Min-Sik Ku

Comparison of near-infrared and mid-infrared spectroscopy for the determination of distillation property of kerosene

Abstract Near-infrared (NIR) and mid-infrared (MIR) spectroscopy have been compared and evaluated for the determination of the distillation property of kerosene with the use of partial least squares (PLS) regression. Since kerosene is a complex mixture of similar hydrocarbons, both spectroscopic methods will be best evaluated with this complex sample matrix. PLS calibration models for each percent recovery temperature have been developed by using both NIR and MIR spectra without spectral pretreatment. Both methods have shown good correlation with the corresponding reference method, however NIR provided better calibration performance over MIR. To rationalize the improved calibration performance of NIR, spectra of the same kerosene sample were continuously collected and the corresponding spectral reproducibility was evaluated. The greater spectral reproducibility including signal-to-noise ratio of NIR led to the improved calibration performance, even though MIR spectroscopy provided more qualitative spectral information. The reproducibility of measurement, signal-to-noise ratio, and richness of qualitative information should be simultaneously considered for proper selection of a spectroscopic method for quantitative analysis.

Comparison of Near-Infrared, Infrared, and Raman Spectroscopy for the Analysis of Heavy Petroleum Products

Near-infrared (NIR) spectroscopy has been successfully applied to the determination of API (American Petroleum Institute) gravity of atmospheric residue (AR), which is the heaviest fraction in crude oil. This fraction is completely dark and very viscous. Preliminary studies involving Raman and infrared (IR) spectroscopies were also evaluated along with NIR spectroscopy. The Raman spectrum of AR was completely dominated by strong fluorescence from polycyclic aromatic hydrocarbons, called asphaltenes. IR spectroscopy provided reasonable spectral features; however, its spectral reproducibility was poorer and noisier than that of NIR. Although absorption bands in the NIR region were broad and less characterized, NIR provided better spectral reproducibility with higher signal-to-noise ratio (which is one of the most important parameters in quantitative calibration in comparison to Raman and IR spectroscopies). Partial least-squares (PLS) regression was utilized to develop calibration models. NIR spectra of AR samples were broad, and baselines were varying due to the strong absorption in the visible range. However, the necessary information was successfully extracted and correlated to the reference API gravity with the use of PLS regression. API gravities in the prediction set were accurately predicted with an SEP (standard error of prediction) of 0.22. Additionally NIR showed approximately three times better repeatability compared to the ASTM reference method, which directly influences the process control performance.

Comparison of Near-Infrared and Raman Spectroscopy for the Determination of Chemical and Physical Properties of Naphtha

Near-infrared (NIR) and Fourier transform (FT) Raman spectroscopy have been compared and evaluated for the quantitative analysis of naphtha with the use of partial least-squares (PLS) regression. Naphtha has been chosen for this purpose since it is a complex mixture of similar hydrocarbons; therefore, both spectroscopic methods can be evaluated with a complex sample of different concentration ranges and also a physical property. Six different chemical compositions [total paraffin, total naphthene (cycloalkane), total aromatic, C6 paraffin, benzene, and cyclopentane] and specific gravity (as a physical parameter) have been selected to evaluate both spectroscopic methods. PLS calibration models for each property have been developed by using both NIR and Raman spectra without spectral pretreatment. Both methods showed good correlation with the corresponding reference methods, but NIR provided the better calibration performance over Raman. The superior signal-to-noise ratio as well as spectral reproducibility of NIR led to the improved calibration performance even though Raman spectroscopy provided richer spectral information. The signal-to-noise ratio, reproducibility of measurement, and richness of spectral information should be simultaneously considered for proper selection of a spectroscopic method, especially for quantitative analysis.

Feasibility of Simultaneous Measurement of Xylene Isomers and other Hydrocarbons in p-Xylene Production Processes Using Near-Infrared Spectroscopy

The feasibility of simultaneous measurement of important components such as o-xylene, m-xylene, p-xylene, ethylbenzene, toluene, aliphatic hydrocarbons, and total C9–C10 aromatic hydrocarbons in the p-xylene production process is investigated. Mixtures of those components were prepared to simulate concentration levels in actual p-xylene processes, and near-infrared (NIR) spectra were collected from mixtures over the spectral range of 1100 to 2500 nm. Even with the very similar spectral features of xylene isomers and other aromatic compounds, the concentrations of each of the components in the mixtures are accurately predicted by using a partial least-squares (PLS) algorithm and show excellent correlation with conventional gas chromatographic analysis. The results clearly demonstrate the possibility of using NIR spectroscopy for monitoring the major components in an actual p-xylene production process for process control and optimization.

