摘要
准确测定冶炼烟尘中锗含量对于科学再利用具有重要指导意义。冶炼烟尘中含有大量的偏锡酸,包裹样品,盐酸、硝酸对此难以完全分解。考察多种溶样方式后发现,过氧化钠-盐酸-硝酸可完全分解样品,且通过控制温度,可避免锗的挥发损失。因此,选择Ge 259.253 nm为分析线,采用电感耦合等离子体原子发射光谱法(ICP-AES)对样品溶液进行测定,建立了冶炼烟尘中锗的测定方法。在优化的试验条件下,锗的质量浓度在0.50~15.00μg/mL范围内与发射强度呈良好线性关系,线性系数为r=0.99973,方法检出限为0.0013%(质量分数)。基体效应考察结果表明,冶炼烟尘中共存元素对锗的测定无显著影响。按照试验方法测定冶炼烟尘中锗,结果的相对标准偏差(RSD,n=11)为1.15%~2.82%,回收率为97.7%~100.8%。
Accurate determination of germanium(Ge)content in smelting dust is of great guiding significance for scientific recycling of smelting dust.Smelting dust contains a large amount of metastannic acid,which can encapsulate the sample,making it difficult to achieve complete decomposition using hydrochloric acid(HCl)and nitric acid(HNO3).A variety of sample dissolution methods were investigated,and complete sample decomposition was achieved by using sodium peroxide(Na2O2)-hydrochloric acid-nitric acid for sample digestion.Meanwhile,the temperature was controlled to avoid the volatilization loss of germanium.The analytical line of Ge at 259.253 nm was selected,and contents of sample solution were determined by inductively coupled plasma atomic emission spectrometry(ICP-AES).Overall,a method for determination of germanium in smelting dust was established.Under the optimized experimental conditions,mass concentration of germanium in the range of 0.50~15.00μg/mL showed a good linear relationship with the emission intensity,with a linear correlation coefficient(r)of 0.99973,and a detection limit of 0.0013%(mass fraction).The matrix effect was investigated,and results showed that the coexisting elements in smelting dust had no significant influence on the determination of germanium.When the proposed method was applied to the determination of germanium in smelting dust samples,the relative standard deviation(RSD,n=11)ranged from 1.15%to 2.82%,and the recovery rate was in the range of 97.7%to 100.8%.
作者
石如祥
陈建华
师云春
李云
SHI Ruxiang;CHEN Jianhua;SHI Yunchun;LI Yun(Tin Smelting Branch of Yunnan Tin Co.,Ltd.,Mengzi 661100,China)
出处
《铜业工程》
2026年第1期121-125,共5页
Copper Engineering
基金
云南省科技厅重大科技专项计划(202302AB080014)资助。
