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Related Concept Videos

IR Spectrometers01:25

IR Spectrometers

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...
Aliasing01:18

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original signal...
Discrete Fourier Transform01:15

Discrete Fourier Transform

The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
Atomic Spectroscopy: Absorption, Emission, and Fluorescence01:23

Atomic Spectroscopy: Absorption, Emission, and Fluorescence

Atomic spectroscopy is a vital tool in elemental analysis, both qualitatively and quantitatively. It can be broadly divided into optical spectroscopy, mass spectroscopy, and X-ray spectroscopy methods. The optical spectroscopic methods are atomic absorption spectroscopy (AAS), atomic emission spectroscopy (AES), and atomic fluorescence spectroscopy (AFS). The first step in all three methods is atomization, where the solid, liquid, or solution-phase samples are converted into gas-phase atoms and...
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

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 C=O, C=N, and C=C occur between 1600–1850 cm−1.
The...
Atomic Absorption Spectroscopy: Interference01:25

Atomic Absorption Spectroscopy: Interference

Interference leads to systematic error in atomic absorption (AA) measurements by enhancing or diminishing the analytical signal or the background. These interferences can be grouped into three main categories: spectral interference, chemical interference, and physical interference.
Spectral interference occurs when signals from other elements or molecules overlap with the analyte signal, falsely elevating or masking the analyte's absorbance. This interference can be corrected using Zeeman,...

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A Multimodal Wide-Field Fourier-Transform Raman Microscope
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Ghosts and artifacts in Fourier-transform spectrometry.

R C Learner, A P Thorne, J W Brault

    Applied Optics
    |November 19, 2010
    PubMed
    Summary
    This summary is machine-generated.

    Ghosts in Fourier-transform spectrometry (FTS) can cause spectral analysis errors and limit signal quality. This study details ghost types, their origins, and methods for identification and mitigation in FTS data.

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    Area of Science:

    • Spectroscopy
    • Analytical Chemistry
    • Physical Chemistry

    Background:

    • Ghosts are artifacts in Fourier-transform spectrometry (FTS) that impact spectral data quality.
    • Understanding these artifacts is crucial for accurate spectral analysis and interpretation.

    Purpose of the Study:

    • To elucidate the significance of ghosts in FTS.
    • To describe various ghost types and their origins.
    • To provide methods for ghost identification and mitigation.

    Main Methods:

    • Review and discussion of ghost origins (amplitude modulation, phase modulation, intermodulation).
    • Analysis of hardware and software artifacts contributing to ghosts.
    • Development of strategies for ghost detection and avoidance.

    Main Results:

    • Ghosts introduce spurious frequency differences, distort phase correction, and reduce signal-to-noise ratio.
    • Different modulation types lead to distinct ghost characteristics.
    • Practical techniques for identifying and minimizing ghost effects are presented.

    Conclusions:

    • Effective management of ghosts is essential for reliable FTS measurements.
    • The provided guidance aids researchers in improving spectral accuracy and data quality.
    • Addressing ghosts enhances the overall utility of Fourier-transform spectrometry.