The high pKa-guided defect engineering: improving fluoride removal in actual scenarios by benzimidazole modulated metal-organic frameworks

IF 12.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Water Research Pub Date : 2025-03-16 DOI:10.1016/j.watres.2025.123510
Ziyi Zhao , Yanan Mi , Shili Wang , Xuedong Du , Qingrui Zhang
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Abstract

We firstly present a novel strategy for enhancing fluoride removal from contaminated water using defect-engineered UiO-66 (Zr-MOFs), emphasizing the crucial role of pKa in modulator selection. By utilizing modulators with varying pKa values-specifically benzimidazole (BI), benzoic acid (BA), and acetic acid (AA)-we synthesized defect-rich Act-UiO-66-M(X). The higher pKa of BI facilitated greater defect formation, resulting in significantly improved adsorption capacity and faster diffusion rates. Act-UiO-66-BI(8), modulated with BI, showed a higher intensity peak at g = 2.003 in ESR analysis, indicating more oxygen vacancies. Its fluoride adsorption capacity reached 93.59 mg F/g, nearly six times higher than commercial ZrO2, with rapid kinetics—evidenced by a kinetic rate constant (kint) of 2.64 mg/g·min0.5 and equilibrium achieved within 10 min. The kinetic performance was enhanced by 270% compared to raw Act-UiO-66. Furthermore, Act-UiO-66-BI(8) demonstrated high selectivity and stability in high-salinity environments, with a Kd coefficient consistently exceeding 17,900 mL/g. The study highlights that selecting modulators based on pKa enhances defect formation, improving active site exposure and pore diffusion, as confirmed by DFT calculations and XPS analysis. The ability of Act-UiO-66-BI(8) to treat up to 1160 kg of wastewater per kg of adsorbent highlights its potential for large-scale water purification, showcasing a promising approach for developing high-performance MOF materials.

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高pka引导缺陷工程:苯并咪唑调制金属-有机框架在实际情况下改善除氟效果
我们首先提出了一种利用缺陷工程的uuo -66 (Zr-MOFs)增强污染水中氟化物去除的新策略,强调了pKa在调节剂选择中的关键作用。通过使用不同pKa值的调节剂——特别是苯并咪唑(BI)、苯甲酸(BA)和乙酸(AA)——我们合成了富含缺陷的Act-UiO-66-M(X)。BI的pKa越高,形成的缺陷越多,吸附能力显著提高,扩散速率加快。经BI调制的Act-UiO-66-BI(8)在ESR分析中在g = 2.003处显示出更高的强度峰,表明氧空位较多。吸附量达到93.59 mg F/g,是工业ZrO2吸附量的近6倍,动力学速率常数(kint)为2.64 mg/g·min0.5, 10分钟即可达到吸附平衡。与原始Act-UiO-66相比,其动力学性能提高了270%。此外,act - uiu -66- bi(8)在高盐度环境中表现出高选择性和稳定性,Kd系数始终超过17,900 mL/g。DFT计算和XPS分析证实,基于pKa选择调制剂可以增强缺陷形成,改善活性位点暴露和孔隙扩散。Act-UiO-66-BI(8)每公斤吸附剂处理高达1160公斤废水的能力突出了其大规模水净化的潜力,展示了开发高性能MOF材料的有前途的方法。
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来源期刊
Water Research
Water Research 环境科学-工程:环境
CiteScore
20.80
自引率
9.40%
发文量
1307
审稿时长
38 days
期刊介绍: Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.
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