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Surface characterizations and methylene blue pollutant removal efficiency of ZnO nanorods/biochar hybrids
In this study, the integration of carbon nanotube (CNT), graphene, and biochar (BC) with zinc oxide nanorods (ZnO NRs) was investigated for efficient water pollutant removal. Two types of ZnO NRs/BC hybrids (BC on top and bottom of ZnO NRs) were synthesized and compared to other carbon material‐based ZnO NRs combinations. Methylene blue (MB) adsorption efficiency was evaluated for various carbon material‐based ZnO NRs composites, revealing good performance in ZnO NRs/BC hybrids, particularly with BC on top. The adsorption efficiency reached an impressive 61.79% for ZnO NRs/BC, surpassing other configurations. MB removal by ZnO NRs/BC fitted well with pseudo‐first‐order kinetics and the rate constants of MB adsorption is 9.19 × 10−2 1/min (R2 = 0.9237). Surface characterizations revealed a distinctive distribution of BC grains, with denser aggregation observed on top of ZnO NRs. This unique distribution contributed to higher MB adsorption rates, substantiated by Fourier transform infrared spectroscopy (FTIR) analysis that showcased stronger MB adsorption in ZnO NRs/BC hybrids. Notably, the enhanced MB adsorption rates were attributed to the population of BC grains. This research establishes ZnO NRs/BC composites as promising candidates for effective water pollutant removal. The developed materials can be combined with the existed conventional wastewater treatment systems to further purify the water quality. ZnO NRs/BC hybrids achieve a remarkable 61.79% efficiency in removing MB pollutants, surpassing other carbon materials. MB removal using BC‐based materials follows pseudo‐first‐order kinetics. BC grains exhibit unique distribution patterns on ZnO NRs, with densely packed grains atop contributing to higher MB removal. FTIR analysis confirms increased MB‐related bond vibration, supporting the effectiveness of ZnO NRs/BC hybrids for water pollutant removal.
Surface characterizations and methylene blue pollutant removal efficiency of ZnO nanorods/biochar hybrids
In this study, the integration of carbon nanotube (CNT), graphene, and biochar (BC) with zinc oxide nanorods (ZnO NRs) was investigated for efficient water pollutant removal. Two types of ZnO NRs/BC hybrids (BC on top and bottom of ZnO NRs) were synthesized and compared to other carbon material‐based ZnO NRs combinations. Methylene blue (MB) adsorption efficiency was evaluated for various carbon material‐based ZnO NRs composites, revealing good performance in ZnO NRs/BC hybrids, particularly with BC on top. The adsorption efficiency reached an impressive 61.79% for ZnO NRs/BC, surpassing other configurations. MB removal by ZnO NRs/BC fitted well with pseudo‐first‐order kinetics and the rate constants of MB adsorption is 9.19 × 10−2 1/min (R2 = 0.9237). Surface characterizations revealed a distinctive distribution of BC grains, with denser aggregation observed on top of ZnO NRs. This unique distribution contributed to higher MB adsorption rates, substantiated by Fourier transform infrared spectroscopy (FTIR) analysis that showcased stronger MB adsorption in ZnO NRs/BC hybrids. Notably, the enhanced MB adsorption rates were attributed to the population of BC grains. This research establishes ZnO NRs/BC composites as promising candidates for effective water pollutant removal. The developed materials can be combined with the existed conventional wastewater treatment systems to further purify the water quality. ZnO NRs/BC hybrids achieve a remarkable 61.79% efficiency in removing MB pollutants, surpassing other carbon materials. MB removal using BC‐based materials follows pseudo‐first‐order kinetics. BC grains exhibit unique distribution patterns on ZnO NRs, with densely packed grains atop contributing to higher MB removal. FTIR analysis confirms increased MB‐related bond vibration, supporting the effectiveness of ZnO NRs/BC hybrids for water pollutant removal.
Surface characterizations and methylene blue pollutant removal efficiency of ZnO nanorods/biochar hybrids
Chen, Hung‐Hsiang (author) / Lu, Lin‐Sin (author) / Jhang, Jia‐Jie (author) / Lee, Chang‐Hsueh (author) / Chen, Hsiang (author) / Chen, Ku‐Fan (author)
2023-10-01
11 pages
Article (Journal)
Electronic Resource
English
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