Coal fly ash supported CoFe2O4 nanocomposites: Synergetic Fenton-like and photocatalytic degradation of methylene blue

光催化 材料科学 X射线光电子能谱 傅里叶变换红外光谱 纳米复合材料 粉煤灰 核化学 亚甲蓝 催化作用 扫描电子显微镜 化学工程 化学 纳米技术 复合材料 有机化学 工程类
作者
Nimra Nadeem,Muhammad Yaseen,Zulfiqar Ahmad Rehan,Muhammad Zahid,Abdul Shakoor,Asim Jilani,Javed Iqbal,Shahid Rasul,Imran Shahid
出处
期刊:Environmental Research [Elsevier]
卷期号:206: 112280-112280 被引量:47
标识
DOI:10.1016/j.envres.2021.112280
摘要

Rapid industrialization is causing a serious threat for the environment. Therefore, this research was aimed in developing ceramic cobalt ferrite (CoFe2O4) nanocomposite photocatalyst coated with coal fly ash (CFA-CoFe2O4) using facile hydrothermal synthesis route and their applications against methylene blue. The pristine cobalt ferrite photocatalyst was also prepared, characterized, and applied for efficiency comparison. Prepared photocatalyst were characterized by X-ray diffraction (XRD), fourier transformed infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy with energy dispersive spectroscopy (SEM/EDS). Optical response of catalysts was check using photoluminescence spectroscopy (PL). pH drift method was used for the surface charge characteristics of the material under acidic and basic conditions of solution pH. The photocatalytic degradation potential of all the materials were determined under ultra-violet irradiations. The influencing reaction parameters like pH, catalyst dose, oxidant dose, dye concentration, and irradiation time, were sequentially optimized to obtain best suited conditions. The 99% degradation of 10 ppm methylene blue was achieved within 60 min of reaction time under pH = 5 and 7, catalyst dose = 10 and 12 mg/100 mL, oxidant = 12 mM and 5 mM for cobalt ferrite and CFA-CoFe2O4 photocatalysts, respectively. Afterwards, the radical scavenging experiments were conducted to find out the effective radical scavengers (˙OH, h+, and e-) in photocatalytic degradation process. The kinetic study of the process was done by applying 1st order, 2nd order, and BMG models. Statistical assessment of interaction effect among experimental variables was achieved using response surface methodology (RSM).
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