模式识别-优化迭代目标转换因子分析法同时测定硝基苯类化合物的研究

Pattern Recognition and Iterated Target Transformation Factor Analysis for Spectrophotometry to Determine Simultaneously the Five Multicomponents Nitrobenzens

摘要: 将聚类分析与优化迭代目标转换因子分析相结合用于紫外分光光度法同时测定硝基苯,2,4-二硝基氯苯,对硝基甲苯、间硝基甲苯、对硝基氯苯5种光谱重叠严重的化合物.对混合模拟水样的5种硝基苯类化物进行了初步研究,较成功地进行了定性定量分析、相对标准偏差小于5%,结果令人满意.并对优化波长集合进行了比较研究.

Abstract: The fivespectrum-overlapping multicomponents nitrobenzene, 2,4-dinitrochlorobenzene, p-nitrotoluene, m-nitrotoluene and p-chloronitrobenze, were determined by usingUV-spectrophotometry with the iterative target transformation factor analysis (ITTFA)andcluster-factor analysis. The method used was applied to the simultaneous qualitative andqualitative analysis for the five multicomponents in the mixture samples, which broughtabout satisfied results the relative standard deviation is within 5%.