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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Self-consistent ion beam analysis: An approach by multi-objective optimization

Texto completo
Autor(es):
Silva, T. F. [1] ; Rodrigues, C. L. [1] ; Added, N. [1] ; Rizzutto, M. A. [1] ; Tabacniks, M. H. [1] ; Hoschen, T. [2] ; von Toussaint, U. [2] ; Mayer, M. [2]
Número total de Autores: 8
Afiliação do(s) autor(es):
[1] Univ Sao Paulo, Inst Fis, Rua Matao, Trav R 187, BR-05508090 Sao Paulo - Brazil
[2] Max Planck Inst Plasma Phys, Boltzmannstr 2, D-85748 Garching - Germany
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION B-BEAM INTERACTIO; v. 506, p. 32-40, NOV 1 2021.
Citações Web of Science: 0
Resumo

Ion Beam Analysis (IBA) comprises a set of analytical techniques suited for material analysis, many of which are rather closely related. Self-consistent analysis of several IBA techniques takes advantage of this close relationship to combine different Ion Beam measurements in a unique model to obtain an improved characterization of the sample. This approach provides a powerful tool to obtain an unequivocal and reliable model of the sample, increasing confidence and reducing ambiguities. Taking advantage of the recognized reliability and quality of the simulations provided by SIMNRA, we developed a multi-process program for a self consistent analysis based on SIMNRA calculations. MultiSIMNRA uses computational algorithms to minimize an objective function running multiple instances of SIMNRA. With four different optimization algorithms, the code can handle sample and setup parameters (including correlations and constraints), to find the set of parameters that best fits simultaneously all experimental data. (AU)

Processo FAPESP: 12/00202-0 - Investigações científicas nos museus paulistas
Beneficiário:Márcia de Almeida Rizzutto
Modalidade de apoio: Auxílio à Pesquisa - Regular