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Related Concept Videos

Insensitive Nuclei Enhanced by Polarization Transfer (INEPT)01:15

Insensitive Nuclei Enhanced by Polarization Transfer (INEPT)

Insensitive Nuclei Enhanced by Polarization Transfer (INEPT) is an advanced Nuclear Magnetic Resonance (NMR) technique specifically designed to detect and enhance the signals of low-abundance nuclei, such as carbon-13 and nitrogen-15, in small molecules. The fundamental principle behind INEPT is the transfer of polarization from a more abundant and highly polarizable nucleus, typically hydrogen-1, to the low-abundance nucleus of interest. This process effectively boosts the NMR signal of the...
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Irradiation of a spin-active nucleus causes an increase or decrease in the signal intensity of neighboring nuclei that are not necessarily chemically bonded or involved in J-coupling. This phenomenon, called the nuclear Overhauser enhancement (NOE), results from through-space interactions between the nuclear spins. The NOE effect decreases with increasing internuclear distance and is generally not observed beyond 4 angstroms. In NOE, dipole-dipole interactions between neighboring spin-active...
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¹H NMR: Interpreting Distorted and Overlapping Signals

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 slanted or...

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Related Experiment Video

Updated: Jun 23, 2026

Coulomb Explosion Imaging as a Tool to Distinguish Between Stereoisomers
08:51

Coulomb Explosion Imaging as a Tool to Distinguish Between Stereoisomers

Published on: August 18, 2017

Neural network based molecular structure retrieval from Coulomb explosion imaging data.

A Ghanaatian1, A K Ravi2, J Stallbaumer3

  • 1Department of Computer Science, Kansas State University, Manhattan, Kansas 66506, USA.

The Journal of Chemical Physics
|June 22, 2026
PubMed
Summary
This summary is machine-generated.

We developed a new AI method using neural networks to reconstruct molecular structures from Coulomb explosion imaging data. This technique enables precise, event-by-event analysis of molecular dynamics in ultrafast chemistry.

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Area of Science:

  • Ultrafast molecular physics and chemistry
  • Atomic and molecular physics
  • Computational chemistry

Background:

  • Determining molecular structure and evolution during reactions is crucial in ultrafast science.
  • Coulomb explosion imaging (CEI) shows promise for real-time molecular structure analysis.
  • Current CEI methods lack direct algorithms for retrieving molecular structure from fragment-ion data.

Purpose of the Study:

  • To develop a novel algorithm for direct molecular structure retrieval from CEI data.
  • To address the inverse problem of inferring molecular geometry from fragment-ion momenta.
  • To enable automated, event-by-event structure determination in CEI experiments.

Main Methods:

  • Utilized neural networks to solve the inverse problem in CEI.
  • Trained networks to infer initial atomic positions from final fragment-ion momenta.
  • Applied the scheme to simulated CEI data of polyhalomethane isomers.

Main Results:

  • Successfully retrieved molecular structures from simulated CEI data.
  • Achieved an average per-atom position error of approximately 0.1 atomic units.
  • Demonstrated accuracy within 5% of typical bond lengths for retrieved structures.

Conclusions:

  • The proposed neural network scheme enables automated, direct structure retrieval from CEI data.
  • This method allows for single-molecule analysis, crucial for complex reaction dynamics.
  • Facilitates the analysis of pump-probe experiments with multiple reaction products.