EFFECT OF SYNTHESIS PARAMETERS ON DIMENSIONAL CHARACTERISTICS OF Fe3O4 NANOPARTICLES: NEURAL-NETWORK RESEARCH

Autor:	I.M. Shevchenko, V.N. Kramarenko, A.A. Gvozdenko, А.A. Blinova, M.A. Yasnaya, A.V. Blinov, A.B. Golik
Jazyk:	ruština
Rok vydání:	2019
Předmět:	double iron oxide nanoparticles Materials science Artificial neural network neural network modeling lcsh:QD450-801 multilayer perceptron dynamic light scattering method lcsh:Physical and theoretical chemistry Biological system Fe3o4 nanoparticles response surface
Zdroj:	Физико-химические аспекты изучения кластеров, наноструктур и наноматериалов, Iss 11, Pp 298-306 (2019)
ISSN:	2658-4360 2226-4442
Popis:	Our research shows the possibility of using the neural-network processing of experimental data to study the influence of various factors on the process of synthesis of nanoscale Iron (II, III) oxide. A mathematical model was obtained which adequately describes the effect of temperature, stabilizer mass and precipitant quantity on the size of nanoparticles of Iron (II, III) oxide. The optimal synthesis conditions were determined, which provide a high content of Fe3O4 particles with an average hydrodynamic radius less than 100 nm.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47066fac032cae2c6e2fcb3f8e7c89b0 https://physchemaspects.ru/2019/doi-10-26456-pcascnn-2019-11-298/?lang=en Zobrazit plný text záznamu