Optimized Data Analysis Algorithm for On-Site Chemical Identification Using a Hand-Held Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) Spectrometer

2013 ◽  
Vol 67 (12) ◽  
pp. 1395-1400 ◽  
Author(s):  
Izhar Ron ◽  
Amalia Zaltsman ◽  
Shai Kendler
Keyword(s):  
Fourier Transform ◽  
Data Analysis ◽  
Fourier Transform Infrared ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Chemical Identification ◽  
Analysis Algorithm ◽  
Ft Ir

Chemometric Approach to a Rapid Attenuated Total Reflection Fourier Transform Infrared Analysis of Complex Heroin-Based Mixtures

2020 ◽  
pp. 000370282096971
Author(s):  
Nataša Radosavljević Stevanović ◽  
Milena Jovanović ◽  
Federico Marini ◽  
Slavica Ražić
Keyword(s):  
Principal Component Analysis ◽  
Fourier Transform ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Illegal Market ◽  
Ft Ir

Heroin is one of the most frequently seized drugs in Southeastern Europe. Due to the position in the Balkan route, the Republic of Serbia keeps important role in suppression of the trafficking of heroin for domestic and foreign illegal market. This research is aimed to provide a good scientific approach in the field of seized heroin analysis. Two different forms of heroin are present in the illegal market, mostly in mixtures with typical “cutting” agents: caffeine, paracetamol, and sugars. It was observed that the quantity of pure heroin in seized samples slightly increases from year to year. The aim of this study was to produce a reliable and fast procedure for classification of illicit heroin samples and determination of the concentration range of heroin in the samples. For that purpose, the attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) technique was used and combined with such chemometric methods as principal component analysis, cluster analysis, and partial least squares. Principal component analysis (PCA) as an unsupervised model was used for exploratory purposes to identify trends, similarities, and differences between samples by reducing the dimensionality of the data. The cluster classification of examined samples turned out to be extremely useful to evaluate the possibilities of the ATR FT-IR technique to classify the samples appropriately into the patterns, the constituted clusters. Additionally, partial least square was the suitable method for the purpose of determination of the heroin hydrochloride concentration range in examined samples. It is proved that the joined application of spectroscopy and chemometrics can be extremely convenient and useful for forensic and drugs control laboratories.

Novel Attenuated Total Reflection Fourier Transform Infrared Microscopy Using a Gem Quality Diamond as an Internal Reflection Element

2005 ◽  
Vol 59 (10) ◽  
pp. 1236-1241 ◽  
Author(s):  
Sanong Ekgasit ◽  
Pimthong Thongnopkun
Keyword(s):  
Fourier Transform ◽  
Total Internal Reflection ◽  
Fourier Transform Infrared ◽  
Normal Incidence ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Internal Reflection ◽  
The Novel ◽  
Infrared Microscope ◽  
Ft Ir

A novel technique for attenuated total reflection Fourier transform infrared (ATR FT-IR) spectral acquisition by an infrared microscope with a gem-quality faceted diamond as an internal reflection element (IRE) is introduced. Unlike conventional IREs, the novel diamond IRE has a sharp tip configuration instead of a flat tip configuration. Light at normal incidence was coupled into the diamond while the transflected radiation from the diamond was collected through the table facet by the built-in 15× Cassegrainian objective. The number of reflections in the novel diamond IRE equals two. The evanescent field generated under total internal reflection at the pavilion facet was exploited for ATR spectral acquisition of materials attached to the IRE. The observed ATR spectra were compared to those obtained via a traditional zinc selenide IRE.

Multivariate Analysis of Attenuated Total Reflection—Fourier Transform Infrared Spectroscopic Data to Confirm the Origin of Honeys

2008 ◽  
Vol 62 (10) ◽  
pp. 1115-1123 ◽  
Author(s):  
Siobhán Hennessy ◽  
Gerard Downey ◽  
Colm O'Donnell
Keyword(s):  
Fourier Transform ◽  
Discriminant Analysis ◽  
Fourier Transform Infrared ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Correct Classification ◽  
Standard Normal Variate ◽  
Standard Normal ◽  
Ft Ir ◽  
Solids Content

