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Title: Hypothesis-driven classification of materials using nuclear magnetic resonance relaxometry

Abstract

Technologies related to identification of a substance in an optimized manner are provided. A reference group of known materials is identified. Each known material has known values for several classification parameters. The classification parameters comprise at least one of T.sub.1, T.sub.2, T.sub.1.rho., a relative nuclear susceptibility (RNS) of the substance, and an x-ray linear attenuation coefficient (LAC) of the substance. A measurement sequence is optimized based on at least one of a measurement cost of each of the classification parameters and an initial probability of each of the known materials in the reference group.

Inventors:
; ; ;
Issue Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1288655
Patent Number(s):
9,411,031
Application Number:
13/869,718
Assignee:
Los Alamos National Security, LLC (Los Alamos, NM)
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Patent
Resource Relation:
Patent File Date: 2013 Apr 24
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY

Citation Formats

Espy, Michelle A., Matlashov, Andrei N., Schultz, Larry J., and Volegov, Petr L. Hypothesis-driven classification of materials using nuclear magnetic resonance relaxometry. United States: N. p., 2016. Web.
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Espy, Michelle A., Matlashov, Andrei N., Schultz, Larry J., & Volegov, Petr L. Hypothesis-driven classification of materials using nuclear magnetic resonance relaxometry. United States.
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Espy, Michelle A., Matlashov, Andrei N., Schultz, Larry J., and Volegov, Petr L. Tue . "Hypothesis-driven classification of materials using nuclear magnetic resonance relaxometry". United States. https://www.osti.gov/servlets/purl/1288655.
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@article{osti_1288655,
title = {Hypothesis-driven classification of materials using nuclear magnetic resonance relaxometry},
author = {Espy, Michelle A. and Matlashov, Andrei N. and Schultz, Larry J. and Volegov, Petr L.},
abstractNote = {Technologies related to identification of a substance in an optimized manner are provided. A reference group of known materials is identified. Each known material has known values for several classification parameters. The classification parameters comprise at least one of T.sub.1, T.sub.2, T.sub.1.rho., a relative nuclear susceptibility (RNS) of the substance, and an x-ray linear attenuation coefficient (LAC) of the substance. A measurement sequence is optimized based on at least one of a measurement cost of each of the classification parameters and an initial probability of each of the known materials in the reference group.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2016},
month = {8}
}
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Works referenced in this record:

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