SNIC
SUPR
SNIC SUPR
Cross Collision Section Predictions
Dnr:

SNIC 2017/3-93

Type:

SNAC Small

Principal Investigator:

Christine Gallampois

Affiliation:

UmeƄ universitet

Start Date:

2017-10-25

End Date:

2018-11-01

Primary Classification:

10401: Analytical Chemistry

Webpage:

Allocation

Abstract

In environmental samples, numerous trace level contaminants co-exist with many other more abundant anthropogenic chemicals as well as natural compounds. It is thus difficult to detect these trace compounds with common separation methods. With the development of detection methods, ion mobility separation (IMS) has the ability to separate analytes in the gas phase according to their charge, shape and size as they travel at different velocity in a drift cell. IMS experiment enable the determination of collision cross section (CCS) value that is a unique physicochemical property of a molecule that can aid structural studies and also facilitates small molecules identification. Ion mobility remains largely unexplored in environmental studies. The incorporation of IMS into current mass spectrometry-based methods will lead to improved separation power for a better coverage of low abundance chemicals. CCS needs to be implemented in the identification workflow to select plausible candidates for an unknown compound. In this work I want to explore the possibility of using computationally predicted CCS value with molecular dynamic calculations to assist in the identification workflow of anthropogenic chemicals.