Key Laboratory of Resources Conversion and Pollution Control of the State Ethnic Affairs Commission, College of Resources and Environment, South-Central Minzu University, Wuhan, 430074, China.
Key Laboratory for Synergistic Prevention of Water and Soil Environmental Pollution, Xinyang Normal University, Nanhu Road 237, Xinyang, 464000, China.
Chemosphere. 2023 Apr;319:138042. doi: 10.1016/j.chemosphere.2023.138042. Epub 2023 Feb 1.
Activated carbon fiber (ACF) has received increasing attention as an adsorbent due to its excellent surface properties. However, the adsorption mechanism of ACF for micropollutants, especially those in ionic forms, has not been sufficiently characterized to date. Therefore, the adsorption property of ACF was characterized using isotherm experiments and linear free energy relationship (LFER). For the experiments, adsorption affinities of thirty-five chemicals, i.e., pharmaceuticals and endocrine-disrupting chemicals, on ACF were estimated. Afterward, the adsorption affinities were used as dependent variables to build the LFER modeling. Finally, three isolated models for each chemical species, i.e., cations, anions, and neutrals, and a comprehensive model for the whole dataset were developed. The LFER results revealed that the models for anionic and neutral compounds have high predictabilities in R of 0.97 and 0.96, respectively, while that for cations has a slightly lower R of 0.72. In the comprehensive model including cationic, anionic, and neutral compounds, the accuracy of it is 0.81. From the developed LFER model based on the whole dataset, the adsorption mechanisms of ACF for the selected substances could be interpreted, in which the terms of hydrophobic interaction, hydrogen bonding basicity, and anionic Coulombic force of the compounds were identified as the predominant interactions with ACF.
活性炭纤维（ACF）因其优异的表面性能而受到越来越多的关注，作为一种吸附剂。然而，迄今为止，ACF 对痕量污染物（尤其是离子形式的污染物）的吸附机制尚未得到充分表征。因此，本文采用等温实验和线性自由能关系（LFER）对 ACF 的吸附性能进行了表征。在实验中，估算了 35 种化学物质（即药物和内分泌干扰化学物质）在 ACF 上的吸附亲和力。然后，将吸附亲和力作为因变量构建 LFER 模型。最后，为每种化学物质（即阳离子、阴离子和中性物质）分别开发了三个孤立模型，以及一个包含整个数据集的综合模型。LFER 结果表明，阴离子和中性化合物模型的预测能力很高，R 值分别为 0.97 和 0.96，而阳离子模型的 R 值略低，为 0.72。在包含阳离子、阴离子和中性化合物的综合模型中，其准确性为 0.81。从基于整个数据集开发的 LFER 模型中，可以解释 ACF 对所选物质的吸附机制，其中化合物的疏水相互作用、氢键碱性和阴离子库仑力等术语被确定为与 ACF 相互作用的主要因素。
