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NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

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...

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A Protocol for Real-time 3D Single Particle Tracking
10:16

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Published on: January 3, 2018

On the correction of errors in some multiple particle tracking experiments.

Christopher J Rowlands1, Peter T C So

  • 1Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.

Applied Physics Letters
|February 14, 2013
PubMed
Summary
This summary is machine-generated.

Particle tracking experiments can have errors, especially when tracking few particles. This study offers a model showing measured displacement can be 50% lower than actual values.

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Area of Science:

  • Physics
  • Physical Chemistry
  • Biophysics

Background:

  • Particle tracking is crucial for studying dynamic processes in various scientific fields.
  • Errors in particle tracking can lead to misinterpretations of experimental data.
  • Quantifying and understanding these errors is essential for reliable scientific conclusions.

Purpose of the Study:

  • To identify a common source of error in particle tracking experiments.
  • To develop a theoretical model for quantifying this particle tracking error.
  • To validate the model using simulations and experimental data.

Main Methods:

  • Theoretical modeling of particle tracking errors.
  • Numerical simulations to test the model's predictions.
  • Experimental validation using polystyrene microspheres in water.

Main Results:

  • A common source of error in particle tracking experiments was identified.
  • The developed theoretical model accurately predicts the magnitude of the error.
  • The error can cause measured mean squared displacement to be up to 50% smaller than the actual value in systems with few tracked particles.

Conclusions:

  • The study provides a theoretical framework to understand and correct for a specific error in particle tracking.
  • The findings are significant for experiments involving a limited number of tracked particles, such as single-particle tracking.
  • Validated model enhances the accuracy of particle tracking analysis in physical and biological sciences.