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Evolutionary algorithms to solve complicated NMR spectra
W Leo Meerts1, C A de Lange, A C J Weber
1Molecular- and Biophysics Group, Institute for Molecules and Materials, Radboud University Nijmegen, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands. leo.meerts@science.ru.nl
The Journal of Chemical Physics
|February 5, 2009
Summary
Analyzing complex nuclear magnetic resonance (NMR) spectra is challenging. This study introduces an automated evolutionary algorithm to successfully interpret the 12-spin proton NMR spectrum of pentane.
Area of Science:
- Nuclear Magnetic Resonance (NMR) Spectroscopy
- Computational Chemistry
- Physical Chemistry
Background:
- Proton NMR spectra complexity increases with the number of spins in partially ordered solvents.
- Analysis of large spin systems (>8 spins) is often difficult or impossible.
- Interconversion among multiple conformations complicates spectral interpretation.
Purpose of the Study:
- To apply a general automated evolutionary algorithm for solving complex NMR spectra.
- To analyze the 12-spin proton NMR spectrum of pentane.
- To develop a model for interpreting spectral parameters and orientational orders in different conformers.
Main Methods:
- Application of a general automated evolutionary algorithm.
- Analysis of the 12-spin system pentane's proton NMR spectrum.
- Utilizing a model to connect orientational orders in symmetry-unrelated conformers.
Main Results:
- Successful interpretation of a highly complex 12-spin proton NMR spectrum.
- Demonstration of the evolutionary algorithm's capability for large spin systems.
- Obtained spectral parameters require conformational modeling for interpretation.
Conclusions:
- Automated evolutionary algorithms can solve complex NMR spectra previously considered intractable.
- The method is applicable to solutes with multiple, rapidly interconverting conformations.
- A model is essential for relating spectral data to molecular structure and dynamics in complex systems.
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