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Related Concept Videos

Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

2.6K
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...
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Raman Spectroscopy Instrumentation: Overview01:26

Raman Spectroscopy Instrumentation: Overview

1.8K
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...
1.8K
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

1.3K
When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
1.3K
IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

2.0K
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...
2.0K
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

2.1K
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...
2.1K
IR Spectrum Peak Broadening: Hydrogen Bonding01:23

IR Spectrum Peak Broadening: Hydrogen Bonding

1.9K
The vibrational frequency of a bond is directly proportional to its bond strength. As a result, stronger bonds vibrate at higher frequencies, while weaker bonds vibrate at lower frequencies. The stretching vibration of the strong O–H bond in alcohols and phenols (very dilute solution or gas phase) appears as a sharp peak at 3600–3650 cm−1.
However, the extent of hydrogen bonding influences the observed stretching frequency and band broadening. Intermolecular or intramolecular...
1.9K

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Ultrafast Time-resolved Near-IR Stimulated Raman Measurements of Functional π-conjugate Systems
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[A new peak detection algorithm of Raman spectra].

Cheng-Zhi Jiang, Qiang Sun, Ying Liu

    Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
    |May 3, 2014
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    A new bi-scale correlation algorithm enhances Raman peak identification. It offers faster processing and higher accuracy than traditional methods, requiring no pre-processing for effective Raman spectral analysis.

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    Area of Science:

    • Spectroscopy
    • Analytical Chemistry

    Context:

    • Raman spectroscopy is crucial for material analysis.
    • Accurate peak identification is essential for interpreting Raman spectra.
    • Existing methods like continuous wavelet transform have limitations.

    Purpose:

    • To introduce a novel, efficient, and accurate Raman peak recognition method.
    • To compare the bi-scale correlation algorithm with the continuous wavelet transform method.
    • To validate the algorithm's performance on real-world Raman spectra.

    Summary:

    • The bi-scale correlation algorithm combines correlation coefficient and local signal-to-noise ratio for Raman peak identification.
    • It achieves an average identification time of 0.51 seconds, outperforming the 0.71 seconds of continuous wavelet transform.
    • Recognition accuracy exceeds 99% for signal-to-noise ratios >= 6, with lower peak position error compared to traditional methods.

    Impact:

    • The algorithm provides automated, high-speed, and accurate Raman peak identification.
    • It eliminates the need for de-noising and background removal, simplifying spectral analysis.
    • Demonstrates superior performance and operability for practical Raman spectroscopy applications.