Anna Marija Sumrova

PhD thesis: TBC

In my PhD project I will focus on a development of an automated approach for processing and assignment of NMR spectra of unknown mixtures. One of the key milestones I intend to achieve is partial extraction of meaningful insights from NMR spectra such as change of functional group in the compound and relative ratio of unknown species in the mixture. As there is no explicitly defined condition for a spectrum to be fully interpretable, this might be impossible. However, selective partial information extraction might be sufficient for tasks where complete assignment is not needed. For instance, when an absence of species needs to be confirmed. The algorithm will be designed to extract information about crude reaction mixtures or a subset of compounds present in it when complete assignment is limited. The project will also aim to adapt the algorithm and develop a highly useful tool for in situ reaction monitoring. This would improve mechanistic understanding of many known reactions and simplify exploration of new chemical space.

Who or what inspired you to pursue your research interests?

Current experimental progress enables to carry out highly data-intensive research – recording thousands of spectra per day. However, due to the absence of sufficiently efficient methods for spectral data processing many existing spectra are left unexplored. A lot of important information is not extracted, thereby significantly limiting understanding of chemical processes and ways for their optimisation. Over many years of practical experience in various fields of chemistry, I found myself repeatedly working with NMR, sparking my passion for this research. I believe that a more structured and automated approach to spectral data analysis can extract significantly more information, uncover hidden trends, and streamline further experimentation, ultimately advancing the field and enhancing capabilities of humankind.