Signal variation in single particle aerosol mass spectrometry

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Physics, 2007.

Sonraí bibleagrafaíochta
Príomhchruthaitheoir: Wissner-Gross, Zachary Daniel
Rannpháirtithe: Matthias Frank and Young Lee.
Formáid: Tráchtas
Teanga:eng
Foilsithe / Cruthaithe: Massachusetts Institute of Technology 2008
Ábhair:
Rochtain ar líne:http://hdl.handle.net/1721.1/40921
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author Wissner-Gross, Zachary Daniel
author2 Matthias Frank and Young Lee.
author_facet Matthias Frank and Young Lee.
Wissner-Gross, Zachary Daniel
author_sort Wissner-Gross, Zachary Daniel
collection MIT
description Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Physics, 2007.
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institution Massachusetts Institute of Technology
language eng
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publisher Massachusetts Institute of Technology
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spelling mit-1721.1/409212019-04-12T09:15:23Z Signal variation in single particle aerosol mass spectrometry Wissner-Gross, Zachary Daniel Matthias Frank and Young Lee. Massachusetts Institute of Technology. Dept. of Physics. Massachusetts Institute of Technology. Dept. of Physics. Physics. Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Physics, 2007. Includes bibliographical references (p. 33-34). Rapid and accurate detection of airborne micro-particles is currently an important problem in national security. One approach to such detection, bioaerosol mass spectrometry (BAMS), is currently under development at Lawrence Livermore National Laboratory. BAMS is a type of single particle aerosol mass spectrometry that rapidly records dual-polarity mass spectra of aerosolized micro-particles. However, the accuracy of the BAMS system is limited by various uncertainties, resulting in shot-to-shot variations in the mass spectra. I found that the variations in mass peak areas in BAMS spectra were significantly larger than those predicted by Poisson statistics based on the mean number of detected ions. Furthermore, these variations were surprisingly consistent as a function of peak area among synthetic, organic, and biological samples. For both positive and negative ions, the standard deviation in a peak's area was approximately proportional to the mean value of that area to the 0.9 power. Using the consistency of this data, I also developed a novel method for quantitatively evaluating the similarity between mass spectra using a chi-square factor. Peak area variations in other single particle aerosol mass spectrometers may be similarly analyzed and used to improve methods for rapid particle identification. by Zachary Daniel Wissner-Gross. S.B. 2008-03-27T18:23:35Z 2008-03-27T18:23:35Z 2007 2007 Thesis http://hdl.handle.net/1721.1/40921 212378223 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 34 p. application/pdf Massachusetts Institute of Technology
spellingShingle Physics.
Wissner-Gross, Zachary Daniel
Signal variation in single particle aerosol mass spectrometry
title Signal variation in single particle aerosol mass spectrometry
title_full Signal variation in single particle aerosol mass spectrometry
title_fullStr Signal variation in single particle aerosol mass spectrometry
title_full_unstemmed Signal variation in single particle aerosol mass spectrometry
title_short Signal variation in single particle aerosol mass spectrometry
title_sort signal variation in single particle aerosol mass spectrometry
topic Physics.
url http://hdl.handle.net/1721.1/40921
work_keys_str_mv AT wissnergrosszacharydaniel signalvariationinsingleparticleaerosolmassspectrometry