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Title: bem: modeling for neutron Bragg-edge imaging

Abstract

Due to its zero net charge, neutron is a unique probe of materials. Low neutron absorption and scattering cross sections by most nuclei make it suitable for studying bulk samples. Unlike X-ray scattering, neutron form factors are not monotonically dependent on atomic numbers; the fact that the neutron scattering cross section of hydrogen is large makes neutron a useful tool in biology. In the past half century, neutron imaging has seen growing applications in various scientific fields including physics, engineering sciences, biology, and archaeology (Strobl et al., 2009).With energy-resolved neutron imaging techniques, neutron Bragg-edge imaging has recently found applications for materials science in phase mapping, stress/strain mapping, and texture analysis (Josic, Steuwer, & Lehmann, 2010, Sato (2017)). To model Braggedge neutron imaging data, it is necessary to calculate the total neutron cross section of a sample. This open-source python package provides easy-to-use functions to calculate coherent elastic (diffraction), incoherent elastic, coherent inelastic, and incoherent inelastic scattering cross sections, as well as absorption cross sections based on approximations and formulas in (Vogel, 2000). Also implemented are algorithms that take into account the March-Dollase texture model, and the Jorgensen peak profile (Vogel, 2000).

Authors:
ORCiD logo [1]; ORCiD logo [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1558489
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Open Source Software
Additional Journal Information:
Journal Volume: 3; Journal Issue: 30; Journal ID: ISSN 2475-9066
Publisher:
Open Source Initiative - NumFOCUS; Copyright - Open Journals
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Lin, Jiao, and Song, Gian. bem: modeling for neutron Bragg-edge imaging. United States: N. p., 2018. Web. doi:10.21105/joss.00973.
Lin, Jiao, & Song, Gian. bem: modeling for neutron Bragg-edge imaging. United States. https://doi.org/10.21105/joss.00973
Lin, Jiao, and Song, Gian. 2018. "bem: modeling for neutron Bragg-edge imaging". United States. https://doi.org/10.21105/joss.00973. https://www.osti.gov/servlets/purl/1558489.
@article{osti_1558489,
title = {bem: modeling for neutron Bragg-edge imaging},
author = {Lin, Jiao and Song, Gian},
abstractNote = {Due to its zero net charge, neutron is a unique probe of materials. Low neutron absorption and scattering cross sections by most nuclei make it suitable for studying bulk samples. Unlike X-ray scattering, neutron form factors are not monotonically dependent on atomic numbers; the fact that the neutron scattering cross section of hydrogen is large makes neutron a useful tool in biology. In the past half century, neutron imaging has seen growing applications in various scientific fields including physics, engineering sciences, biology, and archaeology (Strobl et al., 2009).With energy-resolved neutron imaging techniques, neutron Bragg-edge imaging has recently found applications for materials science in phase mapping, stress/strain mapping, and texture analysis (Josic, Steuwer, & Lehmann, 2010, Sato (2017)). To model Braggedge neutron imaging data, it is necessary to calculate the total neutron cross section of a sample. This open-source python package provides easy-to-use functions to calculate coherent elastic (diffraction), incoherent elastic, coherent inelastic, and incoherent inelastic scattering cross sections, as well as absorption cross sections based on approximations and formulas in (Vogel, 2000). Also implemented are algorithms that take into account the March-Dollase texture model, and the Jorgensen peak profile (Vogel, 2000).},
doi = {10.21105/joss.00973},
url = {https://www.osti.gov/biblio/1558489}, journal = {Journal of Open Source Software},
issn = {2475-9066},
number = 30,
volume = 3,
place = {United States},
year = {Mon Oct 01 00:00:00 EDT 2018},
month = {Mon Oct 01 00:00:00 EDT 2018}
}

Works referenced in this record:

Energy selective neutron radiography in material research
journal, March 2010


Advances in neutron radiography and tomography
journal, November 2009