skip to main content
DOE Patents title logo U.S. Department of Energy
Office of Scientific and Technical Information

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):
9411031
Application Number:
13/869,718
Assignee:
Los Alamos National Security, LLC (Los Alamos, NM)
Patent Classifications (CPCs):
G - PHYSICS G01 - MEASURING G01N - INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
G - PHYSICS G01 - MEASURING G01R - MEASURING ELECTRIC VARIABLES
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.
Espy, Michelle A., Matlashov, Andrei N., Schultz, Larry J., & Volegov, Petr L. Hypothesis-driven classification of materials using nuclear magnetic resonance relaxometry. United States.
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.
@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}
}

Patent:

Save / Share:

Works referenced in this record:

Toward direct mapping of neuronal activity: MRI detection of ultraweak, transient magnetic field changes
journal, June 2002


SQUID-Based Simultaneous Detection of NMR and Biomagnetic Signals at Ultra-Low Magnetic Fields
journal, June 2005


SQUID detected NMR in microtesla magnetic fields
journal, September 2004


Directly mapping magnetic field effects of neuronal activity by magnetic resonance imaging
journal, August 2003