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Related Concept Videos

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

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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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Infrared (IR) Spectroscopy: Overview01:09

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When electromagnetic radiation passes through a material, atoms or molecules transition from a lower to a higher energy state by absorbing radiation corresponding to the energy difference between the two states. The absorption of infrared (IR) radiation causes transitions between vibrational energy levels in a molecule. Therefore, IR spectroscopy is a useful analytical tool for determining the molecular structure of molecules.
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IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration01:16

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A covalently bonded heteronuclear diatomic molecule can be modeled as two vibrating masses connected by a spring. The vibrational frequency of the bond can be expressed using an equation derived from Hooke's law, which describes how the force applied to stretch or compress a spring is proportional to the displacement of the spring. In this case, the atoms behave like masses, and the bond acts like a spring.
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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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Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single...
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A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
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Related Experiment Video

Updated: Dec 23, 2025

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
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Variable Screening for Near Infrared (NIR) Spectroscopy Data Based on Ridge Partial Least Squares Regression.

Naifei Zhao1, Qingsong Xu2, Man-Lai Tang3

  • 1School of Mathematics and Statistics, Changsha University of Science & Technology, Changsha, P.R. China

Combinatorial Chemistry & High Throughput Screening
|April 29, 2020
PubMed
Summary

A new variable screening method for Near Infrared (NIR) spectroscopy effectively handles highly correlated data and small sample sizes. This approach improves quantitative analysis accuracy in complex datasets.

Keywords:
Puffer transformationnear infrared (NIR) spectroscopy datapreconditioningridge partial least squares regressionsure independence screening (SIS)variable screening

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Area of Science:

  • Chemometrics
  • Spectroscopy
  • Data Analysis

Background:

  • Near Infrared (NIR) spectroscopy generates large datasets with numerous correlated variables.
  • Traditional variable screening methods struggle with high dimensionality and multicollinearity.
  • Partial Least Squares (PLS) regression offers an alternative for complex NIR data analysis.

Purpose of the Study:

  • To propose a fast variable screening strategy for NIR spectroscopy data.
  • To address challenges posed by high-dimensional and highly correlated covariates.
  • To improve the accuracy of quantitative analysis in NIR spectroscopy.

Main Methods:

  • Introduced a preconditioned screening for ridge partial least squares regression (PSRPLS).
  • Utilized Puffer transformation to simplify variable screening with correlated predictors.
  • Applied Ridge Partial Least Squares (RPLS) regression for computational efficiency.

Main Results:

  • The proposed PSRPLS method demonstrates theoretically consistent model selection.
  • Effectiveness validated through four simulation studies and two real-world NIR datasets.
  • Puffer transformation successfully mitigates issues arising from high correlation.

Conclusions:

  • The developed PSRPLS approach effectively handles high correlation in NIR data.
  • RPLS regression enhances simplicity and computational efficiency for large models.
  • The method maintains high prediction precision even when model size exceeds sample size.