Fourier transform infrared (FT-IR) spectroscopy and chemometrics were used to verify the origin of honey samples ( n = 150) from Europe and South America. Authentic honey samples were collected from five sources, namely unfiltered samples from Mexico in 2004, commercially filtered samples from Ireland and Argentina in 2004, commercially filtered samples from the Czech Republic in 2005 and 2006, and commercially filtered samples from Hungary in 2006. Samples were diluted with distilled water to a standard solids content (70° Brix) and their spectra (2500–12 500 nm) recorded at room temperature using an FT-IR spectrometer equipped with a germanium attenuated total reflection (ATR) accessory. First- and second-derivative and standard normal variate (SNV) data pretreatments were applied to the recorded spectra, which were analyzed using partial least squares (PLS) regression analysis, factorial discriminant analysis (FDA), and soft independent modeling of class analogy (SIMCA). In general, when an attenuated wavelength range (6800–11 500 nm) rather than the whole spectrum (2500–12 500 nm) was studied, higher correct classification rates were achieved. An overall correct classification of 93.3% was obtained for honeys by PLS discriminant analysis, while FDA techniques correctly classified 94.7% of honey samples. Correct classifications of up to 100% were achieved using SIMCA, but models describing some classes had very high false positive rates.

Attenuated Total Reflection (ATR) Micro-Fourier Transform Infrared (Micro-FT-IR) Spectroscopy to Enhance Repeatability and Reproducibility of Spectra Derived from Single Specimen Organic-Walled Dinoflagellate Cysts

2021 ◽  
pp. 000370282110411
Author(s):  
Pjotr Meyvisch ◽  
Pieter R. Gurdebeke ◽  
Henk Vrielinck ◽  
Kenneth Neil Mertens ◽  
Gerard Versteegh ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Fourier Transform Infrared ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Data Sets ◽  
Systematic Exploration ◽  
Ft Ir ◽  
Repeatability And Reproducibility ◽  
Processing Steps ◽  
Ft Ir Spectroscopy

The chemical composition of recent and fossil organic-walled dinoflagellate cyst walls and its diversity is poorly understood and analyses on single microscopic specimens are rare. A series of infrared spectroscopic experiments resulted in the proposition of a standardized attenuated total reflection micro-Fourier transform infrared-based method that allows the collection of robust data sets consisting of spectra from individual dinocysts. These data sets are largely devoid of nonchemical artifacts inherent to other infrared spectrochemical methods, which have typically been used to study similar specimens in the past. The influence of sample preparation, specimen morphology and size and spectral data processing steps is also assessed within this methodological framework. As a result, several guidelines are proposed which facilitate the collection and qualitative interpretation of highly reproducible and repeatable spectrochemical data. These, in turn, pave the way for a systematic exploration of dinocyst chemistry and its assessment as a chemotaxonomical tool or proxy.

scholarly journals Discrimination between human and animal blood by attenuated total reflection Fourier transform-infrared spectroscopy

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Ewelina Mistek-Morabito ◽  
Igor K. Lednev
Keyword(s):  
Fourier Transform ◽  
External Validation ◽  
Fourier Transform Infrared ◽  
Nondestructive Method ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Training Data ◽  
Animal Blood ◽  
Data Set ◽  
Ft Ir

AbstractForensic chemistry is an important area of analytical chemistry. This field has been rapidly growing over the last several decades. Confirmation of the human origins of bloodstains is important in practical forensics. Current serological blood tests are destructive and often provide false positive results. Here, we report on the development of a nondestructive method that could potentially be applied at the scene for differentiation of human and animal blood using attenuated total reflection Fourier transform-infrared (ATR FT-IR) spectroscopy and statistical analysis. The following species were used to build statistical models for binary human–animal blood differentiation: cat, dog, rabbit, horse, cow, pig, opossum, and raccoon. Three other species (deer, elk, and ferret) were used for external validation. A partial least squares discriminant analysis (PLSDA) was used for classification purposes and showed excellent performance in internal cross-validation (CV). The method was externally validated first using blood samples from new donors of species used in the training data set, and second using donors of new species that were not used to construct the model. Both validations showed excellent results demonstrating potential of the developed approach for nondestructive, rapid, and statistically confident discrimination between human and animal blood for forensic purposes.

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