What I was curious to discover was: is it possible to recalculate the components of a mixture if the diffusion coeffients are known? From a pure mathematical point of view the answer was already: "yes", but I wanted to verify it in practice.
As far as I know, something like: "QR-DOSY" has never been mentioned. So many DOSY methods already exist and I don't mind to increase the Babel with yet another acronym. Do you?
THEORY
If we know the diffusion coefficient D(j) we can calculate that the NMR signal in the spectrum i will be proportional to a value A(i,j) = exp(-D(j)F(i)) where F is a function of the gyromagnetic ratio, the gradient strength, the diffusion delay, etc.. but not a function of the chemical shift nor of the diffusion coefficient.
For each column of the DOSY spectrum we have a system of equations: Ax = b.
x = intensity of the spectrum of the pure compounds at the chemical shift that coresponds to the given column.
b = intensity of the DOSY along the same column.
We know A and b, therefore we can calculate x. A is the same for all the columns and this is a great advantage. We can apply a well known decomposition: Rx = Qb.
Calculating Q and R from A takes time, but we need to do it only once. Then then computer can swiftly solve all the systems in the form Rx = Qb.
METHODS
Obviously, we will find that some values of the x will be negative. In such a case, we can choose a subset of A (omitting the component with negative intensity) and solve the reduced problem. This simplifying mechanism can be applied iteratively, even when the value of x is positive yet small.
RESULTS
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This is the same old spectrum we are familiar with, processed with the new QR-DOSY.
DISCUSSION
Two components are completely separated. The third component is not, although at this point it becomes easy to recognize its peaks. Other cases I have studied yield similar results, maybe not as nice. Advantages of the QR-DOSY method:
- easy to understand;
- easy to use WITH THE ASSISTANCE of a software for the book-keeping activity (like measuring the diffusion coefficients);
- fast;
- the user can play with a few parameters, trying to improve the results;
- the final spectra are clean from artifacts.
Cons:
- not all the components are always resolved;
- it's a problem if two diffusion coefficients are similar (of course the program itself can easily detect this circumstance).