Iterative least-squares fit procedures for the identification of organic vapor mixtures by Fourier-transform infrared spectrophotometry

1989 ◽  
Vol 61 (24) ◽  
pp. 2708-2714 ◽  
Author(s):  
Hongkui. Xiao ◽  
Steven P. Levine ◽  
James B. D'Arcy
Keyword(s):  
Fourier Transform ◽  
Least Squares ◽  
Fourier Transform Infrared ◽  
Infrared Spectrophotometry ◽  
Organic Vapor ◽  
Least Squares Fit ◽  
Vapor Mixtures

A Fourier Transform Infrared Study of Mineral Matter in Coal: The Application of a Least Squares Curve-Fitting Program

1981 ◽  
Vol 35 (1) ◽  
pp. 102-106 ◽  
Author(s):  
Paul C. Painter ◽  
Susan M. Rimmer ◽  
Randy W. Snyder ◽  
Alan Davis
Keyword(s):  
Fourier Transform ◽  
Least Squares ◽  
Curve Fitting ◽  
Fourier Transform Infrared ◽  
Mineral Matter ◽  
Infrared Study ◽  
Least Squares Curve Fitting ◽  
Mineral Mixtures ◽  
Good Agreement

The application of Fourier transform infrared spectroscopy to the quantitative determination of mineral matter in coal is discussed. The use of a least squares curve-fitting program allows a choice between standards to be made. The results of an analysis of mineral mixtures and a coal low temperature ash are presented. The results are in good agreement with known concentrations and those obtained by other methods of analysis.

scholarly journals Application of Fourier Transform Infrared Spectrophotometry Method for Analysis of Metformin Hydrochloride in Marketed Tablet Dosage Form

2021 ◽  
Vol 7 (2) ◽  
pp. 168-177
Author(s):  
Nerdy Nerdy ◽  
Linda Margata ◽  
Dian Ika Perbina Meliala ◽  
Bunga Mari Sembiring ◽  
Selamat Ginting ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Dosage Form ◽  
Limit Of Detection ◽  
Fourier Transform Infrared ◽  
Metformin Hydrochloride ◽  
Infrared Spectrophotometry ◽  
Relative Standard ◽  
Limit Of Quantitation ◽  
The Fourier Transform ◽  
Tablet Dosage

The first line drug given for monotherapy for diabetes mellitus type 2 is metformin hydrochloride, which is a biguanide antihyperglycemic drug. The aim of this research was to develop, validate, and apply the Fourier Transform Infrared spectrophotometry method to identify and determine metformin hydrochloride in marketed tablet dosage form. This research included preparation of standard, analysis of samples, and validation of method. The specific wavenumber obtained for qualitative analysis was 1645.68 cm–1 and 1574.8 cm–1. The specific area obtained for quantitative analysis with a single baseline ranged from 1701.53 cm–1 to 1535.66 cm–1. All metformin hydrochloride marketed tablet dosage forms were analyzed and met all of the qualitative and quantitative requirements. The methods met the requirements of method validation for accuracy with a percentage of recovery of 100.22 %, precision with relative standard deviation of 0.48 %, linearity with a correlation coefficient of 0.9992, limit of detection of 11.17 mg per mL, limit of quantitation of 33.84 mg per mL, and good specificity results. In this study, the Fourier Transform Infrared spectrophotometry method was successfully developed and validated for application in identification and determination of metformin hydrochloride in marketed tablet dosage form.

scholarly journals Partial Least Squares (PLS) Integrated Fourier Transform Infrared (FTIR) Approach for Prediction of Moisture in Transformer Oil and Lubricating Oil

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Siong Fong Sim ◽  
Amelia Laccy Jeffrey Kimura
Keyword(s):  
Fourier Transform ◽  
Least Squares ◽  
Partial Least Squares ◽  
Fourier Transform Infrared ◽  
Ftir Spectra ◽  
Transformer Oil ◽  
Lubricating Oil ◽  
Least Squares Regression ◽  
Promising Alternative ◽  
Karl Fischer

Fourier transform infrared (FTIR) spectroscopy has been advocating a promising alternative for Karl Fischer titration method for quantification of moisture in oil. This study aims to integrate partial least squares regression (PLSR) approach on FTIR spectra for prediction of moisture in locally accessible transformer oil and lubricating oil. The oil samples spiked with known moisture concentrations were extracted with acetonitrile and subjected to analysis with an FTIR spectrophotometer. The PLSR model was built based on 100 training/test splits, and the prediction performance was measured with the percentage root mean squares error (% RMSE). The range of concentration studied was between 0 and 5000 ppm. The marker region of moisture was found at 3750–3400 and 1700–1600 cm−1 with the latter demonstrating a better predictive ability in both lubricating oil and transformer oil. The prediction of moisture in lubricating oil was characterized with lower % RMSE. At concentration less than 700 ppm, the prediction accuracy deteriorates suggesting poor sensitivity. The PLSR was implemented on IR spectra of a set of blind samples, verified with Karl Fischer (for transformer oil) method and Kittiwake (for lubricating oil) method. The prediction was encouraging at concentrations above 1000 ppm; at lower concentrations, the prediction was characterized with high percent error. The algorithm, validated with 100 training/test splits, was converted into an executable program for prediction of moisture based on FTIR spectra. This program can be used for prediction of other substances given that the marker region is identified. FTIR can be used for prediction of moisture in oil nevertheless the sensitivity and precision is low for samples with low moisture concentration.

scholarly journals Rapid Quantitative Analysis of Forest Biomass Using Fourier Transform Infrared Spectroscopy and Partial Least Squares Regression

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Gifty E. Acquah ◽  
Brian K. Via ◽  
Oladiran O. Fasina ◽  
Lori G. Eckhardt
Keyword(s):  
Fourier Transform ◽  
Chemical Composition ◽  
Ftir Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Fourier Transform Infrared ◽  
Least Squares Regression ◽  
Forest Logging ◽  
Logging Residue

Fourier transform infrared reflectance (FTIR) spectroscopy has been used to predict properties of forest logging residue, a very heterogeneous feedstock material. Properties studied included the chemical composition, thermal reactivity, and energy content. The ability to rapidly determine these properties is vital in the optimization of conversion technologies for the successful commercialization of biobased products. Partial least squares regression of first derivative treated FTIR spectra had good correlations with the conventionally measured properties. For the chemical composition, constructed models generally did a better job of predicting the extractives and lignin content than the carbohydrates. In predicting the thermochemical properties, models for volatile matter and fixed carbon performed very well (i.e.,R2> 0.80, RPD > 2.0). The effect of reducing the wavenumber range to the fingerprint region for PLS modeling and the relationship between the chemical composition and higher heating value of logging residue were also explored. This study is new and different in that it is the first to use FTIR spectroscopy to quantitatively analyze forest logging residue, an abundant resource that can be used as a feedstock in the emerging low carbon economy. Furthermore, it provides a complete and systematic characterization of this heterogeneous raw material.

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