With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, the groups of Professors James Edwards and James Grinias from Saint Louis University and Rowan University, respectively, are working to improve the analysis of chemicals in complex mixtures like wastewater sludge and blood by devising improved methods to physically separate the constituents prior to their identification and quantitation. The approach utilizes a novel "green chemistry" based technique, with reduced dependence on expensive and potentially harmful solvents. The team is also devising a series of sample pretreatments intended to improve both the separation efficiency and the subsequent analysis. The analysis improvements will enhance the measurement and understanding of environmental and biological phenomena. The collaboration is introducing undergraduate and graduate students to complex chemical systems and tools for their characterization, thereby enhancing the training of the next generation of workforce.

The analysis of small molecules and metabolites is limited largely by the performance of the separation system. Methods being jointly developed in the Edwards and Grinias laboratories are capable of preconcentrating derivatized small molecules and then chromatographically resolving them based on analyte structure. Specifically, the approach entails development of a two-dimensional (2D) ion exchange-supercritical fluid chromatography (IEX-SFC) separation system. In this approach, small molecules are derivatized with a cationic aromatic tag which allows them to be preconcentrated on an IEX column. Using organic solvent rather than salts to elute off the IEX renders the eluent compatible with SFC and mass spectrometry (MS). The SFC then resolves analytes based on hydrophilic interactions, independent (insofar as possible) of the tag. Both a full-bore IEX-SFC system and a capillary based SFC system are being developed with multi-faceted gradients (organic solvent and temperature). In addition, a novel nanospray interface is being developed to facilitate MS detection coupled to SFC.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Chemistry (CHE)
Type
Standard Grant (Standard)
Application #
1904454
Program Officer
Kelsey Cook
Project Start
Project End
Budget Start
2019-08-15
Budget End
2022-07-31
Support Year
Fiscal Year
2019
Total Cost
$228,399
Indirect Cost
Name
Rowan University
Department
Type
DUNS #
City
Glassboro
State
NJ
Country
United States
Zip Code
08028