Robust 1D NMR lineshape fitting using real and imaginary data in the frequency domain

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Computational Chemistry

Background:

• Quantitative Nuclear Magnetic Resonance (NMR) relies heavily on accurate peak area calculations.
• Existing peak fitting methods may lack precision and robustness, impacting quantitative results.

Purpose of the Study:

• To develop and validate a new method for improved peak fitting in quantitative NMR.
• To enhance the precision and accuracy of peak area calculations using complex-valued peak descriptions.

Main Methods:

• Utilized complex-valued peak descriptions in the frequency domain for Fourier-transformed NMR data.
• Incorporated phase correction, baseline correction, and apodization within the fitting process.
• Implemented the method in an open-source R package, rnmrfit.

Main Results:

• Demonstrated significantly higher precision in peak fitting compared to existing software on real data.
• Achieved coefficients of variation below 0.1% at signal-to-noise ratios of approximately 100 using simulation data.
• Showcased the effectiveness of complex-valued data for improving quantitative NMR analysis.

Conclusions:

• Complex-valued peak descriptions offer a simple yet effective strategy for enhancing peak fitting in quantitative NMR.
• The rnmrfit package provides a readily accessible tool for researchers seeking improved quantitative NMR analysis.
• This method holds potential for advancing the reliability and precision of NMR-based quantitative measurements.