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Degradation

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Hussein Ali Shnawa – One of the best experts on this subject based on the ideXlab platform.

  • Thermal stabilization of polyvinyl chloride with traditional and naturally derived antioxidant and thermal stabilizer synthesized from tannins
    Journal of Thermal Analysis and Calorimetry, 2017
    Co-Authors: Hussein Ali Shnawa
    Abstract:

    The effects of tannin-cadmium complex on the thermal and oxidation stability of PVC were investigated. Tannin-cadmium complex has been successfully synthesized and characterized by Fourier transform infrared spectroscopy, scanning electron microscopy and energy-dispersive X-ray analysis techniques. Thermal Degradation and thermal oxidoxidationDegradation behaviors of PVC formulations obtained by thermal mixing method were evaluated by thermogravimetric analysis (TG) and differential scanning calorimetry (DSC) under inert and oxidizing atmospheres, respectively. The obtained results such as the onset, maximum and final Degradation temperatures as well as the Degradation rates from TG and DTG curves revealed that the tannin-cadmium has significant impact on the thermal stability of PVC. The experimental data of PVC thermal Degradation obtained by DSC studies also clearly showed that the stabilizing efficiency of tannin-cadmium is superior to that of synthetic thermal stabilizer applied as reference. Due to the HCl scavenging and antioxidation activities of tannin-cadmium, the global thermal and morphological properties of PVC stabilized by this product proved the best in morphology and stabilization properties both against thermal and thermal oxidoxidationDegradations. Graphical abstract

Lei Zhang – One of the best experts on this subject based on the ideXlab platform.

  • learning a single convolutional super resolution network for multiple Degradations
    Computer Vision and Pattern Recognition, 2018
    Co-Authors: Kai Zhang, Lei Zhang
    Abstract:

    Recent years have witnessed the unprecedented success of deep convolutional neural networks (CNNs) in single image super-resolution (SISR). However, existing CNN-based SISR methods mostly assume that a low-resolution (LR) image is bicubicly downsampled from a high-resolution (HR) image, thus inevitably giving rise to poor performance when the true Degradation does not follow this assumption. Moreover, they lack scalability in learning a single model to nonblindly deal with multiple Degradations. To address these issues, we propose a general framework with dimensionality stretching strategy that enables a single convolutional super-resolution network to take two key factors of the SISR Degradation process, i.e., blur kernel and noise level, as input. Consequently, the super-resolver can handle multiple and even spatially variant Degradations, which significantly improves the practicability. Extensive experimental results on synthetic and real LR images show that the proposed convolutional super-resolution network not only can produce favorable results on multiple Degradations but also is computationally efficient, providing a highly effective and scalable solution to practical SISR applications.

  • learning a single convolutional super resolution network for multiple Degradations
    Computer Vision and Pattern Recognition, 2018
    Co-Authors: Kai Zhang, Wangmeng Zuo, Lei Zhang
    Abstract:

    Recent years have witnessed the unprecedented success of deep convolutional neural networks (CNNs) in single image super-resolution (SISR). However, existing CNN-based SISR methods mostly assume that a low-resolution (LR) image is bicubicly downsampled from a high-resolution (HR) image, thus inevitably giving rise to poor performance when the true Degradation does not follow this assumption. Moreover, they lack scalability in learning a single model to nonblindly deal with multiple Degradations. To address these issues, we propose a general framework with dimensionality stretching strategy that enables a single convolutional super-resolution network to take two key factors of the SISR Degradation process, i.e., blur kernel and noise level, as input. Consequently, the super-resolver can handle multiple and even spatially variant Degradations, which significantly improves the practicability. Extensive experimental results on synthetic and real LR images show that the proposed convolutional super-resolution network not only can produce favorable results on multiple Degradations but also is computationally efficient, providing a highly effective and scalable solution to practical SISR applications.

  • learning a single convolutional super resolution network for multiple Degradations
    arXiv: Computer Vision and Pattern Recognition, 2017
    Co-Authors: Kai Zhang, Lei Zhang
    Abstract:

    Recent years have witnessed the unprecedented success of deep convolutional neural networks (CNNs) in single image super-resolution (SISR). However, existing CNN-based SISR methods mostly assume that a low-resolution (LR) image is bicubicly downsampled from a high-resolution (HR) image, thus inevitably giving rise to poor performance when the true Degradation does not follow this assumption. Moreover, they lack scalability in learning a single model to deal with multiple Degradations. To address these issues, we propose a dimensionality stretching strategy that enables a single convolutional super-resolution network to take two key factors of the SISR Degradation process, i.e., blur kernel and noise level, as input. Consequently, the proposed super-resolver can handle multiple and even spatially variant Degradations, which significantly improves the practicability. Extensive experimental results on synthetic and real LR images show that the proposed convolutional super-resolution network not only can produce favorable results on multiple Degradations but also is computationally efficient, providing a highly effective and scalable solution to practical SISR applications.

