Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

IR Spectrometers01:25

IR Spectrometers

2.7K
There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...
2.7K
Infrared (IR) Spectroscopy: Overview01:09

Infrared (IR) Spectroscopy: Overview

5.3K
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.
Different compounds display unique properties due to their...
5.3K
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

2.0K
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...
2.0K
IR Spectroscopy: Molecular Vibration Overview01:24

IR Spectroscopy: Molecular Vibration Overview

4.9K
When Infrared (IR) radiation passes through a covalently bonded molecule, the bonds transition from lower to higher vibrational levels. The fundamental vibrational motions that result in infrared absorption can be classified as stretching or bending vibrations.
Stretching vibrations are vibrational motions that occur along the bond line, changing the bond length or distance between two bonded atoms. They are further distinguished as symmetric or asymmetric. In symmetric stretching, the...
4.9K
IR Frequency Region: X–H Stretching01:24

IR Frequency Region: X–H Stretching

1.5K
In IR spectroscopy, signals produced by the X−H bonds (such as C−H, O−H, or N−H) can be observed in the frequency range of  2700–4000 cm–1. The C−H stretching vibration forms sharp bands in the region 2850–3000 cm–1. The presence of the O−H stretching vibration leads to the forming of an absorption band in the frequency range 3650–3200 cm−1. At the same time, N−H stretching can be confirmed by absorption bands in...
1.5K
IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

1.9K
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...
1.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Survivin, the promising target in hepatocellular carcinoma gene therapy.

Cancer biology & therapy·2008
Same author

Curcumin protects dopaminergic neuron against LPS induced neurotoxicity in primary rat neuron/glia culture.

Neurochemical research·2008
Same author

Cellular mechanisms of reduced sarcoplasmic reticulum Ca2+ content in L-thyroxin induced rat ventricular hypertrophy.

Acta pharmacologica Sinica·2008
Same author

Promoting the formation and stabilization of G-quadruplex by dinuclear RuII complex Ru2(obip)L4.

Inorganic chemistry·2008
Same author

Identification of direct target genes using joint sequence and expression likelihood with application to DAF-16.

PloS one·2008
Same author

In vitro and in vivo investigations on the antiviral activity of a series of mixed-valence rare earth borotungstate heteropoly blues.

European journal of medicinal chemistry·2008

Related Experiment Video

Updated: Feb 19, 2026

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing
10:42

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing

Published on: March 22, 2019

6.6K

Digital demodulation algorithm based on frequency correction for the near-infrared spectrometer.

Jingru Wang, Zhihong Wang, Yuzhe Wang

    Applied Optics
    |November 2, 2017
    PubMed
    Summary
    This summary is machine-generated.

    An improved digital demodulation algorithm enhances scanning near-infrared spectrometer accuracy by correcting frequency fluctuations. This method significantly boosts the signal-to-noise ratio, ensuring more reliable spectral data with minimal impact on measurement time.

    More Related Videos

    Characterizing Far-infrared Laser Emissions and the Measurement of Their Frequencies
    09:38

    Characterizing Far-infrared Laser Emissions and the Measurement of Their Frequencies

    Published on: December 18, 2015

    12.7K
    O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
    06:50

    O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

    Published on: November 8, 2019

    7.1K

    Related Experiment Videos

    Last Updated: Feb 19, 2026

    Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing
    10:42

    Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing

    Published on: March 22, 2019

    6.6K
    Characterizing Far-infrared Laser Emissions and the Measurement of Their Frequencies
    09:38

    Characterizing Far-infrared Laser Emissions and the Measurement of Their Frequencies

    Published on: December 18, 2015

    12.7K
    O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
    06:50

    O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

    Published on: November 8, 2019

    7.1K

    Area of Science:

    • Spectroscopy
    • Optical Engineering
    • Signal Processing

    Background:

    • Traditional digital demodulation in spectrometers requires sampling frequency to be a multiple of signal frequency.
    • Unstable signal frequencies and fixed sampling rates in spectrometers limit demodulation accuracy.
    • This inaccuracy affects the signal-to-noise ratio (SNR) of spectral data.

    Purpose of the Study:

    • To develop an improved digital demodulation algorithm for scanning near-infrared spectrometers.
    • To enhance the signal-to-noise ratio (SNR) of spectral data by addressing frequency instability.
    • To validate the proposed algorithm through theoretical analysis, simulations, and experimental testing.

    Main Methods:

    • Proposed an improved digital demodulation algorithm incorporating frequency correction.
    • Compared the new algorithm with a traditional average absolute value method.
    • Utilized theoretical analysis, computer simulations, and experimental measurements for validation.

    Main Results:

    • The improved algorithm effectively reduced noise stemming from signal frequency fluctuations.
    • The signal-to-noise ratio (SNR) of spectra improved substantially, increasing from 626 to 1124.
    • Measurement time increased by a minimal 0.73%, demonstrating high efficiency.

    Conclusions:

    • The frequency correction-based digital demodulation algorithm significantly enhances SNR in near-infrared spectroscopy.
    • This method overcomes limitations of traditional algorithms when dealing with unstable signal frequencies.
    • The improved algorithm offers a more accurate and efficient approach for spectral analysis in spectrometers.