Near-infrared spectral data transfer using independent standardization samples: a case study on the trans-alkylation process

Abstract A variety of standardization or transfer methods between near infrared spectrometric instruments are applied for the content prediction of five major constituents of the product at trans-alkylation process with spectra measured on two different instruments. Because process samples are difficult to be stored, we use independent transfer samples by blending some pure materials for the spectrum standardization of the process samples. Using the independent standardization samples, we investigate the transfer performance of well-known piecewise direct standardization combined with several regression methods on the raw spectra. Also, we propose some indirect standardization methods utilizing wavelet transferred scores or factor scores through principal component analysis and partial least squares. The standardization by transferring scores takes only a few transfer coefficients, but it shows similar performance to the spectrum transfer case. In addition, we show the possibility of using a fewer number of stable samples than the original set of samples for the standardization with similar performance.

Feasibility of monitoring acetic acid process using near-infrared spectroscopy

Near-infrared (NIR) spectroscopy has been utilized to demonstrate its feasibility for the measurement of major components in the acetic acid process. In order to simulate the acetic acid process, synthetic mixtures were prepared from five different components: acetic acid, methyl acetate, methyl iodide, water, and potassium iodide. Partial least squares (PLS) regression was utilized to differentiate the spectral characteristics as well as to quantify each component for the mixtures. The spectral features of acetic acid, methyl acetate, methyl iodide, and water are noticeably different with each other over the entire NIR region. The quantity of iodide ion, which does not absorb NIR radiation, was determined using the wavelength shift and intensity change of water absorption band caused by the change of iodide ion concentration. The PLS calibration results of the five components show good correlation with reference data. They also demonstrate the technical feasibility of NIR spectroscopy for monitoring important components in the acetic acid process.

Near-infrared spectroscopy for on-line monitoring of lube base oil processes.

Near-infrared (NIR) spectroscopy has been utilized for monitoring the pour point of the lube base oil (LBO) process. Using partial least-squares (PLS) regression, necessary spectral features were successfully extracted and correlated to the reference pour-point data. In a preliminary laboratory feasibility study, it was found that PLS calibration performance was largely governed by the accuracy of the reference pour-point analysis. The same NIR spectroscopic methodology was moved to monitor the pour point continuously in an on-line manner. At this time, the NIR spectrometer was calibrated with the existing on-line pour-point analyzer, which was more accurate. In comparison with the on-line pour-point analyzer, NIR spectroscopy provided faster and more repeatable analytical data. With the help of NIR analysis, LBO process variations during product switch can be detected earlier, and necessary process-control strategy can be applied to improve the process efficiency.

Near-Infrared Spectroscopy for Monitoring the p-Diethylbenzene Separation Process

Near-infrared (NIR) spectroscopy has been successfully used for the monitoring of important components in the p-diethylbenzene (PDEB) separation process. The process is composed of mostly diethylbenzene isomers (ortho, meta, and para) and extractant (p-xylene), as well as other C9–C11 aromatic hydrocarbons. Therefore, the major concern in using NIR spectroscopy in this process was the spectral resolution of NIR spectra among diethylbenzene isomers, since the molecular structures of each isomer were very similar. NIR spectral features of o-diethylbenzene (ODEB), m-diethylbenzene (MDEB), and PDEB showed considerable spectral differences in the 2100–2220 nm range. These combination bands originated from the combination of the =C–H stretch at 3100–3000 cm−1 and C=C ring stretch at 1600–1450 cm−1. Characteristic C=C ring stretches of each isomers in the IR region result in selective and identifiable spectral features in the NIR region. Partial least-squares (PLS) regression was used to build each calibration model for ODEB, MDEB, PDEB, and p-xylene (PX). PLS calibration results of the four components showed excellent correlation with gas chromatography data. The combination region (2100–2500 nm) provided the important isomeric spectral information for PLS calibration since the absorption bands in this region were the most sensitive and selective.