Development of Efficient and Recyclable ZnO-CuO/g-C3N4 Nanocomposite for Enhanced Adsorption of Arsenic from Wastewater

Nanomaterials (Basel). 2022 Nov 12;12(22):3984. doi: 10.3390/nano12223984.

Abstract

Arsenic (III) is a toxic contaminant in water bodies, especially in drinking water reservoirs, and it is a great challenge to remove it from wastewater. For the successful extraction of arsenic (III), a nanocomposite material (ZnO-CuO/g-C3N4) has been synthesized by using the solution method. The large surface area and plenty of hydroxyl groups on the nanocomposite surface offer an ideal platform for the adsorption of arsenic (III) from water. Specifically, the reduction process involves a transformation from arsenic (III) to arsenic (V), which is favorable for the attachment to the -OH group. The modified surface and purity of the nanocomposite were characterized by SEM, EDX, XRD, FT-IR, HRTEM, and BET models. Furthermore, the impact of various aspects (temperatures, pH of the medium, the concentration of adsorbing materials) on adsorption capacity has been studied. The prepared sample displays the maximum adsorption capacity of arsenic (III) to be 98% at pH ~ 3 of the medium. Notably, the adsorption mechanism of arsenic species on the surface of ZnO-CuO/g-C3N4 nanocomposite at different pH values was explained by surface complexation and structural variations. Moreover, the recycling experiment and reusability of the adsorbent indicate that a synthesized nanocomposite has much better adsorption efficiency than other adsorbents. It is concluded that the ZnO-CuO/g-C3N4 nanocomposite can be a potential candidate for the enhanced removal of arsenic from water reservoirs.

Keywords: ZnO–CuO/g–C3N4 nanocomposite; adsorption; arsenic removal; kinetic studies; solution combustion.

Grants and funding

This work was supported by research grants from the Natural Science Foundation of Shanghai (Grant 17ZR1402600), the Shanghai Science and Technology Innovation Action Plan, Belt & Road Young Scientist Program (Grant No. 19160745500), the Natural Science Foundation of Guangdong Province of China (Grant No. 2022A1515011368), the National Natural Science Foundation of China (Grant No. 81870307, 82270413) and The Key Projects of Department of Education of Guangdong Province of China (Grant No. 2022ZDZX2057, 2022ZXKC474). This work was funded by the Researchers Supporting Project Number (RSP-2021/243), King Saud University, Riyadh, Saudi Arabia.