NIR Spectroscopy Technique Research Articles

On the development of experimental methods to determine the rates of asphaltene precipitation, aggregation, and deposition

Despite the efforts throughout the last few decades, asphaltene deposition remains as one of the greatest challenges in the petroleum industry. In this work, we present a comprehensive series of experimental studies to better understand the asphaltene precipitation, aggregation, and deposition mechanisms. Here, we introduce a simple method to determine the amount of precipitated asphaltene using NIR spectroscopy measurements without the implementation of calibration curves. Moreover, the kinetics of asphaltene precipitation and aggregation is simultaneously investigated by a newly developed, fast, and reliable NIR spectroscopy technique. In the new method, only less than 2 ml of sample is required for each experiment. In addition, unlike gravimetric techniques, less time consuming and labor-intensive measurements can be performed. In addition, the temperature can be controlled; hence, experiments can be conducted to evaluate the effects of temperature and the driving force on the kinetics of asphaltene precipitation and aggregation. Subsequently, the quantified precipitated asphaltene amount can be used to calibrate the precipitation and aggregation kinetic parameters of the asphaltene deposition model. The results obtained from the kinetics experiments facilitate in establishing a function to scale the precipitation kinetic parameter from laboratory-scale experiments to real field high-pressure high-temperature conditions. Additionally, a multi-section stainless steel packed bed column is proposed to study asphaltene deposition at high temperature and under dynamic conditions. In these experiments, the amount of deposited asphaltene is directly quantified. The results from the packed bed column deposition tests can be used to calibrate the deposition kinetic parameter of the asphaltene deposition model.

실시간 토양 판별을 위한 근적외선 분광기술과 인공신경망 기술의 적용

실시간 토양 판별을 위한 근적외선 분광기술과 인공신경망 기술의 적용

Synthesis and photoluminescent characteristics of Dy3+ doped Gd2O3 phosphors

Pure and dysprosium doped gadolinium oxide nanoparticles for three different concentrations (2, 5 and 10 mol.%) were synthesized by auto-combustion method using citric acid as fuel. The nanoparticles obtained were characterized using powder x-ray diffraction (XRD), Fourier transform infrared (FTIR), scanning electron microscopy (SEM), UV–vis–NIR spectroscopy and photoluminescence (PL) spectroscopy techniques. XRD pattern revealed the crystalline cubic phase with space group Ia3 (Space Group: 206) for both the pure and doped Gd2O3 nanoparticles. The metal oxide phase formation and purity of Gd2O3 nanoparticles were further confirmed from the FTIR spectra. Morphology of the pure Gd2O3 powder is loosely dispersed clusters of tiny particles with microscopic pores, whereas for the doped samples aggregates were broken to form small clusters. Optical absorption measurements were recorded in the UV–vis–NIR wavelength region and the optical band gap variations with dopant concentration were discussed. The PL spectra of pure and Dy3+ doped Gd2O3 nanoparticles have been studied and the effect of emitted light on the yellow-to-blue intensity ratio (Y/B) of Dy3+ emission was demonstrated.

Effect of film thickness on the solar cell performance of CBD grown CdS/PbS heterostructure

CdS, PbS and CdS/PbS thin films were deposited onto glass and ITO substrates using chemical bath technique. The thickness of the CdS was varied by varying the deposition time and the influence of film thickness on structural, morphological, optical and electrical properties of the as-deposited films were investigated by XRD, SEM, UV–Vis–NIR spectroscopy and two-probe techniques. XRD analysis of CdS and PbS films have shown polycrystalline nature of the films with preferred orientation along (002) and (200) reflections. The grain size of the CdS film was found to increases with the film thickness. Scanning electron microscopic results of the CdS films have revealed smooth morphology and it has found to show increased particle size with the film thickness. Optical transmittance of the CdS thin films was found to decrease with the film thickness. The increase of deposition time is found to shift the band gap from 2.75 to 2.66 eV. Band gap of the PbS film is found to be 1.57 eV for a thickness of 0.89 µm. The photo-response studies done for CdS/PbS heterojunction solar cells have indicated that the film thickness has an influence on the cell efficiency. The observed enhancement in solar cell properties is attributed to the changes in the morphology, the crystalline quality and the optical properties caused by the increase of film thickness.

