NMR
NMR (Nuclear Magnetic Resonance) serves to detemine the molecular structure of pure solved compunds. NMR is a first class candidate for digital superresolution (DS), since the kernel is allways well known and independant of frequency.
Most important applications of DS in nmr are these:
Application | Black
line: Original
data Grey solid: Superresolution Green line: Kernel |
1H,
13C, 31P,
29Si, etc The effecf of DS in nmr is comparable to using duplicate frequency or field. In addition, the long wings of the lorentzians are concentrated into a more gaussian profile of each peak, wich greatly simplifies area estimation by simple integration. The example shows, how DS identifies a weak pentett, wich is confused by a strong doublett. Note the correct identification of the minute peak at digit 125. |
|
Peak identification in noisy
data Up to a noise level of 10%, superresolution is by far the best method to interprete even totally unclear data. Ergonomics A short look on a superresolved spectrum shows very clear data, ready for direct and correct intuitive interpretation. Working with complex patterns is much less time consuming thereby. |
|
Reducing sampling intervals Spectrum A was sampled in 400% of the sampling time of B. Though in B noise is stronger by a factor 2, its superresolution is by far more informative than the non-resolved A. For high throuput optimization DH thus allows for an approximate duplicate sample flow per time. |
Superresolution requires robust
baseline correction.
In PROANALYSI::PEAKS, you find baseline-routines
optimized especially for NMR.
The complete sequence of data analysis can be automatted and
perfomed by simply pressing a button.