Search Results (2)

This study investigates the potential of corn cob-derived biochars produced at 400 °C (BC400) and 700 °C (BC700) as heterogeneous catalysts for the degradation of organochlorine pesticides, lindane and β-endosulfan, through persulfate-based advanced oxidation processes (AOPs). BC700 exhibited enhanced degradation performance compared to BC400, likely due to its greater surface area, higher aromaticity, and lower surface polarity. Under optimized conditions (3.0 mM persulfate, pH 7.02, 0.2 g/L biochar), BC700 enabled the removal of up to 94% of β-endosulfan and 82% of lindane within four hours. Quenching experiments suggested different dominant degradation pathways: singlet oxygen (¹O₂) appeared to play a key role in lindane degradation, while β-endosulfan degradation likely involved both radical (SO₄^•−, HO^•) and non-radical mechanisms. Reusability tests indicated that BC700 retained catalytic activity for β-endosulfan across multiple cycles, whereas lindane degradation efficiency decreased, possibly due to surface fouling or catalyst deactivation. Experiments conducted in real surface water highlighted the influence of matrix components, with partial inhibition observed for β-endosulfan and an unexpected improvement in lindane removal. These results point to the promise of high-temperature corn cob biochar as a selective and potentially reusable catalyst for AOPs in water treatment, warranting further investigation into regeneration strategies and matrix-specific effects. Full article

Due to Internet of Things (IoT), it has become easy to surveil the critical regions. Images are important parts of Surveillance Systems, and it is required to protect the images during transmission and storage. These secure surveillance frameworks are required in IoT systems, because any kind of information leakage can thwart the legal system as well as personal privacy. In this paper, a secure surveillance framework for IoT systems is proposed using image encryption. A hyperchaotic map is used to generate the pseudorandom sequences. The initial parameters of the hyperchaotic map are obtained using partial-regeneration-based non-dominated optimization (PRNDO). The permutation and diffusion processes are applied to generate the encrypted images, and the convolution neural network (CNN) can play an essential role in this part. The performance of the proposed framework is assessed by drawing comparisons with competitive techniques based on security parameters. It shows that the proposed framework provides promising results as compared to the existing techniques. Full article