The Effect of Chain Length on Mid-Infrared and Near-Infrared Spectra of Aliphatic 1-Alcohols

2017 ◽  
Vol 72 (2) ◽  
pp. 288-296 ◽  
Author(s):  
Michał Kwaśniewicz ◽  
Mirosław A. Czarnecki
Keyword(s):  
Correlation Analysis ◽  
Chain Length ◽  
Near Infrared ◽  
Hydrophobic Interactions ◽  
Principal Component ◽  
Butyl Alcohol ◽  
Two Dimensional ◽  
Data Set ◽  
Mid Infrared ◽  
Spectral Changes

Effect of the chain length on mid-infrared (MIR) and near-infrared (NIR) spectra of aliphatic 1-alcohols from methanol to 1-decanol was examined in detail. Of particular interest were the spectra-structure correlations in the NIR region and the correlation between MIR and NIR spectra of 1-alcohols. An application of two-dimensional correlation analysis (2D-COS) and chemometric methods provided comprehensive information on spectral changes in the data set. Principal component analysis (PCA) and cluster analysis evidenced that the spectra of methanol, ethanol, and 1-propanol are noticeably different from the spectra of higher 1-alcohols. The similarity between the spectra increases with an increase in the chain length. Hence, the most similar are the spectra of 1-nonanol and 1-decanol. Two-dimensional hetero-correlation analysis is very helpful for identification of the origin of bands and may guide selection of the best spectral ranges for the chemometric analysis. As shown, normalization of the spectra pronounces the intensity changes in various spectral regions and provides information not accessible from the raw data. The spectra of alcohols cannot be represented as a sum of the CH3, CH2, and OH group spectra since the OH group is involved in the hydrogen bonding. As a result, the spectral changes of this group are nonlinear and its spectral profile cannot be properly resolved. Finally, this work provides a lot of evidence that the degree of self-association of 1-alcohols decreases with the increase in chain length because of the growing meaning of the hydrophobic interactions. For butyl alcohol and higher 1-alcohols the hydrophobic interactions are more important than the OH OH interactions. Therefore, methanol, ethanol, and 1-propanol have unlimited miscibility with water, whereas 1-butanol and higher 1-alcohols have limited miscibility with water.

Application of Chemometrics Approaches to Analysis of Mid-Infrared Spectra of Ibuprofen Diluted in Supercritical Carbon Dioxide

2018 ◽  
Vol 72 (10) ◽  
pp. 1548-1560
Author(s):  
Roman D. Oparin ◽  
Michael G. Kiselev
Keyword(s):  
Correlation Analysis ◽  
Cross Correlation ◽  
Spectral Band ◽  
Principal Component ◽  
Matrix Analysis ◽  
Data Matrix ◽  
Two Dimensional ◽  
Mid Infrared ◽  
Temperature Range ◽  
Cross Correlation Analysis

This work represents a comprehensive analysis of mid-infrared (mid-IR) spectra of ibuprofen diluted in supercritical CO2 (in the temperature range of 40–90 ℃ and at the CO2 density corresponding to 1.3 of its critical value). The study employed mathematical approaches based on data matrix analysis such as two-dimensional cross-correlation analysis (2D-COS) and principal component analysis (PCA). Two-dimensional cross-correlation analysis allowed us to reveal correlations between the spectral contributions constituting the analytical spectral band and assigned to certain ibuprofen conformers, as well as the significance of these correlations. It has been shown that the considerable increase in the total intensity of the analytical spectral band, proportional to the equilibrium ibuprofen concentration in the supercritical CO2 phase, is accompanied by certain redistribution of intensities of the spectral components related to the corresponding conformers. The PCA allowed us to determine the changes of intensities of individual spectral contributions for each thermodynamic point in the considered temperature range. It has been shown that these two complementary methods provide more precise information that may be used as the initial data in the classical analysis of spectral data based on spectral curve deconvolution into individual spectral contributions.

Two-Dimensional Heterospectral Correlation Analysis of Water and Liquid Oleic Acid Using an Online Near-Infrared/Mid-Infrared Dual-Region Spectrometer

2013 ◽  
Vol 67 (7) ◽  
pp. 724-730 ◽  
Author(s):  
Takuma Genkawa ◽  
Masahiro Watari ◽  
Takashi Nishii ◽  
Masao Suzuki ◽  
Yukihiro Ozaki
Keyword(s):  
Oleic Acid ◽  
Correlation Analysis ◽  
Near Infrared ◽  
Two Dimensional ◽  
Mid Infrared

Canonical Correlation Analysis of Mid- and Near-Infrared Oil Spectra

1993 ◽  
Vol 47 (7) ◽  
pp. 1024-1029 ◽  
Author(s):  
M. F. Devaux ◽  
P. Robert ◽  
A. Qannari ◽  
M. Safar ◽  
E. Vigneau
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Infrared Spectra ◽  
Canonical Correlation ◽  
Near Infrared ◽  
Principal Component ◽  
Canonical Variate ◽  
Mid Infrared ◽  
Highly Correlated ◽  
Spectral Patterns

