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Abstract

In this study, a stable and effective magnetically recoverable nanocatalyst was prepared by coating Fe 3O 4 nanoparticles with SiO 2, followed by functionalization with N-(2-aminoethyl)- 3-aminopropyltrimethoxysilane (AEPTMS) and produce Schiff base ligand to linkage Ru(OTf) 2 onto the surface. The nanocatalyst was characterized using various techniques such as FT-IR spectroscopy, SEM, TEM, and VSM to confirm its successful synthesis. The nanocatalyst was used for the trimethylsilylation of various alcohols (primary, secondary, and tertiary alcohols) using hexamethyldisilazane as a silylating agent in dichloromethane at room temperature. The reaction proceeded quickly with a protection time of only 90 seconds, which is a remarkable advantage of this nanocatalyst. The turnover frequency (TOF) values of the catalytic system were estimated to be 1869 h -1. The use of this nanocatalyst offers many advantages, such as excellent yield, catalyst reusability, high acidity, and strong magneticp roperties. These advantages make it a fascinating candidate for green chemistry principles. The simple reprocessing procedure and quick response times are also additional benefits of this nanocatalyst. Overall, this study provides a promising approach for the facile preparation of a stable and effective magnetically recoverable nanocatalyst that can be utilized for the trimethylsilylation of alcohols. The exceptional properties of this catalyst make it an attractive candidate for practical applications in the field of catalysis.
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Authors and Affiliations

Somayeh Mehdigholami
1
Esmaeil Koohestanian
2

  1. Young Researchers and Elite Club, Iranshahr Branch, Islamic Azad University, Iranshahr, Iran
  2. Department of Chemical Engineering, Iranshahr Branch, Islamic Azad University, Iranshahr, Iran
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Abstract

Land use dynamics describes the changes occurring in an area which can be approximated from a land use and land cover map (LULC). This research aims to assess how the mangrove forest in the Niger Delta Region has degraded. Landsat imagery of 1987, 2002, and 2022 were used to create LULC maps from which change detection of the area derived from supervised classification technique, were investigated. The classification accuracy was determined and the result shows that for 1987, 2002, and 2022 the accuracy score are 82.16%, 82.16%, and 83.97%, respectively and the corresponding kappa coefficients for the epochs are 75.63%, 75.63%, and 78.43%. The producer and user accuracy are high for all the classes except grassland and urban areas. The change detection result showed a net loss in mangrove, grassland, and water bodies between 1987 and 2002 with significant gains for urban and woodlands however significant losses were revealed in the mangrove, woodlands, water bodies, and grassland with gains in only the urban settlement between the 2002 and 2022 study period. The result also revealed that the mangrove forest cover has seen a consistent loss in the two study periods. The Niger Delta Region is a key component of the global climate system and our research provides an accurate assessment of the land use dynamics and the mangrove degradation in the region.
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Authors and Affiliations

Ibrahim Opeyemi Isiaka
1
Tata Herbert
1
Samuel Olumide Akande
1

  1. Federal University of Technology, Akure, Nigeria

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