1 Ocak 2015 Dergi makalesi Açık Erişim

Kiransan, Murat; Khataee, Alireza; Karaca, Semra; Sheydaei, Mohsen

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  "@context": "https://schema.org/", 
  "@id": 76577, 
  "@type": "ScholarlyArticle", 
  "creator": [
    {
      "@type": "Person", 
      "affiliation": "Ataturk Univ, Fac Sci, Dept Chem, TR-25240 Erzurum, Turkey", 
      "name": "Kiransan, Murat"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Univ Tabriz, Fac Chem, Dept Appl Chem, Res Lab Adv Water & Wastewater Treatment Proc, Tabriz, Iran", 
      "name": "Khataee, Alireza"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Ataturk Univ, Fac Sci, Dept Chem, TR-25240 Erzurum, Turkey", 
      "name": "Karaca, Semra"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Univ Tabriz, Fac Chem, Dept Appl Chem, Res Lab Adv Water & Wastewater Treatment Proc, Tabriz, Iran", 
      "name": "Sheydaei, Mohsen"
    }
  ], 
  "datePublished": "2015-01-01", 
  "description": "In this study, the photocatalytic ability of ZnO/Montmorilonite (ZnO/MMT) nanocomposite under UV-A, UV-B and UV-C radiation was investigated. ZnO nanoparticles were synthesized on the surface of MMT and used as photocatalyst in decolorization of Disperse Red 54 (DR54) solution. Synthesized nanocomposite was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) techniques and nitrogen adsorption/desorption isotherms curves. The average width of synthesized ZnO particles is in the range of 30-45 nm. Effect of UV light regions, initial dye concentration, initial dosage of nanocomposite, and reusability of catalyst was studied on decolorization efficiency. The highest decolorization efficiency was achieved under UV-C radiation. A three-layered feed forward back propagation artificial neural network model was developed to predict the photocatalysis of DR54 under UV-C radiation. According to ANN model the ZnO/MMT dosage with a relative importance of 49.21% is the most influential parameter in the photocatalytic decolorization process. (C) 2015 Elsevier B.V. All rights reserved.", 
  "headline": "Artificial neural network modeling of photocatalytic removal of a disperse dye using synthesized of ZnO nanoparticles on montmorillonite", 
  "identifier": 76577, 
  "image": "https://aperta.ulakbim.gov.tr/static/img/logo/aperta_logo_with_icon.svg", 
  "license": "http://www.opendefinition.org/licenses/cc-by", 
  "name": "Artificial neural network modeling of photocatalytic removal of a disperse dye using synthesized of ZnO nanoparticles on montmorillonite", 
  "url": "https://aperta.ulakbim.gov.tr/record/76577"
}