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Two-Dimensional (2D) NMR: Overview01:12

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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.
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The resolution of a mass spectrometer depends on the efficiency of separating ions with different ion masses. The mass of an atom is approximated to the sum of the masses of protons and neutrons inside, considering the masses of protons and neutrons as equal. However, the masses of the proton (1.6726 × 10−24 g) and neutron (1.6749 × 10−24 g) are not truly equal. There is a minor error in the expression of atomic masses relative to the simplest atom of hydrogen. For...
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Related Experiment Video

Updated: May 6, 2026

Three-Dimensional Particle Shape Analysis Using X-ray Computed Tomography: Experimental Procedure and Analysis Algorithms for Metal Powders
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Nanoparticle characterisation via 2D classification using single particle averaging.

Iain Harley1, Anke Kaltbeitzel1, Francesca Mazzotta1

  • 1Max Planck Institute for Polymer Research, Ackermannweg 10, 55128 Mainz, Germany. lieberw@mpip-mainz.mpg.de.

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Summary

This study introduces 2D class averaging (2D-CA) for nanoparticle (NP) characterization, offering accurate size distribution analysis for complex NP systems. This novel approach overcomes limitations of traditional methods, even for challenging samples like agglomerated NPs.

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Area of Science:

  • Nanotechnology
  • Materials Science
  • Biophysics

Background:

  • Characterizing nanoparticle (NP) size and morphology, particularly in complex structures like core-shell particles and nanocapsules, is challenging with conventional methods.
  • Existing techniques often face limitations in resolution and applicability to diverse NP systems.

Purpose of the Study:

  • To introduce and validate a novel image-based nanoparticle characterization method using 2D class averaging (2D-CA).
  • To demonstrate the applicability of 2D-CA for analyzing diverse and challenging nanoparticle systems.

Main Methods:

  • Utilized 2D class averaging (2D-CA) techniques from single particle analysis, adapted from structural biology software.
  • Applied the method to various nanoparticle systems including nanocapsules, nanorods, and bimodal distributions.
  • Validated the technique through comparative studies against established characterization methods.

Main Results:

  • 2D-CA provides detailed size distribution analysis for diverse nanoparticle systems.
  • The method effectively characterizes challenging samples, including highly agglomerated nanoparticles, inaccessible to conventional techniques.
  • Demonstrated statistically robust results with minimal human bias via automated particle identification.

Conclusions:

  • 2D-CA offers a powerful and accurate approach for nanoparticle size and morphology characterization.
  • This method enhances the analysis of complex and challenging nanoparticle systems.
  • Leveraging established software streamlines the workflow for processing large numbers of micrographs.