EVOLUTIONARY QUANTITATIVE FULL-PROFILE X-RAY PHASE ANALYSIS BASED ON THE RIETVELD METHOD, A SELF-CONFIGURABLE MULTIPOPULATION GENETIC ALGORITHM AND ELEMENTAL ANALYSIS DATA

Autor:	Sergey V. Burakov, Igor S. Yakimov, Aleksandr Zaloga, P. S. Dubinin, Oksana E. Bezrukova, Konstantin A. Gusev, M. E. Semenkina
Rok vydání:	2018
Předmět:	Set (abstract data type) Software business.industry Elemental analysis Computer science Computer cluster Personal computer Genetic algorithm Evolutionary algorithm Sample (statistics) Condensed Matter Physics business Algorithm
Zdroj:	Industrial laboratory. Diagnostics of materials. 84:25-31
ISSN:	2588-0187 1028-6861
DOI:	10.26896/1028-6861-2018-84-3-25-31
Popis:	We developed a self configuring genetic algorithm to quantify phase concentrations in a crystalline sample from powder X-ray diffraction data. The algorithm does not require the fine-tuning of parameters, which is inherent to most evolutionary algorithms. The software executing the algorithm uses parallel computing and allows performing reference-free quantitative phase analysis on a personal computer, a computing cluster or with the help of a computer network. The suggested method was tested on a set of trial samples with known composition. It was demonstrated that one may use data on the chemical composition of a sample to increase the accuracy of quantitative phase analysis.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8a68d55c87760c65597f4d4e5cef68fb https://doi.org/10.26896/1028-6861-2018-84-3-25-31 Zobrazit plný text záznamu