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盐湖卤水中硼酸盐化学形态及Raman光谱定量分析

Research on the Chemical Species of Borates in Salt Lake Brine and Its Quantitative Analysis by Raman Spectroscopy
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摘要 我国青藏盐湖以富含硼锂而著称,卤水中硼化学赋存状态随湖水化学类型的不同而发生变化,其中以硫酸盐型盐湖卤水中硼酸盐的存在形式变化最为复杂,卤水蒸发过程一般不以固体盐形式结晶析出,而是以多硼物种形式富集于氯化镁饱和老卤中,表现出严重的过饱和性,对后续锂盐和镁盐的分离提取影响较大。开展盐湖卤水体系中硼酸盐化学形态、分布规律及离子间作用机制等溶液化学研究对盐湖资源高效开发具有重要的意义。相比常规拉曼光谱技术,拉曼积分球基于拉曼散射原理可极大地提高激发光的使用效率和拉曼散射信号,对硼酸盐溶液结构检测具有拉曼响应信号强、检出限低、信噪比高等优点,为盐卤复杂体系硼酸盐化学形态的定量分析奠定了基础。利用拉曼积分球开展了盐湖卤水硼酸盐化学形态研究,阐述了卤水蒸发过程多硼酸根离子的变化规律;同时借助响应曲面法进行实验设计与优化,建立了共存盐类干扰回归模型用于盐湖卤水中单硼物种B(OH)_(3)的准确测定。结果表明,盐湖卤水浓缩过程中硼不断聚合生成多聚度硼酸根离子如B3O3(OH)-4和B_(6)O_(7)(OH)2-7等,硼的化学形态变化规律与碱土金属如MgCl_(2)-MgO-2B_(2)O_(3)-H_(2)O体系中硼物种变化一致,但与碱金属溶液体系物种变化差别较大。回归模型对卤水中正硼酸B(OH)_(3)定量分析的相对误差小于5%,准确度较高;阐明了蒸发浓缩过程中B(OH)_(3)物种分布的变化规律,从定量视角初步阐述了卤水富集过程硼酸根离子间的聚合作用关系,可为后续开展盐卤体系多硼物种分布及作用机制研究提供新思路、新方法。 Qinghai-Tibet salt lakes are famous for enriching boron and lithium resources.Nevertheless,the chemical species of borate in the brine varies with the chemical type of salt lake.Among them,the existing borate forms in sulfate-type salt lake brine are the most complicated.Generally,the borates do not crystallize out from the brine during the whole evaporation process of brine but accumulate in the bischofite-saturated brine in different kinds of boron species,which are supersaturated with magnesium borates.This phenomenon may significantly impact the subsequent separation and extraction of lithium and magnesium salts.Therefore,the deep research on the chemical forms,species distribution,and their interactions in the salt lake brine is of great significance for the highly efficient development of salt lake resources.Compared with the classical Raman spectroscopy,the simplified Raman integrating sphere,designed based on the Raman scattering principle,can improve the exciting light's efficiency and the Raman scattering signal.It is characteristic of a strong Raman scattering signal,low detection limit,and high signal-to-noise ratio for the characterization of the borate structures,which favors the quantitative analysis of the chemical forms of the borate in the complicated brine system.Based on the above,this study aimed to investigate the chemical forms of borate in salt lake brine using the Raman integrating spheres.It also elucidated the changes of polyborate ions during the brine evaporation process.Secondly,the response surface method was used to explore the effects of the coexisting salts on the determination of B(OH)_(3)in salt lake brine.The results showed that borates in the salt lake brine could be polymerized to form poly borate ions such as B3O3(OH)-4 and B_(6)O_(7)(OH)2-7 during the brine evaporation process,which agreed well with the borate changes in the alkaline-earth metal solution system of MgCl_(2)-MgO-2B_(2)O_(3)-H_(2)O,but differed greatly with that changes in alkaline metal solutions.The relative error of the B(OH)_(3)determination in brine was less than 5%after being corrected by the response surface interference model.Therefore,the distribution of B(OH)_(3)in the brine was also studied during the evaporation process,which helped explain the polymerization mechanism among borate ions in brine from a quantitative perspective.In sum,this research could provide new ideas and methods for further study of borate speciation and their interaction mechanism in complicated brine systems.
作者 彭姣玉 杨克利 董亚萍 冯海涛 张波 李武 PENG Jiao-yu;YANG Ke-li;DONG Ya-ping;FENG Hai-tao;ZHANG Bo;LI Wu(Key Laboratory of Comprehensive and Highly Efficient Utilization of Salt Lake Resources,Qinghai Institute of Salt Lakes,Chinese Academy of Sciences,Xining 810008,China;Qinghai Engineering and Technology Research Center of Comprehensive Utilization of Salt Lake Resources,Xining 810008,China;Key Laboratory of Salt Lake Resources Chemistry of Qinghai Province,Xining 810008,China)
出处 《光谱学与光谱分析》 SCIE EI CAS CSCD 北大核心 2024年第9期2514-2522,共9页 Spectroscopy and Spectral Analysis
基金 中国科学院稳定支持基础研究计划领域青年团队计划项目(YSBR-039) 青海省应用基础研究计划项目(2020-ZJ-730) 国家重点研发计划项目(2017YFC0602805) 中国科学院青年创新促进会(E010GC1501)资助。
关键词 卤水 硼酸盐:响应曲面 拉曼光谱 定量分析 Salt lake brine Borates Response surface method Raman spectra Quantitative analysis
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