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Surface complexation modeling of divalent metal cation adsorption on birnessite
Chemical Geology ( IF 3.6 ) Pub Date : 2020-09-01 , DOI: 10.1016/j.chemgeo.2020.119774
Ying Li , Xiaopeng Zhao , Jiangtong Wu , Xueyuan Gu

Abstract Birnessite is one of the most common manganese oxides in the environment and an important scavenger of trace metals. This study investigated the adsorption of seven divalent metal cations (Cd2+, Co2+, Cu2+, Mn2+, Ni2+, Pb2+ and Zn2+) on birnessite at different pH conditions, ionic strengths and initial concentrations. The adsorption data were used to formulate a self-consistent, two-site surface complexation model consisting of a triple-corner-sharing (TCS) complex at interlayer vacancies and a double-corner-sharing (DCS) complex at mineral edge sites. Unlike the other metals, Ni2+ had a relatively low adsorption capacity on birnessite, attributable to its tendency to incorporate within Mn vacancies (INC); hence a two-site model with INC and DCS complexes was used to describe Ni2+ adsorption on birnessite. The model well described all the adsorption data and was verified by data from the literature. In addition, a linear free energy relationship (LFER) was developed between the TCS binding constants and metal electronegativity and hydrous ionic radii, which can be used to estimate the binding constants of other trace metals. The proposed model contributes to a better understanding of the adsorption mechanisms of trace metals by manganese oxides. Furthermore, the data set can be included in geochemical assemblage models to predict the dissolution and mobility of metals in the environment.

中文翻译:

水钠锰矿吸附二价金属阳离子的表面络合模型

摘要 水钠锰矿是环境中最常见的锰氧化物之一,是微量金属的重要清除剂。本研究调查了七种二价金属阳离子(Cd2+、Co2+、Cu2+、Mn2+、Ni2+、Pb2+ 和 Zn2+)在不同 pH 条件、离子强度和初始浓度下对水钠锰矿的吸附。吸附数据用于制定自洽的双位点表面复合模型,该模型由层间空位处的三角共享 (TCS) 复合物和矿物边缘位置的双角共享 (DCS) 复合物组成。与其他金属不同,Ni2+ 对水钠锰矿的吸附能力相对较低,这是由于它倾向于并入 Mn 空位 (INC);因此,使用具有 INC 和 DCS 复合物的双位点模型来描述水钠锰矿上的 Ni2+ 吸附。该模型很好地描述了所有吸附数据,并通过文献数据进行了验证。此外,在 TCS 结合常数与金属电负性和含水离子半径之间建立了线性自由能关系 (LFER),可用于估计其他痕量金属的结合常数。所提出的模型有助于更好地理解锰氧化物对痕量金属的吸附机制。此外,该数据集可以包含在地球化学组合模型中,以预测金属在环境中的溶解和流动性。可用于估计其他痕量金属的结合常数。所提出的模型有助于更好地理解锰氧化物对痕量金属的吸附机制。此外,该数据集可以包含在地球化学组合模型中,以预测金属在环境中的溶解和流动性。可用于估计其他痕量金属的结合常数。所提出的模型有助于更好地理解锰氧化物对痕量金属的吸附机制。此外,该数据集可以包含在地球化学组合模型中,以预测金属在环境中的溶解和流动性。
更新日期:2020-09-01
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