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Nonisothermal Cure Kinetics of Epoxy/Polyvinylpyrrolidone Functionalized Superparamagnetic Nano-Fe3o4 Composites: Effect of Zn and Mn Doping Publisher



Jouyandeh M1 ; Ganjali MR1, 2 ; Seidi F3 ; Xiao H4 ; Saeb MR5
Authors
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Authors Affiliations
  1. 1. Center of Excellence in Electrochemistry, School of Chemistry, College of Science, University of Tehran, Tehran, 11155-4563, Iran
  2. 2. Biosensor Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, 11155-4563, Iran
  3. 3. Provincial Key Lab of Pulp and Paper Science and Technology and Joint International Research Lab of Lignocellulosic Functional Materials, Nanjing Forestry University, Nanjing, 210037, China
  4. 4. Department of Chemical Engineering, University of New Brunswick, Fredericton, E3B 5A3, NB, Canada
  5. 5. Department of Resin and Additives, Institute for Color Science and Technology, P.O. Box: 16765-654, Tehran, Iran

Source: Journal of Composites Science Published:2020


Abstract

The effects of the bulk and surface modification of nanoparticles on the cure kinetics of low-filled epoxy nanocomposites containing electrochemically synthesized polyvinylpyrrolidone (PVP) functionalized superparamagnetic iron oxide (PVP-SPIO), Zn-doped PVP-SPIO (Zn-PVP-SPIO), and Mn-doped PVP-SPIO (Mn-PVP-SPIO) were studied using differential scanning calorimetry (DSC) and cure kinetics analyses. Integral and differential isoconversional methods were used to calculate the activation energies (Eα) and consequently propose the appropriate reaction model for the curing reaction under nonisothermal conditions. According to the alteration of Eα versus the fractional extent of conversion, the Eα trend was changed through the partial replacement of Fe2+ sites by the Zn2+ and Mn2+ cations in the general formula of MxFe3-xO4, due to smaller amounts of energy being required for curing by the incorporation of Zn-PVP-SPIO and Mn-PVP-SPIO nanoparticles into the epoxy resin. A good agreement was observed between the theoretical calculation and the observed calorimetric data for the model validation. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
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