A mathematical procedure based on Canonical Correlation Analysis (CCA) was used in order to assign the wavelengths of the near-infrared spectra through knowledge of the mid-infrared spectra. The relevance of the treatment was tested on commercial oils that mainly differ in their level of unsaturation. Initially, two separated Principal Component Analyses (PCAs) were performed on the near- and mid-infrared data to overcome the high intercorrelations across the wavelengths. CCA was then applied to the resulting principal components. Near- and mid-infrared canonical variates were assessed so that they achieved maximum correlation. The procedure makes it possible to draw CCA spectral patterns that exhibit significant positive and negative peaks. The first near-infrared canonical variate was highly correlated with the first mid-infrared canonical variate ( r2 = 0.97). The corresponding near- and mid-infrared CCA spectral patterns were therefore given the same interpretation. The mid-infrared pattern opposed negative peaks characteristic of CH2 groups to the positive peaks of CH3 and =CH groups. Consequently, in the near-infrared pattern, the positive peaks at 1708, 2140, 2170, and 2480 nm were assigned to CH3 or =CH groups, and the negative peaks at 2304, 2344, and 2445 nm were assigned to CH2 groups. A more precise interpretation was obtained by comparing the wavelengths observed to theoretical values and to previous assignments.

Mid and near Infrared Study of Carbohydrates by Canonical Correlation Analysis

1993 ◽  
Vol 1 (2) ◽  
pp. 99-108 ◽  
Author(s):  
P. Robert ◽  
M.F. Devaux ◽  
A. Qannari ◽  
M. Safar
Keyword(s):  
Correlation Analysis ◽  
Infrared Spectra ◽  
Canonical Correlation ◽  
Near Infrared ◽  
Sugar Content ◽  
Infrared Region ◽  
Total Sugar ◽  
Mid Infrared ◽  
Total Sugar Content ◽  
Near Infrared Spectra

Multivariate data treatments were applied to mid and near infrared spectra of glucose, fructose and sucrose solutions in order to specify near infrared frequencies that characterise each carbohydrate. As a first step, the mid and near infrared regions were separately studied by performing Principal Component Analyses. While glucose, fructose and sucrose could be clearly identified on the similarity maps derived from the mid infrared spectra, only the total sugar content of the solutions was observed when using the near infrared region. Characteristic wavelengths of the total sugar content were found at 2118, 2270 and 2324 nm. In a second step, the mid and near infrared regions were jointly studied by a Canonical Correlation Analysis. As the assignments of frequencies are generally well known in the mid infrared region, it should be useful to study the relationships between the two infrared regions. Thus, the canonical patterns obtained from the near infrared spectra revealed wavelengths that characterised each carbohydrate. The OH and CH combination bands were observed at: 2088 and 2332 nm for glucose, 2134 and 2252 nm for fructose, 2058 and 2278 nm for sucrose. Although a precise assignment of the near infrared bands to chemical groups within the molecules was not possible, the present work showed that near infrared spectra of carbohydrates presented specific features.

Effect of the chain length on near-infrared spectra of 1-alcohols from methanol to 1-decanol

NIR news ◽  
2019 ◽  
Vol 30 (3) ◽  
pp. 6-8
Author(s):  
Mirosław Antoni Czarnecki ◽  
Michał Kwaśniewicz
Keyword(s):  
Principal Component Analysis ◽  
Chain Length ◽  
Infrared Spectra ◽  
Near Infrared ◽  
Principal Component ◽  
Pure Liquid ◽  
Chemometric Methods ◽  
Near Infrared Spectra ◽  
Similarities And Differences ◽  
Self Association

This work shows the effect of the chain length on near-infrared spectra of 1-alcohols and is based on a recent paper by Kwaśniewicz and Czarnecki ( Appl Spectrosc 2018, 72: 288). Near-infrared spectra of 1-alcohols from methanol to 1-decanol in the pure liquid phase were recorded from 5200 to 9000 cm−1. The similarities and differences between the spectra were analyzed by the classical and chemometric methods (principal component analysis). The obtained results reveal that the near-infrared spectra of methanol, ethanol, and 1-propanol are appreciably different from the spectra of higher 1-alcohols. As shown, the degree of self-association of 1-alcohols decreases with the increase in the chain length.

