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Related Concept Videos

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

Two-Dimensional (2D) NMR: Overview

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.
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

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...
NMR Spectroscopy: Chemical Shift Overview01:15

NMR Spectroscopy: Chemical Shift Overview

The position of the absorption signal of a sample is reported relative to the position of the signal of tetramethylsilane (TMS), which is added as an internal reference while recording spectra. The difference between the absorption frequencies of the sample and TMS (in Hz) is divided by the spectrometer operating frequency (in MHz) to obtain a dimensionless quantity called the chemical shift. It is reported on the δ (delta) scale and expressed in parts per million.
For instance, the proton...
¹H NMR Chemical Shift Equivalence: Enantiotopic and Diastereotopic Protons00:58

¹H NMR Chemical Shift Equivalence: Enantiotopic and Diastereotopic Protons

Replacing each alpha-hydrogen in chloroethane by bromine (or a different functional group) yields a pair of enantiomers. Such protons are called prochiral or enantiotopic and are related by a mirror plane. Enantiotopic protons are chemically equivalent in an achiral environment. Because most proton NMR spectra are recorded using achiral solvents, enantiotopic hydrogens yield a single signal.
In chiral compounds such as 2-butanol, replacing the methylene hydrogens at C3 produces a pair of...
2D NMR: Overview of Homonuclear Correlation Techniques01:16

2D NMR: Overview of Homonuclear Correlation Techniques

Homonuclear correlation spectroscopy (COSY) is a powerful technique used in Nuclear Magnetic Resonance (NMR) spectroscopy to study the correlations between nuclei of the same type within a molecule. It provides information about scalar couplings between adjacent nuclei, which helps determine connectivity and structural information. There are several COSY variants, each with its unique strengths and experimental parameters.
COSY90 is the standard two-dimensional (2D) COSY experiment that...
¹H NMR Chemical Shift Equivalence: Homotopic and Heterotopic Protons01:03

¹H NMR Chemical Shift Equivalence: Homotopic and Heterotopic Protons

Protons in identical electronic environments within a molecule are chemically equivalent and have the same chemical shift. The replacement test is a useful tool to identify chemical equivalence and predict NMR spectra. A substituent replaces each of the protons being examined and the resulting molecules are compared. If the same molecule is obtained, the protons are equivalent or homotopic. Replacement of any hydrogens in ethane by chlorine yields chloroethane because all six protons are...

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Related Experiment Videos

Efficient Prediction of Transition-Metal NMR Chemical Shifts Using Machine Learning: Do Two-Dimensional Descriptors

Yaroslav I Isaev1, Alexey E Kovalev1, Alexander A Ksenofontov1

  • 1G.A. Krestov Institute of Solution Chemistry of the Russian Academy of Sciences, 153045 Ivanovo, Russian Federation.

Journal of Chemical Information and Modeling
|June 18, 2026
PubMed
Summary

Machine learning models accurately predict nuclear magnetic resonance chemical shifts for transition metals. This approach offers a computationally efficient alternative to traditional quantum-chemical methods for predicting chemical shifts in coordination compounds.

Related Experiment Videos

Area of Science:

  • Computational Chemistry
  • Materials Science
  • Spectroscopy

Background:

  • Predicting nuclear magnetic resonance (NMR) chemical shifts for transition metals is computationally intensive and data-limited.
  • Existing quantum-chemical methods are often too costly for routine predictions.
  • Experimental NMR data for transition-metal compounds is scarce.

Purpose of the Study:

  • Develop accurate and efficient machine learning (ML) models for predicting NMR chemical shifts in transition-metal coordination compounds.
  • Evaluate various ML architectures and molecular representations for predictive performance.
  • Understand metal-specific structure-property relationships governing chemical shifts.

Main Methods:

  • Curated dataset of 1956 experimental NMR chemical shift measurements for Mn, Fe, Nb, and Mo compounds.
  • Development and evaluation of descriptor-based models, graph neural networks, and transformer architectures.
  • Application of Shapley additive explanations (SHAP) for model interpretation.
  • External validation using 195Pt complexes.

Main Results:

  • The Tabular Prior-Data Fitted Network model achieved the best performance, with prediction errors of 4.5-8% of the chemical shift range.
  • Two-dimensional (2D) molecular descriptors offered accuracy comparable to 3D approaches with significantly lower computational cost.
  • Model interpretation revealed element-specific structure-property relationships and defined applicability domains.
  • External validation on 195Pt complexes demonstrated the generalizability of the 2D descriptor approach (159 ppm MAE).

Conclusions:

  • ML models utilizing molecular descriptors provide an efficient and reliable alternative to quantum-chemical methods for predicting transition-metal NMR chemical shifts.
  • 2D descriptors offer a computationally advantageous representation for developing predictive NMR shift models.
  • The element-specific nature of chemical shifts necessitates tailored models for different transition metals.