Near-infrared spectra of liquid/solid acetylene under Titan relevant conditions and implications for Cassini/VIMS detections

Acetylene is thought to be abundant on Titan according to most photochemical models. While detected in the atmosphere, its likely presence at the surface still lacks physical evidence. It is thought that solid acetylene could be a major component of Titan’s lakes shorelines and dry lakebed, detected as the 5μm-bright deposits with the Cassini/VIMS instrument. Acetylene could also be present under its liquid form as dissolved solids in Titan’s methane–ethane lakes, as emphasized by thermodynamics studies. This paper is devoted to the near-infrared spectroscopy study of acetylene under solid and liquid phases between 1 and 2.2μm, synthesized in a Titan simulation chamber that is able to reproduce extreme temperature conditions. From experiments, we observed a ∼10% albedo increase between liquid acetylene at 193–188K and solid acetylene at 93K. Using the NIR spectroscopy technique we successfully calculated the reflectivity ratio of solid/liquid acetylene as 1.13. The second difference we observed between liquid and solid acetylene is a shift in the major absorption band detected at 1.54μm, the shift of ∼0.01μm occurring toward higher wavelength. In order to assess the detectability of acetylene on Titan using the Cassini/VIMS instrument, we adapted our spectra to the VIMS spectral resolution. The spectral band at 1.55μm and a negative slope at 2.0μm falls in the Cassini/VIMS atmospheric windows over several VIMS infrared spectels, thus Cassini/VIMS should be able to detect acetylene.

Surface modifications caused by a swift heavy ion irradiation on crystalline p-type gallium antimonide

Surface modifications caused by a swift heavy ion irradiation on crystalline p-type gallium antimonide crystal have been reported. Single crystal, 100〉 orientations and ∼500μm thick p-type GaSb samples with carrier concentration of 3.30×1017cm−3 were irradiated at 100MeV Fe7+ ions. We have used 15UD Pelletron facilities at IUAC with varying fluences of 5×1010–1×1014 ions cm−2. The effects of irradiation on these samples have been investigated using, spectroscopic ellipsometry, atomic force microscopy and ultraviolet–visible–NIR spectroscopy techniques. Ellipsometry parameters, psi (Ψ) and delta (Δ) for the unirradiated sample and samples irradiated with different fluences were recorded. The data were fit to a three phase model to determine the refractive index and extinction coefficient. The refractive index and extinction coefficient for various fluences in ultraviolet, visible, and infrared, regimes were evaluated. Atomic force microscopy has been used to study these surface modifications. In order to have more statistical information about the surface, we have plotted the height structure histogram for all the samples. For unirradiated sample, we observed the Gaussian fitting. This result indicates the more ordered height structure symmetry. Whereas for the sample irradiated with the fluence of 1×1013, 5×1013 and 1×1014 ions cm−2, we observed the scattered data. The width of the histogram for samples irradiated up to the fluence of 1×1013 ion cm−2 was found to be almost same however it decreased at higher fluence. UV reflectance spectra of the sample irradiated with increasing fluences exhibit three peaks at 292, 500 and 617nm represent the high energy GaSb; E1, E1+Δ and E2 band gaps in all irradiated samples.

Structure–property relations in donor–acceptor–donor type benzimidazole containing conjugated polymers

In order to gain deeper insight about structure–property relations properties, two novel donor–acceptor–donor type monomers were studied. 4′-Tert-butyl-4,7-di(thiophen-2-yl)spiro[benzo[d]imidazole-2,1′-cyclohexane] and 4,7-di(2,2′-bithiophen-5-yl)-4′-tert-butylspiro[benzo[d]imidazole-2,1′-cyclohexane] were synthesized and electrochemically polymerized. Electrochemical and optical properties of the polymers were investigated via cyclic voltammetry and UV–Vis–NIR spectroscopy techniques. It was found that changing donor unit from thiophene to bithiophene results in a drastic change in optical and electrochemical properties, especially in optical contrast. In this study, we investigate the effect of conjugation on the properties of electrochemically synthesized polymers. For this purpose, 4,7-dibromo-4′-(tert-butyl)spiro[benzo[d]imidazole-2′-cyclohexane] was synthesized as an acceptor unit and coupled with two different donor units, namely thiophene and bitihophene. Their optical and electronic properties were compared and spectroelectrochemical studies showed that with increasing conjugation, absorption maxima is red shifted together with a decrease in the optical band gap.

Hyperspectral Imaging Applications in Agriculture and Agro-Food Product Quality and Safety Control: A Review

In this review, various applications of near-infrared hyperspectral imaging (NIR-HSI) in agriculture and in the quality control of agro-food products are presented. NIR-HSI is an emerging technique that combines classical NIR spectroscopy and imaging techniques in order to simultaneously obtain spectral and spatial information from a field or a sample. The technique is nondestructive, nonpolluting, fast, and relatively inexpensive per analysis. Currently, its applications in agriculture include vegetation mapping, crop disease, stress and yield detection, component identification in plants, and detection of impurities. There is growing interest in HSI for safety and quality assessments of agro-food products. The applications have been classified from the level of satellite images to the macroscopic or molecular level.

