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Computer simulation of backscattering spectra from paint

Mayer, M. ; Silva, T.F.

Nuclear instruments & methods in physics research. Section B, Beam interactions with materials and atoms, 2017-09, Vol.406, p.75-81 [Periódico revisado por pares]

Elsevier B.V

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  • Título:
    Computer simulation of backscattering spectra from paint
  • Autor: Mayer, M. ; Silva, T.F.
  • Assuntos: Ion beam analysis ; Lateral inhomogeneity ; Paint ; STRUCTNRA
  • É parte de: Nuclear instruments & methods in physics research. Section B, Beam interactions with materials and atoms, 2017-09, Vol.406, p.75-81
  • Descrição: To study the role of lateral non-homogeneity on backscattering analysis of paintings, a simplified model of paint consisting of randomly distributed spherical pigment particles embedded in oil/binder has been developed. Backscattering spectra for lead white pigment particles in linseed oil have been calculated for 3MeVH+ at a scattering angle of 165° for pigment volume concentrations ranging from 30vol.% to 70vol.% using the program STRUCTNRA. For identical pigment volume concentrations the heights and shapes of the backscattering spectra depend on the diameter of the pigment particles: This is a structural ambiguity for identical mean atomic concentrations but different lateral arrangement of materials. Only for very small pigment particles the resulting spectra are close to spectra calculated supposing atomic mixing and assuming identical concentrations of all elements. Generally, a good fit can be achieved when evaluating spectra from structured materials assuming atomic mixing of all elements and laterally homogeneous depth distributions. However, the derived depth profiles are inaccurate by a factor of up to 3. The depth range affected by this structural ambiguity ranges from the surface to a depth of roughly 0.5–1 pigment particle diameters. Accurate quantitative evaluation of backscattering spectra from paintings therefore requires taking the correct microstructure of the paint layer into account.
  • Editor: Elsevier B.V
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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