摘要
主要采用30%TBP-20%NX混合萃取体系对青海某盐湖卤水提锂过程涉及的萃取、洗涤、反萃等过程进行了详细研究。萃取过程:运用正交试验法对萃取相比、铁锂摩尔比及水相酸度进行了显著性分析,发现相比对30%TBP-20%NX混合萃取体系影响显著,水相pH值影响不明显;在O/A=1.5、n(Fe^(3+)/Li^(+))=2和水相酸度0.05 mol/L的最佳条件下,Li^(+)、Mg^(2+)萃取率分别为89.19%和1.69%;采用饱和容量法测量30%TBP+20%NX混合萃取体系的单位负载锂量为2284 mg/L,所需分相时间为15 min。洗涤过程:在c(H^(+))=0.25 mol/L和O/A=20/1的最佳条件下,Li^(+)、Mg^(2+)的洗涤率分别为5.12%、89.46%。反萃过程:在c(H^(+))=3 mol/L和O/A=15/1的最佳条件下,Li^(+)、Mg^(2+)反萃率分别为80.08%、67.56%。TBP-NX混合萃取体系Li+负载量及反萃性能较好。
In this paper,the 30%TBP+20%NX mixed solvent extraction system was adopted to test the lithium extraction process of a salt lake brine from Qinghai.The extraction,scrubbing and stripping processes were described and analyzed in detail.Solvent extraction process:Significance analysis of the solvent extraction ratio(O/A),iron-lithium molar ratio n(Fe^(3+)/Li^(+)),and water phase acidity c(H+)by orthogonal test method shows that the ratio of O/A has a significant impact on this 30%TBP-20%NX mixed system,while the water phase pH is not significant impact parameter.Under the optimal conditions of O/A=1.5,n(Fe^(3+)/Li^(+))=2 and 0.05 mol/L water phase acidity,the solvent extraction rates of Li+and Mg2+are 89.19%and 1.69%,respectively.The saturation capacity method is used to measure the organic phase unit load capacity of lithium in 30%TBP+20%NX mixed system as 2284 mg/L,and the separation time of organic and water phase clarification is 15 min.Scrubbing process:Under the optimal conditions of c(H^(+))=0.25 mol/L and O/A=20/1,the scrubbing rates of Li+and Mg^(2+)are 5.12%and 89.46%,respectively.Stripping process:Under the optimal conditions of c(H^(+))=3 mol/L and O/A=15/1,the stripping rates of Li^(+)and Mg^(2+)are 80.08%and 67.56%,respectively.In summary,the TBP-NX mixed solvent extraction system has good Li+loading and stripping performance.
作者
蒋应平
薛宇飞
邓超群
JIANG Yingping;XUE Yufei;DENG Chaoqun(BGRIMM Technology Group,Beijing 100160,China;Hatch Project Consulting (Shanghai) Co.,Ltd.,Shanghai 200031,China)
出处
《有色金属工程》
CAS
北大核心
2021年第11期41-47,共7页
Nonferrous Metals Engineering
基金
国家重点研发计划项目(2018YFC0604803)。
