Using an electrochemical polymerization technique at room temperature, poly nicotine amide (PNA) was produced from the monomer nicotine amide (NA) in aqueous solution. The structure of polymer layer generated on the stainless steel surface (316 L) (working electrode) is investigated by Fourier Transmission Infrared Region (FT-IR). The anti-corrosion activity of polymer coating on the stainless steel (SS 316 L) is investigated by electrochemical polarization in 0.20M solution of HCl at 293-323K. The graphene -modified polymer film-coated SS had greater protection efficiency (PE percent) when compared to Nano ZnO -modified polymer film-coated SS. For the corrosion process of SS 316 L, kinetic and thermo-dynamic parameters of activation are estimated. The antibacterial activity of coated film has been tested on both gram positive as well as gram negative bacteria by well diffusion approach, which include Staphylococcus aureus (Staph.Aure) and Ecoli. Through adding nanoparticles to a monomer solution to raise the effecincy of the polymer against the corrosion and bacterial, As a result, after modifying poly nicotine amide with nanomaterial, the inhibition zone values increased (Nano ZnO and Graphene).
S Khalifa E, N Adil A, AS Mazin M…, 2008
Carbon dioxide geo-sequestration (CGS) into sediments in the form of (gas) hydrates is one proposed method for reducing anthropogenic carbon dioxide emissions to the atmosphere and, thus reducing global warming and climate change. However, there is a serious lack of understanding of how such CO2 hydrate forms and exists in sediments. We thus imaged CO2 hydrate distribution in sandstone, and investigated the hydrate morphology and cluster characteristics via x-ray micro-computed tomography in 3D in-situ. A substantial amount of gas hydrate (∼17% saturation) was observed, and the stochastically distributed hydrate clusters followed power-law relations with respect to their size distributions and surface area-volume relationships. The layer-
... Show MoreAutomated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 health
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