Hydrothermal Synthesis of Hematite Nanoparticles Decorated on Carbon Mesospheres and Their Synergetic Action on the Thermal Decomposition of Nitrocellulose.
Abdenacer BenhammadaDjalal TracheMohamed KesraouiSalim ChelouchePublished in: Nanomaterials (Basel, Switzerland) (2020)
In this study, carbon mesospheres (CMS) and iron oxide nanoparticles decorated on carbon mesospheres (Fe2O3-CMS) were effectively synthesized by a direct and simple hydrothermal approach. α-Fe2O3 nanoparticles have been successfully dispersed in situ on a CMS surface. The nanoparticles obtained have been characterized by employing different analytical techniques encompassing Fourier transform infrared (FTIR) spectroscopy, Raman spectroscopy, X-ray diffraction (XRD) and scanning electron microscopy (SEM). The produced carbon mesospheres, mostly spherical in shape, exhibited an average size of 334.5 nm, whereas that of Fe2O3 supported on CMS is at around 80 nm. The catalytic effect of the nanocatalyst on the thermal behavior of cellulose nitrate (NC) was investigated by utilizing differential scanning calorimetry (DSC). The determination of kinetic parameters has been carried out using four isoconversional kinetic methods based on DSC data obtained at various heating rates. It is demonstrated that Fe2O3-CMS have a minor influence on the decomposition temperature of NC, while a noticeable diminution of the activation energy is acquired. In contrast, pure CMS have a slight stabilizing effect with an increase of apparent activation energy. Furthermore, the decomposition reaction mechanism of NC is affected by the introduction of the nano-catalyst. Lastly, we can infer that Fe2O3-CMS may be securely employed as an effective catalyst for the thermal decomposition of NC.
Keyphrases
- electron microscopy
- high resolution
- reduced graphene oxide
- raman spectroscopy
- highly efficient
- ionic liquid
- room temperature
- iron oxide nanoparticles
- nitric oxide
- magnetic resonance
- quantum dots
- drinking water
- electronic health record
- risk assessment
- machine learning
- visible light
- anaerobic digestion
- high speed
- walled carbon nanotubes