Jaanus Liigand was awarded the 1st prize in category of natural sciences and technology in the Estonian National Contest for University Students supported by Estonian Research Council for his doctoral thesis.
He defended his PhD thesis on “Standard substance-free quantification for LC/ESI/MS analysis based on the predicted ionization efficiencies”. During his PhD studies, Jaanus has worked hard on understanding the mechanism of electrospray ionization in LC/ESI/MS; primarily understanding how the structure of the compound and the eluent used in the analysis influence the ionization efficiency. Jaanus has verified, based on the largest set of ionization efficiencies measured so far (roughly 400 compounds), that the more hydrophobic compounds and more basic compounds tend to have a higher response in ESI positive mode. From the mobile phase point of view, both organic solvent content, pH of the buffer, and buffer composition, influence the ionization efficiency in ESI/MS. In general, higher organic solvent content and lower pH result in higher ionization efficiency and, therefore, a higher response in positive mode ESI/MS.
Also, he investigated how well are the ionization efficiency values measured on one instrument transferable to other instruments and found that with the aid of 5-6 common compounds the ionization efficiency values can be transferred from one instrument to another. Combining these promising results and machine learning approaches Jaanus has been able to develop a truly universal approach for applying ionization efficiency predictions for quantification in suspect and non-targeted LC/ESI/HRMS analysis.
He is continuing his research at University of Alberta in Canada in Prof. David Wishart research group to further improve mass spectrometric analysis with machine learning.
Congratulations to you, Jaanus, for the well-deserved acknowledgment!