Rapid simulation of two-dimensional spectra with correlated anisotropic dimensions

A new algorithm has been developed to simulate two-dimensional (2D) spectra with correlated anisotropic frequencies faster and more accurately than previous methods. The technique uses finite-element numerical integration on the sphere and an interpolation scheme based on the Alderman–Solum–Grant al...

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Bibliographic Details
Published in:The Journal of chemical physics 2024-04, Vol.160 (13)
Main Authors: Srivastava, Deepansh J., Baltisberger, Jay H., Grandinetti, Philip J.
Format: Article
Language:English
Subjects:
Algorithms
Computer simulation
Distribution functions
Interpolation
Least squares
Mathematical analysis
NMR
Nuclear magnetic resonance
Numerical integration
Probability distribution functions
Spectra
Tensors
Two dimensional analysis
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Summary:A new algorithm has been developed to simulate two-dimensional (2D) spectra with correlated anisotropic frequencies faster and more accurately than previous methods. The technique uses finite-element numerical integration on the sphere and an interpolation scheme based on the Alderman–Solum–Grant algorithm. This method is particularly useful for numerical calculations of joint probability distribution functions involving quantities with a parametric orientation dependence. The technique’s efficiency also allows for practical least-squares fitting of experimental 2D solid-state nuclear magnetic resonance (NMR) datasets. The simulation method is illustrated for select 2D NMR methods, and a least-squares analysis is demonstrated in the extraction of paramagnetic shift and quadrupolar coupling tensors and their relative orientation from the experimental shifting-d echo 2H NMR spectrum of a NiCl2 · 2D2O salt.
ISSN:0021-9606
1089-7690
DOI:10.1063/5.0200042