, vacuum packaged, aged during 7 days and frozen at -24$^{\circ}C$ until the analyses were done. Moisture content was measured by oven drying at 10$0^{\circ}C$, fat content was determined by Soxhlet extraction and protein content was estimated from nitrogen content using the Kjeldahl analysis. The total pigment content was determined by the method of Hornsey and the WHC using the method of filter paper press. The instrumental evaluation of texture (maximum load WB, maximum stress MS and toughness) was conducted in an Instron equipment with a Warner-Bratzler shearing device. This analysis was performed on a chop of 3.5 cm obtained from the longissimus of the 8$^{th}$ rib, aged during 7 days, kept frozen at -24$^{\circ}C$ and cooked before the analysis. Near infrared spectra were recorded as log 1/T (T=transmittance) at 2 nm intervals from 850 to 1050 nm using a Feed Analyzer 1265 of Infratec. Calibrations were performed with the WinISI software (vs. 1.02) using the MPLS method. To examine the effect of scatter correction o. derivation of spectra on the calibration performance, calibrations were calculated with the crude spectra or pretreated with different mathematical treatments (inverse MSC, SNVD) and/or second derivative operation. For chemical composition, the use of the scatter corrections improved the calibration statistics, in terms of lower SECV and higher $r^2$. In most of the variables, the use of the 2$^{nd}$ derivative improved the predictions, mainly when combined with the SNVD treatment. However, for predicting the texture traits, the best estimation was obtained from the crude spectrum. These results showed that the equations obtained for predicting moisture, fat and total pigments were very accurate, with $r^2$ being higher that 0.9. However, the prediction of the texture traits (WB, MS, toughness) from ground meat was poor.

• 한국작물학회지
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• 제50권6호
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• pp.394-399
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• 2005

벼 영양진단에서 중요한 성분인 생체잎의 질소함량을 NIRS를 이용하여 신속하고 정확하게 분석하기 위해 최적의 검량식 작성에 관한 일련의 시험을 실시한 결과는 다음과 같다. 벼 생체엽 질소함량 검량식의 결정계수는 익산, 정읍, 부안지역이 각각 0.879, 0.858, 0.819였다. Outlier를 제거한 후 검량식을 다시 작성한 결과 0.896, 0.878, $0.88\%$로 각각 0.017, 0.02, 0.061씩 향상되었다. Merge 기능을 이용하여 검량식을 합병한 후 검량식을 다시 작성한 결과 0.971로 정확도가 더욱 향상되었다. 벼 생체엽의 질소함량 검량식에 의한 분석값과 습식분석 평균값의 차이는 $0.001\%$를 나타냈다. 이와 같은 결과로서 건조와 분쇄과정을 생략하기 때문에 시료의 변질을 막을 수 있고 시간과 비용을 줄일 수 있는 벼 생잎의 질소농도 측정이 근적외분석기술에 의해 가능할 것으로 판단되었다.

• 농업과학연구
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• 제39권1호
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• pp.117-123
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• 2012

Pathogenic fungi and bacteria such as Pectobacterium atrosepticum, Clavibacter michiganensis subsp. sepedonicus, Verticillium albo-atrum, and Rhizoctonia solani were the major microorganism which causes diseases in seed potato during postharvest process. Current detection method for disease-infected seed potato relies on human inspection, which is subjective, inaccurate and labor-intensive method. In this study, a reflectance spectroscopy was used to classify sound and disease-infected seed potatoes with the spectral range from 400 to 1100 nm. Partial least square discriminant analysis (PLS-DA) with various preprocessing methods was used to investigate the feasibility of classification between sound and disease-infected seed potatoes. The classification accuracy was above 97 % for discriminating disease seed potatoes from sound ones. The results show that Vis/NIR reflectance method has good potential for non-destructive sorting for disease-infected seed potatoes.

• 한국세라믹학회지
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• 제53권1호
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• pp.105-109
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• 2016

We prepared a working electrode (WE) with a blocking layer (BL) containing 0 ~ 0.5 wt% Ag nano powders to improve the energy conversion efficiency (ECE) of dye sensitized solar cell (DSSC). FESEM and micro-Raman were used to characterize the microstructure and phase. UV-VIS-NIR spectroscopy was employed to determine the adsorption of the WE with Ag nano powders. A solar simulator and a potentiostat were used to confirm the photovoltaic properties of the DSSC with Ag nano powders. From the results of the microstructural analysis, we confirmed that Ag nano powders with particle size of less than 150 nm were dispersed uniformly on the BL. Based on the phase and adsorption analysis, we identified the existence of Ag and found that the adsorption increased when the amount of Ag increased. The photovoltaic results show that the ECE became 4.80% with 0.3 wt%-Ag addition compared to 4.31% without Ag addition. This improvement was due to the increase of the localized surface plasmon resonance (LSPR) of the BL resulting from the addition of Ag. Our results imply that we might be able to improve the efficiency of a DSSC by proper addition of Ag nano powder to the BL.