New Algorithm by Maximizing Mutual Information for Correction of Frequency Drifts Arising from One-Dimensional NMR Spectroscopic Data Acquisition.

Abstract

Benchtop nuclear magnetic resonance (NMR) instruments are getting popular these days. However, the obtained spectra sometimes suffer from significant frequency drifts, which cause difficulty in accumulating the raw data. In this paper, a new algorithm for correction of frequency drifts is proposed, which operates by maximizing mutual information between the obtained spectroscopic data. The algorithm worked well for both 1H and 19F NMR spectroscopic data, even in the case of very noisy ones. In comparison with the previously reported algorithms, the present algorithm has an advantage that NMR spectra complicated by signal overlapping and spin coupling can be handled without difficulty. This makes the present algorithm particularly advantageous for application of benchtop NMR spectrometers in organic chemistry.