Bayesian data analysis for ERDA measurements

Edelmann, Erik; Arstila, Kai; Keinonen, J.

doi:10.1016/j.nimb.2004.10.071

Cited by 5 publications

(3 citation statements)

References 5 publications

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“…Sample effects such as roughness will also result in an apparent concentration gradient, which is not real. One method of taking this into account is to use the apparent depth profiles generated with the direct method as raw data for a Bayesian inference analysis, based on a Monte Carlo calculations that considers all other effects, in order to derive the final depth profile 186 .…”

Section: Profile Extractionmentioning

confidence: 99%

Status of ion beam data analysis and simulation software

Raühala

Barradas

Fazinić

et al. 2006

Nuclear Instruments and Methods in Physics Research Section B:

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The status of ion beam data analysis codes dedicated to Rutherford backscattering, elastic recoil detection analysis, and non-resonant nuclear reaction analysis, is reviewed. The most important methods and approaches employed are discussed. The stopping power and scattering cross section databases used, the ion-target interaction physics, the experimental and detection system characteristics, and the structure of samples all have a strong impact on the analytical results. The models and algorithms used by different codes are reviewed and discussed in detail. Limitations in existing codes and perspectives for further developments are presented. The importance of ascertaining the correctness and accuracy of different methods and codes used in ion beam data analysis is stressed.

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Section: Profile Extractionmentioning

confidence: 99%

Status of ion beam data analysis and simulation software

Raühala

Barradas

Fazinić

et al. 2006

Nuclear Instruments and Methods in Physics Research Section B:

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“…Trajectories featuring multiple scattering are not computed directly in the 3D structure. An implementation of 2D or 3D sample features in an MC simulation program has been presented for MCERD [4], in which it was shown that AFM images could be used as an input for surface roughness. NDF [5] can simulate abstract geometrical shapes such as quantum dots [6].…”

Section: Introductionmentioning

confidence: 99%

Spectrum simulation of rough and nanostructured targets from their 2D and 3D image by Monte Carlo methods

Schiettekatte

Chicoine

2016

Nuclear Instruments and Methods in Physics Research Section B:

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Corteo is a program that implements Monte Carlo (MC) method to simulate ion beam analysis (IBA) spectra of several techniques by following the ions trajectory until a sufficiently large fraction of them reach the detector to generate a spectrum. Hence, it fully accounts for effects such as multiple scattering (MS). Here, a version of Corteo is presented where the target can be a 2D or 3D image. This image can be derived from micrographs where the different compounds are identified, therefore bringing extra information into the solution of an IBA spectrum, and potentially significantly constraining the solution. The image intrinsically includes many details such as the actual surface or interfacial roughness, or actual nanostructures shape and distribution. This can for example lead to the unambiguous identification of structures stoichiometry in a layer, or at least to better constraints on their composition. Because MC computes in details the trajectory of the ions, it simulates accurately many of its aspects such as ions coming back into the target after leaving it (re-entry), as well as going through a variety of nanostructures shapes and orientations. We show how, for example, as the ions angle of incidence becomes shallower than the inclination distribution of a rough surface, this process tends to make the effective roughness smaller in a comparable 1D simulation (i.e. narrower thickness distribution in a comparable slab simulation). Also, in ordered nanostructures, target reentry can lead to replications of a peak in a spectrum. In addition, bitmap description of the target can be used to simulate depth profiles such as those resulting from ion implantation, diffusion, intermixing, etc. Other improvements to Corteo include the possibility to interpolate the crosssection in angle-energy tables, and the generation of energy-depth maps.

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“…These laterally inhomogeneous samples constitute new challenges for simulation codes. Several models with different levels of generality have been developed for the simulation of IBA spectra from rough substrates or rough layers [6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]. A model for porous materials with random distribution of small spherical pores is described in [21].…”

Section: Introductionmentioning

confidence: 99%

Intercomparison of ion beam analysis software for the simulation of backscattering spectra from two-dimensional structures

Mayer

Malínský

Schiettekatte

et al. 2016

Nuclear Instruments and Methods in Physics Research Section B:

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The codes RBS-MAST, STRUCTNRA, F95-Rough and CORTEO are simulation codes for ion beam analysis spectra from two-or three-dimensional sample structures. The codes were intercompared in a code-code comparison using an idealized grating structure and by comparison to experimental data from a silicon grating on tantalum interlayer. All codes are in excellent agreement at higher incident energies and not too large energy losses. At lower incident energies, grazing angles of incidence and/or larger energy losses plural scattering effects play an increasing role. Simulation codes with plural scattering capabilities offer higher accuracy and better agreement to experimental results in this regime.

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Bayesian data analysis for ERDA measurements

Cited by 5 publications

References 5 publications

Status of ion beam data analysis and simulation software

Status of ion beam data analysis and simulation software

Spectrum simulation of rough and nanostructured targets from their 2D and 3D image by Monte Carlo methods

Intercomparison of ion beam analysis software for the simulation of backscattering spectra from two-dimensional structures

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