Mehrdad Seifali Abbas-abadi – One of the best experts on this subject based on the ideXlab platform.

  • The effect of process and structural parameters on the stability, thermo-mechanical and thermal Degradation of polymers with hydrocarbon skeleton containing PE, PP, PS, PVC, NR, PBR and SBR
    Journal of Thermal Analysis and Calorimetry, 2020
    Co-Authors: Mehrdad Seifali Abbas-abadi
    Abstract:

    Many studies have been done on the stability, thermo-mechanical Degradation and pyrolysis of polymers with hydrocarbon skeleton. According to the main structure, side groups, with and without double bond in the structure, polymer has different responses in reference to the thermo-mechanical and thermal Degradations. The polymers in extruder are faced with thermo-mechanical Degradation while with appropriate stability against thermo-mechanical Degradation, the shelf time of the final products increases, and the polymeric wastes are reduced. On the other hand, the structural and process parameters can significantly affect the resulting pyrolysis products as suitable process to reduce the non-recyclable polymers. Also the literature review in this field containing reactor and TG studies shows that the chemical bonds and the related Degradation mechanisms can affect the quality and quantity of the pyrolytic products obviously. For this purpose, the effects of different molecular specifications, additives and related effective parameters on the thermal stability and the thermo-mechanical Degradation of plastics are considered. Meanwhile, the mechanisms of Degradation, the share of each mechanism, the related products under different structural and process parameters and the needed activation energy for all of the studied polymers are investigated to reduce the polymeric wastes sent to landfills.

Koray Ozturk – One of the best experts on this subject based on the ideXlab platform.

  • pure zno and composite zno tio2 catalyst plates a comparative study for the Degradation of azo dye pesticide and antibiotic in aqueous solutions
    Journal of Colloid and Interface Science, 2014
    Co-Authors: Eylem Topkaya, Mehmet Konyar, Cengiz H Yatmaz, Koray Ozturk
    Abstract:

    Abstract Photocatalytic Degradations of azo dye (RR 180), pesticide (2,4-D) and antibiotic (enrofloxacin) in aqueous solutions were performed and compared by using pure ZnO and ZnO/TiO2 composite (at 1:1 ZnO to TiO2 mole ratio) catalysts in a self-supporting plate form. The plates were produced by tape casting of the constituent powder slurries and sintering at 600 °C. Photocatalytic Degradations of these pollutants were carried out under UVA and UVC irradiations for 120 min. Maximum Degradation was obtained for 2,4-D solution using pure ZnO plates under UVC. Due to the photolysis effect, UVC wavelength yielded higher efficiency values for all the chemicals than UVA. The discrepancy in the photocatalytic performances of the pure ZnO and the ZnO/TiO2 composite plates were not found to be significant. The plates were found to be effective for the consecutive Degradation tests which indicated their potentiality in extended applications.

Eylem Topkaya – One of the best experts on this subject based on the ideXlab platform.

  • pure zno and composite zno tio2 catalyst plates a comparative study for the Degradation of azo dye pesticide and antibiotic in aqueous solutions
    Journal of Colloid and Interface Science, 2014
    Co-Authors: Eylem Topkaya, Mehmet Konyar, Cengiz H Yatmaz, Koray Ozturk
    Abstract:

    Abstract Photocatalytic Degradations of azo dye (RR 180), pesticide (2,4-D) and antibiotic (enrofloxacin) in aqueous solutions were performed and compared by using pure ZnO and ZnO/TiO2 composite (at 1:1 ZnO to TiO2 mole ratio) catalysts in a self-supporting plate form. The plates were produced by tape casting of the constituent powder slurries and sintering at 600 °C. Photocatalytic Degradations of these pollutants were carried out under UVA and UVC irradiations for 120 min. Maximum Degradation was obtained for 2,4-D solution using pure ZnO plates under UVC. Due to the photolysis effect, UVC wavelength yielded higher efficiency values for all the chemicals than UVA. The discrepancy in the photocatalytic performances of the pure ZnO and the ZnO/TiO2 composite plates were not found to be significant. The plates were found to be effective for the consecutive Degradation tests which indicated their potentiality in extended applications.