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Efficient treatment of chromium-containing wastewater based on auxiliary intelligent model with rapid-response adsorbents

吸附 废水 污水处理 废物管理 环境科学 工艺工程 化学 工程类 有机化学
作者
Biao Yuan,Zhenglu Yang,Pan Wu,Xingbo Yin,Changjun Liu,Fujin Sun,Jian He,Wei Jiang
出处
期刊:Separation and Purification Technology [Elsevier BV]
卷期号:363: 132037-132037 被引量:19
标识
DOI:10.1016/j.seppur.2025.132037
摘要

• The adsorbent showed excellent adsorption capacity of up to 97.9 mg/g for Cr(VI). • Exhibited a rapid-response and high-efficiency performance. • Showed excellent removal result of Cr(VI) in simulated and real solutions. • Analyzed and predicted adsorption results by auxiliary intelligent model. • Scaled-up experiments showed attractive potential for industrialization. Wastewater containing chromium ions (Cr(VI)) presents substantial environmental pollution risks and is governed by stringent regulations. However, due to fluctuations in industrial production, the Cr(VI) concentrations in such wastewater vary significantly. This study employs rapid-response adsorbents in the wastewater treatment process, leading to a remarkable improvement in treatment speed. The adsorbent features an amorphous structure with –OH and Zr-OH groups present on its surface. During the adsorption process, the adsorbent surface showed a positive charge, enabling excellent adsorption performance for the Cr(VI) anion. The adsorption capacity reaches up to 97.9 mg/g. The Density Functional Theory (DFT) calculations verify negative adsorption energies. The Langmuir isotherm modeling and pseudo-second-order kinetic suggest that the adsorption process is a monolayer one, predominantly governed by chemisorption. The low activation energy of 6.78 kJ/mol indicates the rapid responsiveness of the adsorbent to Cr(VI). The adsorbent exhibits excellent performance in removing Cr(VI) from both simulated and real Cr(VI)-containing wastewater within 30 min, and the chromium concentration meets the emission standards. The adsorption results were effectively analyzed and predicted using an artificial neural network (ANN) model with two hidden layers, achieving an R 2 of 0.988. The solution scale-up experiments further demonstrate the potential of this adsorbent for industrial applications. The zirconium-based adsorbents investigated in this study display excellent performance and hold promising prospects for industrialization.
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