Feasibility Study on the Evaluation of the Dry Rubber Content of Field and Concentrated Latex of Para Rubber by Diffuse Reflectance near Infrared Spectroscopy

The analysis of the dry rubber content (DRC) of Para rubber latex, including field latex and concentrated latex, using near infrared spectroscopy was conducted using a Fourier transform near infrared (FT-NIR) spectrometer in diffuse reflection mode over the wavenumber range of 4000–10,000 cm−1. The proposed method is useful for industrial purposes. The best model was developed using the partial least square regression (PLSR) from the spectra, which were pretreated using the 2nd derivative method, where the correlation ( r2), standard error of prediction ( SEP) and bias were 0.997, 0.3398% and −0.0239%, respectively. The ratio of standard deviation ( SD) to SEP of the reference data in the prediction sample set ( RPD) was 18.18 and the ratio of the range to the SEP of the prediction set ( REP) was 74.4. The model was validated using a new batch of samples and the prediction performance was good with an r2 of 0.999, a SEP of 0.3898% and a bias of −0.0008%. Therefore, the NIR spectroscopy technique can be used as an accurate and rapid method for estimating the DRC of Para rubber latex for both field and concentrated latex.

Measurement of process variables in solid-state fermentation of wheat straw using FT-NIR spectroscopy and synergy interval PLS algorithm

The feasibility of rapid determination of the process variables (i.e. pH and moisture content) in solid-state fermentation (SSF) of wheat straw using Fourier transform near infrared (FT-NIR) spectroscopy was studied. Synergy interval partial least squares (siPLS) algorithm was implemented to calibrate regression model. The number of PLS factors and the number of subintervals were optimized simultaneously by cross-validation. The performance of the prediction model was evaluated according to the root mean square error of cross-validation (RMSECV), the root mean square error of prediction (RMSEP) and the correlation coefficient (R). The measurement results of the optimal model were obtained as follows: RMSECV=0.0776, Rc=0.9777, RMSEP=0.0963, and Rp=0.9686 for pH model; RMSECV=1.3544% w/w, Rc=0.8871, RMSEP=1.4946% w/w, and Rp=0.8684 for moisture content model. Finally, compared with classic PLS and iPLS models, the siPLS model revealed its superior performance. The overall results demonstrate that FT-NIR spectroscopy combined with siPLS algorithm can be used to measure process variables in solid-state fermentation of wheat straw, and NIR spectroscopy technique has a potential to be utilized in SSF industry.

A feasibility study on quantitative analysis of glucose and fructose in lotus root powder by FT-NIR spectroscopy and chemometrics

The feasibility of rapid analysis of glucose and fructose in lotus root powder by Fourier transform near-infrared (FT-NIR) spectroscopy was studied. Diffuse reflectance spectra were collected between 4000 and 12,432cm(-1). Calibration models established by partial least-squares regression (PLSR), interval PLS of forward (FiPLS) and backward (BiPLS), back propagation-artificial neural networks (BP-ANN) and least squares-support vector machine (LS-SVM) were compared. The optimal models for glucose and fructose were obtained by LS-SVM with the first 10 latent variables (LVs) as input. For fructose the correlation coefficients of calibration (rc) and prediction (rp), the root-mean-square errors of calibration (RMSEC) and prediction (RMSEP), and the residual predictive deviation (RPD) were 0.9827, 0.9765, 0.107%, 0.115% and 4.599, respectively. For glucose the indexes were 0.9243, 0.8286, 0.543%, 0.812% and 1.785. The results indicate that NIR spectroscopy technique with LS-SVM offers effective quantitative capability for glucose and fructose in lotus root powder.

Rapid measurement of antioxidant activity in dark soy sauce by NIR spectroscopy combined with spectral intervals selection and nonlinear regression tools

This paper attempted to show the feasibility of measuring the antioxidant activity in dark soy sauce by NIR spectroscopy technique. Chemometrics on spectral intervals selection and nonlinear regression tools were systematically studied in the calibrating model. First, the optimal spectral intervals were selected by synergy interval-partial least square (Si-PLS). Then, kernel PLS (KPLS) and back propagation artificial neural network (BPANN), as two nonlinear regression tools, were performed comparatively to calibrate models based on optimal spectral intervals, called Si-KPLS and Si-BPANN models, respectively. These models were optimized by cross-validation, and the performance of the final model was evaluated according to correlation coefficient (Rp2) and root mean square error of prediction (RMSEP) in the prediction set. The results showed that the Si-BPANN model was superior to other models, and the optimal result was achieved with Rp2 = 0.9769 and RMSEP = 0.0221 in the prediction set. This work demonstrated that total antioxidant capacity in dark soy sauce could be measured by NIR spectroscopy technique, and Si-BPANN showed its superiority in model calibration.

