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Related Concept Videos

¹H NMR Signal Integration: Overview00:58

¹H NMR Signal Integration: Overview

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The intensity of a signal, which can be represented by the area under the peak, depends on the number of protons contributing to that signal. The area under each peak is shown as a vertical line called an integral, with the integral value listed under it, as seen in the proton NMR spectrum of benzyl acetate. Each integral value is divided by the smallest integral value to obtain the ratio of the number of protons producing each signal. The ratio reveals the relative number of protons and not...
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¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

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Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...
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Interpreting ¹H NMR Signal Splitting: The (n + 1) Rule01:10

Interpreting ¹H NMR Signal Splitting: The (n + 1) Rule

1.5K
In the AX proton spin system, proton A can sense the two spin states of a coupled proton X, resulting in a doublet NMR signal with two peaks of equal (1:1) intensity. When proton A is coupled to two equivalent protons (AX2 spin system), the spin states of each X can be aligned with or against the external field, creating three possible scenarios. This results in a 1:2:1  triplet signal, where the central peak corresponds to the chemical shift of A and is twice as large or intense as the...
1.5K
NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

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When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
787
Effective Value of a Periodic Waveform01:07

Effective Value of a Periodic Waveform

726
The concept of effective value, the root mean square (RMS) value, is crucial in understanding electrical circuits and power delivery. This idea emerges from the necessity to measure the effectiveness of a voltage or current source in supplying power to a resistive load.
The effective value of a periodic current represents the direct current (DC) that conveys the same average power to a resistor as the periodic current itself. This concept is crucial when assessing AC circuits. To determine the...
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Two-Dimensional (2D) NMR: Overview01:12

Two-Dimensional (2D) NMR: Overview

910
The 1D NMR spectrum of large and complex molecules like natural products has complicated splitting patterns and overlapping signals, which can be easily interpreted using 2-dimensional (2D) NMR. Unlike 1D NMR, 2D NMR has two frequency axes that provide the coupling information between the nucleus A and nucleus B in a molecule. The process from which 2D spectra are obtained has four steps.
The first step is the preparation period, during which nucleus A is excited with a radiofrequency pulse....
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Related Experiment Video

Updated: Sep 25, 2025

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
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How to Resolve the Maximum Valuable Information in Complex NIR Signal: A Practicable Method Based on Wavelet

Jing Chen1, Xiaoquan Lu1

  • 1Key Lab of Bioelectrochemistry and Environmental Analysis of Gansu, College of Chemistry and Chemical Engineering, Northwest Normal University, Lanzhou, China.

Frontiers in Chemistry
|April 25, 2022
PubMed
Summary
This summary is machine-generated.

Extracting maximum information from complex near-infrared (NIR) signals is challenging. This study proposes a Wavelet Transform (WT) method to effectively resolve NIR signals and obtain valuable data for researchers.

Keywords:
near infrared spectrumresidual error sum of squareroot mean square erroruninformative variable eliminationwavelet transform (CWT)

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Area of Science:

  • Spectroscopy
  • Signal Processing

Background:

  • Near-infrared (NIR) spectroscopy generates complex signals.
  • Extracting meaningful information from these signals is a significant challenge in the field.

Purpose of the Study:

  • To propose a novel method for maximum information extraction from complex NIR signals.
  • To aid researchers in resolving and analyzing NIR spectral data effectively.

Main Methods:

  • A maximum information extraction technique was developed.
  • Wavelet Transform (WT) was the core methodology employed for signal processing.

Main Results:

  • The proposed method demonstrated effectiveness in extracting valuable information.
  • The technique successfully resolved complex features within NIR signals.

Conclusions:

  • The Wavelet Transform-based method is an effective tool for NIR spectrum analysis.
  • This approach enhances the ability to derive maximum insights from NIR studies.