Electron beam induced crystallization of amorphous Al-based alloys in the TEM

Stratton, William G.; Hamann, Joe; Perepezko, John H.; Voyles, Paul M.

doi:10.1016/j.intermet.2006.01.025

Cited by 25 publications

(12 citation statements)

References 26 publications

(35 reference statements)

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“…For a-Si, films need to be <25 nm in thickness (Voyles, 2001). When FEM is used for higher Z materials, such as chalcogenides (Kwon et al, 2007; Lee et al, 2009; Darmawikarta et al, 2013) and amorphous metals (Stratton et al, 2004, 2005, 2006), multiple scattering effects need to be considered. When the scattering factor is independent of angle, the average number of scattering events n iswhere n is the number of scattering events, t the thickness, and Λ the total mean free path for all elastic scattering processes (Treacy & Gibson, 1993).…”

Section: Artifact Correction Via Pattern Screeningmentioning

confidence: 99%

Quantitative Fluctuation Electron Microscopy in the STEM: Methods to Identify, Avoid, and Correct for Artifacts

Bogle

Abelson

2014

Microsc Microanal

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Fluctuation electron microscopy can reveal the nanoscale order in amorphous materials via the statistical variance in the scattering intensity as a function of position, scattering vector, and resolution. However, several sources of experimental artifacts can seriously affect the magnitude of the variance peaks. The use of a scanning transmission electron microscope for data collection affords a convenient means to check whether artifacts are present. As nanodiffraction patterns are collected in serial, any spatial or temporal dependence of the scattering intensity across the series can easily be detected. We present examples of the major types of artifact and methods to correct the data or to avoid the problem experimentally. We also re-cast the statistical formalism used to identify sources of noise in view of the present results. The present work provides a basis on which to perform fluctuation electron microscopy with a high level of reliability and confidence in the quantitative magnitude of the data.

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Section: Artifact Correction Via Pattern Screeningmentioning

confidence: 99%

Quantitative Fluctuation Electron Microscopy in the STEM: Methods to Identify, Avoid, and Correct for Artifacts

Bogle

Abelson

2014

Microsc Microanal

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“…By analyzing the variance in TEM image contrast within an amorphous sample, regions have been identified that exhibit aluminum-like order on sub nanometer size scales [20]. Previous study on Al 92 Sm 8 amorphous samples has determined that the ordering is like that of FCC aluminum and not rare earth centered icosahedra or the intermetallic Al 11 Sm 3 phase [8].…”

Section: Primary Crystallizationmentioning

confidence: 99%

Nanostructure development during devitrification and deformation

Perepezko

Imhoff

Hebert

2010

Journal of Alloys and Compounds

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“…As seen, more energy can be transferred to lighter elements. Since the atoms are randomly distributed in the amorphous films, the displacement energy (E d ) can have different values for the same element depending on the atomic position [26] . An estimation of the displacement energies can be given from displacement energies for the materials in crystalline structure.…”

Section: Resultsmentioning

confidence: 99%