摘要
建立了一种新的稳健回归方法，用于解析显色剂二溴对甲偶氮甲磺（DBM-MSA）与铅、铈配合物的重叠吸收光谱，不经分离分光光度法同时测定了铅和铈。铅和铈的配合物最大吸收波长分别为640和642nm，表观摩尔吸光系数分别为7．31×10^4和7．80×10^4L·mol^-1·cm^-1。铅和铈配合物分别在0～9μg／25mL和0～11μg／25mL范围内服从比耳定律。将人工神经网络BP算法（ANN-BP）应用于该体系的解析结果与新的稳健回归方法进行比较，表明两种方法用于铅和铈的同时测定，结果满意。
A chemometrics method of robust regression analysis （RRA） applied to spectrophotometric determination of components in a binary system is reported in this paper. Both Pb and Ce are reacted with dibromop-methylmethylsulfonazo （DBM MSA） to form color complexes, having similar absorption spectra which were seriously overlapped each other. The absorption peaks are located at 640 nm with molar absorptivity 7. 31 × 10^4L · mo1^-1 · cm^-1 for Pb and at 642 run with molar absorptivity 7. 80× 10^4L · mo1^-1 · cm^-1 for Ce, respectively. By using the RRA method, the absorption spectra were resolued and Pb and Ce determined simultaneously without separation. Beer＇s law was obeyed in the range of 0-9μg/25 mL for Ph and 0-11μg/25 mL for Ce. The method has been applied to the analysis of simulated samples and SRM of steels, the results were compared to those obtained by the Artificial Neural Network-BP method, showing that both the methods gave consistent results.
出处
《理化检验（化学分册）》
CAS
CSCD
北大核心
2006年第6期471-472,475,共3页
Physical Testing and Chemical Analysis(Part B:Chemical Analysis)
关键词
二溴对甲偶氮甲磺
稳健回归
人工神经网络
铅
铈
分光光度法
Dibromo-p-methyl-methylsulfonazo （ DBM-MSA ）
Robust regression
Artificial Neural Network
Pb
Ce
Spectrophometry
