Particle analysis using laser ablation mass spectroscopy
Abstract
The present invention provides a method of quickly identifying bioaerosols by class, even if the subject bioaerosol has not been previously encountered. The method begins by collecting laser ablation mass spectra from known particles. The spectra are correlated with the known particles, including the species of particle and the classification (e.g., bacteria). The spectra can then be used to train a neural network, for example using genetic algorithm-based training, to recognize each spectra and to recognize characteristics of the classifications. The spectra can also be used in a multivariate patch algorithm. Laser ablation mass specta from unknown particles can be presented as inputs to the trained neural net for identification as to classification. The description below first describes suitable intelligent algorithms and multivariate patch algorithms, then presents an example of the present invention including results.
- Inventors:
- Issue Date:
- Research Org.:
- Sandia National Lab. (SNL-CA), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1174488
- Patent Number(s):
- 6618712
- Application Number:
- 09/321,906
- Assignee:
- Sandia Corporation (Albuquerque, NM)
- Patent Classifications (CPCs):
-
G - PHYSICS G06 - COMPUTING G06N - COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- DOE Contract Number:
- AC04-94AL85000
- Resource Type:
- Patent
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
Citation Formats
Parker, Eric P., Rosenthal, Stephen E., Trahan, Michael W., and Wagner, John S.. Particle analysis using laser ablation mass spectroscopy. United States: N. p., 2003.
Web.
Parker, Eric P., Rosenthal, Stephen E., Trahan, Michael W., & Wagner, John S.. Particle analysis using laser ablation mass spectroscopy. United States.
Parker, Eric P., Rosenthal, Stephen E., Trahan, Michael W., and Wagner, John S.. Tue .
"Particle analysis using laser ablation mass spectroscopy". United States. https://www.osti.gov/servlets/purl/1174488.
@article{osti_1174488,
title = {Particle analysis using laser ablation mass spectroscopy},
author = {Parker, Eric P. and Rosenthal, Stephen E. and Trahan, Michael W. and Wagner, John S.},
abstractNote = {The present invention provides a method of quickly identifying bioaerosols by class, even if the subject bioaerosol has not been previously encountered. The method begins by collecting laser ablation mass spectra from known particles. The spectra are correlated with the known particles, including the species of particle and the classification (e.g., bacteria). The spectra can then be used to train a neural network, for example using genetic algorithm-based training, to recognize each spectra and to recognize characteristics of the classifications. The spectra can also be used in a multivariate patch algorithm. Laser ablation mass specta from unknown particles can be presented as inputs to the trained neural net for identification as to classification. The description below first describes suitable intelligent algorithms and multivariate patch algorithms, then presents an example of the present invention including results.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2003},
month = {9}
}
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Works referenced in this record:
Total and Viable Airborne Bacterial Load in Two Different Agricultural Environments Using Gas Chromatography-Tandem Mass Spectrometry and Culture: A Prototype Study
journal, August 1998
- Krahmer, Mark; Fox, Karen; Fox, Alvin
- American Industrial Hygiene Association Journal, Vol. 59, Issue 8
Simultaneous Detection of Positive and Negative Ions From Single Airborne Particles by Real-time Laser Mass Spectrometry
journal, January 1996
- Hinz, Klaus-Peter; Kaufmann, Raimund; Spengler, Bernhard
- Aerosol Science and Technology, Vol. 24, Issue 4
On the chemical detection of bioaerosols
journal, December 1994
- Spurny, Kvetoslav R.
- Journal of Aerosol Science, Vol. 25, Issue 8
Methods for Quantitative Assessment of Airborne Levels of Noninfectious Microorganisms in Highly Contaminated Work Environments
journal, February 1998
- Eduarda, Wijnand; Heederik, Dick
- American Industrial Hygiene Association Journal, Vol. 59, Issue 2
How Intelligent Chemical Recognition Benefits from Multivariate Analysis and Genetic Optimization
journal, January 1996
- Wagner, John S.; Trahan, Michael W.; Nelson, William E.
- Computers in Physics, Vol. 10, Issue 2
Real-time detection of individual airborne bacteria
journal, June 1997
- Gieray, R. A.; Reilly, P. T. A.; Yang, M.
- Journal of Microbiological Methods, Vol. 29, Issue 3
Analysis of individual biological particles by mass spectrometry
journal, April 1984
- Sinha, M. P.; Platz, R. M.; Vilker, V. L.
- International Journal of Mass Spectrometry and Ion Processes, Vol. 57, Issue 1
Analysis of trace element in solids by using laser ablation atomic fluorescence spectroscopy
conference, January 2000
- Kim, M. -K.; Ishii, H.; Takao, T.
- Conference on Lasers and Electro-Optics (CLEO 2000). Technical Digest. Postconference Edition. TOPS Vol.39 (IEEE Cat. No.00CH37088)
Time-of-flight mass spectrometry methods for real time analysis of individual aerosol particles
journal, June 1998
- Wood, Sylvia; Prather, Kimberly
- TrAC Trends in Analytical Chemistry, Vol. 17, Issue 6, p. 346-356
Airborne Particle Analysis
journal, December 1996
- Spengler, B.; Hinz, K. -P.; Kaufmann, R.
- Science, Vol. 274, Issue 5295
The assessment of bioaerosols: A critical review
journal, December 1994
- Griffiths, W. D.; DeCosemo, G. A. L.
- Journal of Aerosol Science, Vol. 25, Issue 8