Effect of synthesis parameters on dimensional characteristics of fe3o4 nanoparticles: neural-network research

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 m...

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Bibliografiska uppgifter
Huvudupphovsmän:	Blinov, A. V., Блинов, А. В., Gvozdenko, A. A., Гвозденко, А. А., Yasnaya, M. A., Ясная, М. А., Golik, A. B., Голик, А. Б., Blinova, A. A., Блинова, А. А., Shevchenko, I. M., Шевченко, И. М., Kramarenko, V. N., Крамаренко, В. Н.
Materialtyp:	Статья
Språk:	Russian
Publicerad:	TVER STATE UNIV 2020
Ämnen:	Double iron oxide nanoparticles Neural network modeling Multilayer perception; Response surface Dynamic light scattering method
Länkar:	http://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=7&SID=E1foOAlVMmMF3jxHUZa&page=1&doc=1 https://dspace.ncfu.ru/handle/20.500.12258/11478
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Sammanfattning:	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

Effect of synthesis parameters on dimensional characteristics of fe3o4 nanoparticles: neural-network research

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