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Related Concept Videos

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

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Attenuated total reflectance (ATR) infrared spectroscopy is a powerful analytical technique used to study the composition of materials. It is widely employed in chemistry, materials science, forensic science, and other fields where sample characterization is required. ATR has several advantages over traditional transmission IR spectroscopy, including the requirement of little to no sample preparation and the ability to analyze a wide range of samples.
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IR Frequency Region: Fingerprint Region01:03

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IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
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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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For AAS measurements, samples must be introduced as clear solutions, often requiring extensive preliminary treatment to dissolve materials like soils, animal tissues, and minerals. Common methods for sample preparation include treatment with hot mineral acids, wet ashing, combustion in closed containers, high-temperature ashing, or fusion with reagents.
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Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography
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Cigarette paper as evidence: Forensic profiling using ATR-FTIR spectroscopy and machine learning algorithms.

Muskaan Kapoor1, Akanksha Sharma1, Vishal Sharma1

  • 1Institute of Forensic Science & Criminology, Panjab University Chandigarh, 160014, India.

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Forensic scientists can now identify cigarette paper brands at crime scenes. This study uses spectroscopy and machine learning to differentiate cigarette paper from regular paper, aiding criminal investigations.

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ATR-FTIRBrand differentiationCigarette PaperForensic InvestigationMachine Learning

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Area of Science:

  • Forensic Science
  • Analytical Chemistry
  • Machine Learning

Background:

  • Cigarette paper is often overlooked as crucial forensic evidence.
  • Distinguishing cigarette paper from common paper types is vital for crime scene analysis.

Purpose of the Study:

  • To develop a method for differentiating cigarette paper from other paper materials.
  • To identify specific cigarette paper brands using advanced analytical techniques.

Main Methods:

  • Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy was used for chemical analysis.
  • Principal Component Analysis (PCA) was applied for data dimensionality reduction.
  • Fifteen machine learning (ML) algorithms were evaluated for classification tasks.

Main Results:

  • The CatBoost classifier demonstrated superior performance in distinguishing cigarette paper and identifying brands.
  • The developed method proved effective in differentiating cigarette paper from normal paper.
  • Successful identification of cigarette paper brands was achieved.

Conclusions:

  • ATR-FTIR spectroscopy combined with ML offers a non-destructive and effective approach for cigarette paper analysis in forensics.
  • This technique significantly enhances the value of cigarette paper as forensic evidence.
  • The findings provide valuable tools for crime scene investigations and forensic laboratories.