Hypothesis-driven classification of materials using nuclear magnetic resonance relaxometry

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

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:: Espy, Michelle A.; Matlashov, Andrei N.; Schultz, Larry J.; Volegov, Petr L.

Issue Date:: 2016-08-09

OSTI Identifier:: 1288655

Assignee:: Los Alamos National Security, LLC (Los Alamos, NM) LANL

Patent Number(s):: 9,411,031

Application Number:: 13/869,718

Contract Number:: AC52-06NA25396

Resource Relation:: Patent File Date: 2013 Apr 24

Research Org:: Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Sponsoring Org:: USDOE

Country of Publication:: United States

Language:: English

Subject:: 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY

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