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本文结合中国地质调查项目,用本实验室编制的自学习人工神经网络解析金和铂的流动注射-化学发光法动力学曲线,提出了一种不需要分离、在线、灵敏地同时测定痕量金和铂的方法。以Luminol-H2O2作化学发光试剂,用阳离子交换树脂在线吸附大多数金属离子的干扰,用EDTA作掩蔽剂消除残余的干扰元素。方法可以校正部分实验误差,对金和铂的模拟混合样品的浓度预测,分析结果的相对误差≤20％。
In this paper, we use the self-learning artificial neural network compiled by our laboratory to analyze the kinetic curves of gold and platinum by flow injection and chemiluminescence, and propose a new method that can measure trace gold And platinum method. Luminol-H2O2 was used as a chemiluminescence reagent to online adsorb most of the interference of metal ions with cation exchange resin, and EDTA was used as a masking agent to eliminate the remaining interfering elements. The method can correct some experimental errors. The concentration of simulated mixed samples of gold and platinum is predicted. The relative error of analysis results is less than or equal to 20%.