2012
DOI: 10.1016/j.cocis.2011.11.001
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Phase-sensitive specular neutron reflectometry for imaging the nanometer scale composition depth profile of thin-film materials

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Cited by 174 publications
(179 citation statements)
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“…At any time the user may generate a (Python) problem definition file for the powerful Refl1d [8] fitting program by pressing a button in the application. This definition is based on the current snapshot of the model as displayed in the application, and will essentially replicate the structure defined there in a way that is understood by Refl1d.…”
Section: # "Polarization": "++"mentioning
confidence: 99%
See 2 more Smart Citations
“…At any time the user may generate a (Python) problem definition file for the powerful Refl1d [8] fitting program by pressing a button in the application. This definition is based on the current snapshot of the model as displayed in the application, and will essentially replicate the structure defined there in a way that is understood by Refl1d.…”
Section: # "Polarization": "++"mentioning
confidence: 99%
“…The reflectivity calculations are accomplished through wrapping of the C99 calculation kernels (polarized and unpolarized) in the Refl1d [8] fitting program, which were ported to javascript through Emscripten, after a slight modification to include Nevot-Croce roughness approximation in the magnetic calculations.…”
Section: Software Librariesmentioning
confidence: 99%
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“…PNR data were modeled using the Refl1D software package. 26,37 PNR of a capped/uncapped sample pair for a nominal Gd thickness of 10 nm is shown in Figure 2(top) as circles alongside a theoretical fit to the data (line), while Figure 2(bottom) shows the models used to fit the data. As expected, the thicknesses of the LSMO layers match extremely well.…”
mentioning
confidence: 99%
“…This model was found to fit the data better than 3 discrete layers with sharp interfaces, even at the highest applied fields. The 2 σ uncertainty for the high and low z magnetizations was calculated using a Markov chain Monte Carlo algorithm, [18][19][20] and was found to be less than 10 kA m −1 for all values.…”
mentioning
confidence: 99%