Comparisons of Environmental Ordinations with Principal Component Vegetational Ordinations for Sets of Data Having Different Degrees of Complexity

1971 ◽  
Vol 1 (2) ◽  
pp. 99-112 ◽  
Author(s):  
J. K. Jeglum ◽  
C. F. Wehrhahn ◽  
J. M. A. Swan
Keyword(s):  
Principal Component Analysis ◽  
Water Level ◽  
Principal Component ◽  
Low Complexity ◽  
Component Analysis ◽  
Two Dimensional ◽  
High Complexity ◽  
Water Conductivity ◽  
Data Set ◽  
Total Data

Data from a survey of lowland, mainly peatland, vegetation were subjected to environmental ordination based on measurements of water level and water conductivity, and to vegetational ordination derived from principal component analysis (P.C.A.). Analyzed were the total set of the data ("all types"), half sets ("nonwoody" and "woody types") and quarter sets (stands of "marshes", "meadows", "shrub fens", and "other woody types"); the number of distinct physiognomic groups in a set of data, and presumably the amount of contained heterogeneity, decreased at each segmentation.The effectiveness of the ordination models was tested by correlating measured distances in two-dimensional ordination models with 2W/(A + B) indices of vegetational similarity for randomly selected pairs of types or stands. As the physiognomic complexity decreased, the effectiveness of the P.C.A. vegetational ordination increased whereas that of the environmental ordination decreased. The environmental ordination seemed most appropriate to the data encompassing high complexity (total data set), while the P.C.A. vegetational ordination seemed most appropriate to data with low complexity (quarter sets of the data).

Use of Near-Infrared–Mid-Infrared Dual-Wavelength Spectrometry to Obtain Two-Dimensional Difference Spectra of Sesame Oil as Inactive Drug Ingredient

2020 ◽  
pp. 000370282096919
Author(s):  
Masahiro Watari ◽  
Akifumi Nagamoto ◽  
Takuma Genkawa ◽  
Shigeaki Morita
Keyword(s):  
Room Temperature ◽  
Near Infrared ◽  
Sesame Oil ◽  
Partial Least Square ◽  
Dual Wavelength ◽  
Two Dimensional ◽  
Difference Spectra ◽  
Mid Infrared ◽  
Starting Point ◽  
Drug Ingredient

The present study has investigated the transformation of sesame oil kept at low temperature during a definite period of time for refinement (called winterization) as an inactive drug ingredient by using two-dimensional difference spectra (2D-DS) analysis of spectra collected using a near-infrared (NIR) and mid-infrared (MIR) dual-wavelength spectrometer (NIR–MIR-DWS). The NIR and MIR spectra were measured nearly simultaneously from samples of sesame oil before and after winterization. The difference spectrum analysis of the obtained NIR–MIR data elucidated that, after the winterization process, the absorbances at peaks attributed to C=O, C=C, and OH groups decrease while the absorbances arising from the main chain (CH2) increase. The result indicated the removal of lignan and the fatty acids with relatively short main chains. Moreover, sesame oil unwinterized was cooled from room temperature to near 1 ℃ and subsequently warmed to room temperature. And the cycle was repeated two times. Real-time monitoring during the cooling and warming processes were carried out using the NIR-MIR-DWS. The prediction results obtained from partial least square calibration model for the temperature suggests that there are subtle differences in the oil composition between the first cooling process and after the warming and cooling cycle. For the more detailed analysis, the 2D-DS method is proposed. The results of the analyses using 2D-DS revealed that the starting point of the transformation is around 15 ℃. It can be estimated that sesame oil is mainly transformed by the first cooling down. Moreover, it was implied that the structure of methylene (CH2) was significantly related to the modifications in sesame oil with temperature change. A series of experimental results elucidated that the winterization of sesame oil removed its impurities and stabilized its conditions. These results are probably the first report on the effect of the winterization process on sesame oil.

Multiple-Perturbation Two-Dimensional Near-Infrared Correlation Study of Time-Dependent Water Absorption Behavior of Cellulose Affected by Pressure

2013 ◽  
Vol 67 (2) ◽  
pp. 163-170 ◽  
Author(s):  
Hideyuki Shinzawa ◽  
Kimie Awa ◽  
Isao Noda ◽  
Yukihiro Ozaki
Keyword(s):  
Water Absorption ◽  
Packing Density ◽  
Near Infrared ◽  
Correlation Method ◽  
Underlying Mechanism ◽  
Polymer Structure ◽  
Correlation Study ◽  
Time Dependent ◽  
Two Dimensional ◽  
Spectral Changes

Transient water absorption by cellulosic samples manufactured under varying pressure was monitored by near-infrared spectroscopy to explore the absorption behavior affected by the pressure. A substantial level of variation of the spectral features was induced by the water absorption and changes in the pressure. The detail of the spectral changes was analyzed with a multiple-perturbation, two-dimensional (2D) correlation method to determine the underlying mechanism. The 2D correlation spectra indicated that the compression of the cellulose increased the packing density of the samples, preventing the penetration of water. In addition, the compression substantially disintegrated its crystalline structure and eventually resulted in the development of inter- and intrachain hydrogen-bonded structures arising from an interaction between the water and cellulose. Consequently, the cellulose samples essentially underwent an evolutionary change in the polymer structure as well as in the packing density during the compression. This structural change, in turn, led to the seemingly complicated absorption trends, depending on the pressure.

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