Highly efficient and selective removal of 90Sr by the carboxylated COFs (Tp-DTA) from radionuclides-contaminated groundwater

SEPARATION AND PURIFICATION TECHNOLOGY(2024)

引用 0|浏览3
暂无评分
摘要
In this study, a carboxyl-functionalized covalent organic framework (COF) rich in nitrogen (N) and oxygen (O) functional groups was prepared and characterized, which provided a new opportunity for the efficient and rapid treatment of radioactive contamination in nuclear wastewater. The synthesis of the COF (Tp-DTA) was constructed using 1,3,5-triformylphloroglucinol (TFP) and 2,5-diaminoterephthalic acid (DTA), providing a large specific surface area, mesoporous pore, and abundant coordination sites with high adsorption capacity and exceptional affinity for Sr2+. Batch adsorption experiments exhibited that Tp-DTA achieved a maximum adsorption capacity of 145.4 mg/g for Sr2+ in alkaline solutions, reaching adsorption equilibrium within 60 min. Tp-DTA exhibited rapid kinetics for Sr-90, with the amounts of Sr-90 removed more than 95% within 3 min. In the presence of coexisting ions (Na+, K+, Cs+, Mg2+, and Ca2+), Tp-DTA displayed excellent preferential selectivity for Sr2+ and high removal efficiency. Even in simulated groundwater containing multiple complex ions, Tp-DTA demonstrated a strong affinity for Sr2+ and showed practical applicability with a nearly 100% removal efficiency for Sr-90. XPS and FTIR characterizations confirmed that the adsorption mechanism of Sr2+ involved chelation exchange between the carboxyl groups of Tp-DTA and Sr2+ in the solution. Furthermore, the desorption efficiency of HCl (>0.01 mol/L) can reach 95% and five cyclic desorption-adsorption experiments demonstrated the reusability of Tp-DTA, endowing the carboxyl-functional COF with great potential in the treatment of Sr-90-contaminated radioactive wastewater and environmental remediation.
更多
查看译文
关键词
Sr-90,Selectivity,Covalent organic framework,Carboxyl functionalization,Radionuclides -contaminated groundwater
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要