Study of organo-hybrid layered double hydroxides by medium and near infrared spectroscopy

An Mg/Al layered double hydroxide (LDH) containing carbonate ion in its interlayer region was examined by medium infrared (MIR) and near infrared reflectance spectroscopy (NIRS). The MIR and NIR spectroscopy techniques was also used to study two organo-hybrid LDHs containing interlayer dodecylbenzenesulphonate (DBS) and dodecylsulphate (DS) ions, respectively. The NIR spectra for the latter solids were found to exhibit the overtone and combination bands for the hydroxyl groups in addition to those typical bands of the organic host functions.

Classification of biodiesel using NIR spectrometry and multivariate techniques

This article describes the classification of biodiesel samples using NIR spectroscopy and chemometric techniques. A total of 108 spectra of biodiesel samples were taken (being three samples each of four types of oil, cottonseed, sunflower, soybean and canola), from nine manufacturers. The measurements for each of the three samples were in the spectral region between 12,500 and 4000 cm −1 . The data were preprocessed by selecting a spectral range of 5000–4500 cm −1, and then a Savitzky–Golay second-order polynomial was used with 21 data points to obtain second derivative spectra. Characterization of the biodiesel was done using chemometric models based on hierarchical cluster analysis (HCA), principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA) elaborated for each group of biodiesel samples (cotton, sunflower, soybean and canola). For the HCA and PCA, the formation of clusters for each group of biodiesel was observed, and SIMCA models were built using 18 spectral measurements for each type of biodiesel (training set), and nine spectral measurements to construct a classification set (except for the canola oil which used eight spectra). The SIMCA classifications obtained 100% accurate identifications. Using this strategy, it was feasible to classify biodiesel quickly and nondestructively without the need for various analytical determinations.

Measurement of total flavone content in snow lotus (Saussurea involucrate) using near infrared spectroscopy combined with interval PLS and genetic algorithm

NIR spectroscopy technique was attempted to measure total flavone content in snow lotus in this work. Interval partial least square with genetic algorithm (iPLS-GA) was used to select the efficient spectral regions and variables in model calibration. The performance of the final model was back-evaluated according to root mean square error of calibration (RMSEC) and correlation coefficient (R(c)) in calibration set, and tested by mean square error of prediction (RMSEP) and correlation coefficient (R(p)) in prediction set. The optimal iPLS-GA model was obtained with 6 PLS factors, when 5 spectral regions and 53 variables were selected. The measurement results of final model were achieved as follow: RMSEC (%)=0.8347/R(c)=0.9444 in the calibration set, and RMSEP (%)=1.0766/R(p)=0.9006 in the prediction set. Finally, iPLS-GA moded showed its excellent performance, when compared with other 5 different PLS models. This work demonstrated that total flavone content in snow lotus could be measured by NIR spectroscopy technique, and iPLS-GA revealed its superiority in model calibration.

Analysis of Sugars in Chinese Rice Wine by Fourier Transform Near-Infrared Spectroscopy with Partial Least-Squares Regression

The feasibility of rapid analysis for oligosaccharides, including isomaltose, isomaltotriose, maltose, and panose, in Chinese rice wine by Fourier transform near-infrared (FT-NIR) spectroscopy together with partial least-squares regression (PLSR) was studied in this work. Forty samples of five brewing years (1996, 1998, 2001, 2003, and 2005) were analyzed by NIR transmission spectroscopy with seven optical path lengths (0.5, 1, 1.5, 2, 2.5, 3, and 5 mm) between 800 and 2500 nm. Calibration models were established by PLSR with full cross-validation and using high-performance anion-exchange chromatography coupled with pulsed amperometric detection as a reference method. The optimal models were obtained through wavelength selection, in which the correlation coefficients of calibration (r(cal)) for the four sugars were 0.911, 0.938, 0.925, and 0.966, and the root-mean-square errors of calibrations were 0.157, 0.147, 0.358, and 0.355 g/L, respectively. The validation accuracy of the four models, with correlation coefficients of cross-validation (r(cv)) being 0.718, 0.793, 0.681, and 0.873, were not very satisfactory. This might be due to the low concentrations of the four sugars in Chinese rice wine and the influence of some components having structures similar to those of the four sugars. The results obtained in this study indicated that the NIR spectroscopy technique offers screening capability for isomaltose, isomaltotriose, maltose, and panose in Chinese rice wine. Further studies with a larger Chinese rice wine sample should be done to improve the specificity, prediction accuracy, and robustness of the models.