journal article·2021-02

Highly effective removal of phosphate from complex water environment with porous Zr-bentonite alginate hydrogel beads: Facile synthesis and adsorption behavior study

Huan Xi, Qingqing Li, Yan Yang, Jianfeng Zhang, Feng Guo, Xiaogang Wang, Shikai Xu, Shiping Ruan

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Abstract

Abstract The development of an effective phosphate removal strategy is still considered to be an important challenge in the field of wastewater remediation. In this study, novel alginate immobilized Zr-bentonite hydrogel beads were synthesized assisted by Zr-modification and Na2CO3 + HCl pore forming (abbreviated as NH-SA-ZrBT), that led to an enhancement in the specific surface area and porosity. The novel NH-SA-ZrBT adsorbent exhibited a high stability and adsorption selectivity for phosphate from complex water environments with various competitive anions, NaCl salinity and humic acid. The isotherm was fitted well by both Langmuir and Freundlich models, suggesting that the adsorption process was the chemisorption and the hydrogel beads could function through a variety of mechanisms. The maximum adsorption capacity of NH-SA-ZrBT for phosphate was calculated to be 63.61 mg/g at 25 °C by Langmuir model and had a high retention of 92.2% after five adsorption-desorption cycles. The kinetic data were better fitted by the pseudo-second model. Considering the zeta potential and XPS data before and after the phosphate adsorption, the adsorption mechanism was proposed to be a combination of electrostatic attraction, ligand exchange and inner sphere complexation. The present study demonstrates a new strategy for the fabrication of stable, separable and low-cost bentonite-containing hydrogel beads for phosphate removal from complex wastewater.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Phosphorus and nutrient management · Layered Double Hydroxides Synthesis and Applications · Parathyroid Disorders and Treatments

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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