A review of advantages of high-efficiency X-ray spectrum imaging for analysis of nanostructured ferritic alloys

Parish, Chad M.; Miller, Michael K.

doi:10.1016/j.jnucmat.2014.11.134

Title: A review of advantages of high-efficiency X-ray spectrum imaging for analysis of nanostructured ferritic alloys

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Abstract

Nanostructured ferritic alloys (NFAs) exhibit complex microstructures consisting of 100-500 nm ferrite grains, grain boundary solute enrichment, and multiple populations of precipitates and nanoclusters (NCs). Understanding these materials' excellent creep and radiation-tolerance properties requires a combination of multiple atomic-scale experimental techniques. Recent advances in scanning transmission electron microscopy (STEM) hardware and data analysis methods have the potential to revolutionize nanometer to micrometer scale materials analysis. The application of these methods is applied to NFAs as a test case and is compared to both conventional STEM methods as well as complementary methods such as scanning electron microscopy and atom probe tomography. In this paper, we review past results and present new results illustrating the effectiveness of latest-generation STEM instrumentation and data analysis.

Authors:

Parish, Chad M. ^[1]; Miller, Michael K. ^[1]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Publication Date:: Tue Dec 09 00:00:00 EST 2014

Research Org.:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)

Sponsoring Org.:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

OSTI Identifier:: 1234317

Alternate Identifier(s):: OSTI ID: 1246589

Grant/Contract Number:: AC05-00OR22725

Resource Type:: Accepted Manuscript

Journal Name:: Journal of Nuclear Materials

Additional Journal Information:: Journal Volume: 462; Journal ID: ISSN 0022-3115

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

Subject:: 36 MATERIALS SCIENCE

Citation Formats


                    Parish, Chad M., and Miller, Michael K. A review of advantages of high-efficiency X-ray spectrum imaging for analysis of nanostructured ferritic alloys.  United States: N. p., 2014. 
Web.  doi:10.1016/j.jnucmat.2014.11.134.

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                    Parish, Chad M., & Miller, Michael K. A review of advantages of high-efficiency X-ray spectrum imaging for analysis of nanostructured ferritic alloys.  United States.  https://doi.org/10.1016/j.jnucmat.2014.11.134

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                    Parish, Chad M., and Miller, Michael K. Tue .  
"A review of advantages of high-efficiency X-ray spectrum imaging for analysis of nanostructured ferritic alloys".  United States.  https://doi.org/10.1016/j.jnucmat.2014.11.134.  https://www.osti.gov/servlets/purl/1234317.

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@article{osti_1234317,

  title        = {A review of advantages of high-efficiency X-ray spectrum imaging for analysis of nanostructured ferritic alloys},

  author       = {Parish, Chad M. and Miller, Michael K.},

  abstractNote = {Nanostructured ferritic alloys (NFAs) exhibit complex microstructures consisting of 100-500 nm ferrite grains, grain boundary solute enrichment, and multiple populations of precipitates and nanoclusters (NCs). Understanding these materials' excellent creep and radiation-tolerance properties requires a combination of multiple atomic-scale experimental techniques. Recent advances in scanning transmission electron microscopy (STEM) hardware and data analysis methods have the potential to revolutionize nanometer to micrometer scale materials analysis. The application of these methods is applied to NFAs as a test case and is compared to both conventional STEM methods as well as complementary methods such as scanning electron microscopy and atom probe tomography. In this paper, we review past results and present new results illustrating the effectiveness of latest-generation STEM instrumentation and data analysis.},

  doi          = {10.1016/j.jnucmat.2014.11.134},

  journal      = {Journal of Nuclear Materials},

  number       = ,

  volume       = 462,

  place        = {United States},

  year         = {Tue Dec 09 00:00:00 EST 2014},

  month        = {Tue Dec 09 00:00:00 EST 2014}

}

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