You are here

Automated peak fitting and analysis software for advanced gas chromatography and mass spectrometer systems

Award Information
Agency: Department of Commerce
Branch: National Oceanic and Atmospheric Administration
Contract: WC-133R-17-CN-0082
Agency Tracking Number: 17-1-066
Amount: $119,976.75
Phase: Phase I
Program: SBIR
Solicitation Topic Code: 8.2.7
Solicitation Number: NOAA-2017-1
Solicitation Year: 2017
Award Year: 2017
Award Start Date (Proposal Award Date): 2017-06-12
Award End Date (Contract End Date): 2017-12-12
Small Business Information
45 Manning Road, Billerica, MA, 01821-3976
DUNS: 030817290
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Brian Lerner
 (978) 932-0220
Business Contact
 Brian Lerner
Phone: (978) 932-0220
Research Institution
Recent advances in gas chromatographic and mass spectrometric techniques for atmospheric measurements have led to highly complex data sets that have overwhelmed the capabilities of current data analysis software. We propose a new method for the automated reduction of chromatographic data using peak-fitting algorithms. By relying upon constrained peak-fit parameterization, accuracy of peak identification can be maintained or improved over standard manual integration methods. The proposed analysis software can take advantage of the fast, multithread processors available in current computer systems to process large multidimensional data sets, especially those produced with advanced time-of-flight mass spectrometers. Scientists who use GC-MS instruments will be able to reduce their analysis time to a small fraction of what is currently required. With this automated analysis software, NOAA researchers, and the atmospheric community at large, will be capable of fully and rapidly processing large complex data sets, and will be able to push the boundaries of our understanding of the atmosphere.

* Information listed above is at the time of submission. *

US Flag An Official Website of the United States Government