It is well known that NMR is a very convenient technique for quantification, provided the amount of the material is within the limits of detection in NMR.
When it comes to the actual calculations, this is a very straightforward process that does not require any fancy mathematics. Typically you will select the most convenient signal(s) or multiplet(s) in your spectrum and calculate the integral which can then be mapped to the corresponding concentration units by using a scaling factor that was previously calculated using some internal or external references.
It is however a laborious process. You have to make sure that the signal or multiplet you have selected is isolated enough to avoid contaminations from other signals (solvents, impurities, other compound resonances, etc). Furthermore, you need to know the number of nuclides (i.e. protons) of the integrated signal / multiplet. Again, this is not rocket science but it is particularly labor-intensive. It could take perfectly a few minutes for one single data set.
Now suppose that you have to do this with a library of several hundred or thousands of compounds with their corresponding NMR spectra. Clearly a manual analysis is completely impractical.
There are several approaches out there that can be used to automate this process in some way or another, but to the best of my knowledge they are not optimized to take into account a number of factors that could adversely affect the accuracy and precision of the quantification calculations. Features such as spectral quality variability from sample to sample, different degrees of peak overlap, amongst others, are very important in order to have a robust system.
That is precisely one of the main objectives that we’ve pursued with the development of a new qNMR module for Mnova that we have just released, the ability to process any number of data sets in the most robust way possible.
It has been designed in such a way that it can detect those multiplets in the spectrum that gives the best results whilst discarding those problematic ones (for example, multiplets showing overlapping problems, or having impurities or artifacts). It also calculates the number of nuclides for each of those multiplets, etc.
Bottom line is that this new module is aimed at streamlining qNMR analyses and reporting whilst eliminating tedious and repetitious manual steps.
We believe that it is a useful tool not only in the traditional exploitation of qNMR where the final result is required to the highest level of precision, and the utmost care must be taken in collecting the NMR data, but also in the world of high-throughput NMR where this very careful data acquisition is often not possible. Whilst the first thought may be that qNMR therefore is not possible, we know from collaborative studies that quite reasonable and useful quantitative data can be obtained in this scenario. The error expectation obviously has to be lowered and actual numbers will depend on factors such as the rate of data acquisition, SNR, and impurity levels, but concentration determination to within 5-10% of the actual value is not an unrealistic expectation.
This new module can be tried for free, just go here.
You can also find more information here
Of course, should you have any question or need any further information, please feel free to get in touch with us.
