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Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

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The underlying principle of Raman spectroscopy is based on the interaction between light and matter, specifically molecules' inelastic scattering of photons. When a monochromatic beam of light, typically from a laser source, interacts with a sample, most scattered light has the same frequency as the incident light. This is known as Rayleigh scattering.
However, a small fraction of the scattered light exhibits a frequency shift due to the exchange of energy between the incident photons and...
456
Raman Spectroscopy Instrumentation: Overview01:26

Raman Spectroscopy Instrumentation: Overview

450
A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
The monochromatic laser source, typically using visible or near-infrared radiation, generates a highly focused beam of light. This light interacts with the molecules of the sample, scattering some of the light. Liquid and gaseous samples are usually tested in ordinary glass capillaries, while solids can be analyzed as powders packed in capillaries or as potassium...
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Applications of IR Spectroscopy: Overview01:11

Applications of IR Spectroscopy: Overview

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The non-destructive nature and ability to provide valuable chemical information make IR spectroscopy a versatile technique with broad applications in various scientific and industrial fields. IR spectroscopy is commonly used to identify and characterize organic and inorganic compounds. It provides information about the functional groups present in a molecule and the bonding between atoms. This helps in the structural elucidation of compounds during organic synthesis, pharmaceutical research,...
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IR and UV–Vis Spectroscopy of Carboxylic Acids01:28

IR and UV–Vis Spectroscopy of Carboxylic Acids

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In IR spectroscopy of carboxylic acids, the C=O bond shows a characteristic band between 1710 and 1760 cm⁻¹, and the O–H bond exhibits a broad band between 2500 and 3300 cm⁻¹.
However, the stretching absorptions for the C=O bond vary depending on the structure of carboxylic acids. The C=O bond of the free carboxylic acids shows a higher stretching frequency, 1760 cm−1, while H-bonded carboxylic acids (dimers) exhibit stretching absorptions at a lower frequency,...
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Updated: Jul 20, 2025

Raman and IR Spectroelectrochemical Methods as Tools to Analyze Conjugated Organic Compounds
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Raman and IR Spectroelectrochemical Methods as Tools to Analyze Conjugated Organic Compounds

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Raman Spectroscopy to Enhance Investigative Lead Information in Automotive Clearcoats.

George P Affadu-Danful1, Haoran Zhong1, Kaushalya Sharma Dahal1

  • 1Department of Chemistry, Oklahoma State University, Stillwater, OK, USA.

Applied Spectroscopy
|August 1, 2023
PubMed
Summary

Raman microscopy can identify vehicle make and model from paint chips, outperforming traditional Fourier transform infrared spectroscopy (FT-IR) in forensic investigations. This advanced technique aids hit-and-run case analysis.

Keywords:
Forensic automotive paint analysisRaman spectroscopyautomotive clearcoatsbaseline correctionchemometricsgenetic algorithmspattern recognitiontrace evidence

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Area of Science:

  • Forensic Science
  • Analytical Chemistry
  • Materials Science

Background:

  • Automotive paint analysis is crucial for vehicle-related crime investigations, particularly hit-and-run fatalities.
  • Current methods like Fourier transform infrared spectroscopy (FT-IR) have limitations in discriminating between similar automotive paint samples.
  • Developing more precise analytical techniques is essential for forensic science.

Purpose of the Study:

  • To develop and evaluate a novel method for identifying vehicle make and model using Raman microscopy on automotive paint samples.
  • To assess the discriminatory power of Raman spectroscopy compared to FT-IR for automotive clearcoats.
  • To investigate the effectiveness of a genetic algorithm for pattern recognition in classifying paint spectra.

Main Methods:

  • Collected Raman spectra from 118 automotive paint samples across six General Motors (GM) assembly plants.
  • Utilized a genetic algorithm for pattern recognition, incorporating model inference and sample error in variable selection.
  • Compared the discrimination capabilities of Raman spectroscopy with FT-IR for the same paint samples.

Main Results:

  • Raman spectroscopy successfully discriminated between paint samples from six different GM assembly plants (representing specific vehicle models).
  • A specific spectral region (1802–697 cm⁻¹) proved highly effective for discrimination.
  • FT-IR could only differentiate one out of the six assembly plants, highlighting Raman's superior performance.

Conclusions:

  • Raman spectroscopy, coupled with genetic algorithm pattern recognition, offers significant advantages over FT-IR for automotive clearcoat identification.
  • This method provides a powerful new tool for forensic analysis of paint evidence in vehicle-related incidents.
  • The findings support the adoption of Raman microscopy in forensic laboratories for enhanced vehicle identification.