Gradient-based 2D NMR experiments

I consider structural elucidation using NMR a fun and challenging chemistry puzzle. For molecules of different sizes and complexities, various questions regarding their molecular composition and both the connectivity and spatial arrangement of their atoms may arise. For each question, a specific experiment can be chosen, and the combined analyses can be the key to providing answers and solving the puzzle.

Have you realized that the library of NMR experiments includes not hundreds, but thousands of experiments?!? Each NMR experiment is governed by a pulse sequence designed to enhance certain coherence pathways while suppressing others. Coherence pathways represent specific routes through which spins can evolve during an NMR experiment. By carefully orchestrating RF pulses, delays, and gradients, these sequences enable the selective observation of desired spin interactions, allowing spectroscopists to extract detailed information about molecular structure and dynamics.

The desired coherence pathway can be selected in two ways: by using phase cycling alone, or by employing a Pulsed Field Gradient (PFG).  The phase cycling approach changes the phase of the pulses (e.g., x, -x) and the receiver systematically to ensure that signals from the desired path will be added in consecutive scans, while signals from the other paths will be subtracted. By doing this repeatedly with each scan, the experiment successfully results in the desired output.  However, it can be slow because multiple scans must be collected. The pathway selection using PFG is faster because instead of relying upon multiple scans, it relies on the fact that for the duration with which a gradient is applied (typically, a few milliseconds), the magnetic field becomes inhomogeneous, and the spins acquire a spatial encoding which, later in the experiment, are decoded by another gradient(s). The elegance of this method is that it relies on the fact that each pathway is represented by spins with a specific coherence and each coherence possesses a different dephasing rate, so the use of a proper gradient ratio(s) can selectively refocus the desired coherences, without the need to acquire many scans.

In summary, 2D gradient-based NMR experiments usually provide better-quality data. Since their selection does not rely on the sum and subtraction of signals, a much lower level of t1 noise (vertical “stripes”, more evident for the most intense signals) is expected (Figure 1a and 1b). Moreover, if signal-to-noise ratio (SNR) is not the limiting factor, gradient-based experiments can often be run in a fraction of the time compared to the phase-cycling approach, as many repetitions are not required (Figure 1a and 1c).

Figure 1: Comparison of ¹H-¹³C HSQC data from 1,3-butanediol in D₂O at 100 MHz; a) non-gradient-based HSQC acquired with 8 scans, b) gradient-based HSQC acquired with 8 scans, and c) gradient-based HSQC acquired with 2 scans. For comparison purposes spectra a) and b) have the same intensity level, showing that the regular HSQC has a higher level of t1 noise. However, the regular HSQC data can be zoomed out and the t1 noise will not affect the interpretation of this data, as its intensity is lower than the correlations. When comparing a) and c) the gradient-based HSQC can provide the same level of information in a quarter of the experiment time. In conclusion, in most cases, gradient-based experiments allow you to collect higher-quality 2D data in a fraction of the time. This approach significantly enhances both efficiency and data quality, making it a preferred choice for many applications.

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