What Do You Get from Ion Mobility Q-TOF?

Ion mobility-mass spectrometry has become a valuable analytical tool in providing rotationally averaged collision cross-section values (CCS) that correlate to the size and shape of molecules. It delivers an added dimension of separation based on drift times.

Using accurate mass, retention times, MS/MS spectra and CCS, we can minimize the chance of getting false-positives or false-negatives in targeted or untargeted screening. In discovery workflows, CCS values in combination with machine learning can be used to predict structures minimizing the need for reference standards.

We will show data generated with the IMQTOF and how it can help solve challenges in screening and discovery. We will also look at the integration of machine learning with ion mobility to predict structures of chemical components.

Presenter: Sheher Banu Mohsin, Ph.D. (Senior Applications Scientist, Agilent Technologies, Inc.)

Sheher Mohsin received her Ph.D. in physical chemistry from the University of Illinois and an MBA from Rockhurst University. Sheher currently works at Agilent Technologies as a Senior Applications Scientist. Her recent efforts has been focused on developing workflows for untargeted lipidomics.