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机构地区:[1]江南大学化学与材料工程学院,江苏无锡214122
出 处:《分析科学学报》2011年第1期72-76,共5页Journal of Analytical Science
摘 要:建立了碳纳米管修饰电极-人工神经网络同时检测一氯酚三种异构体的方法。在pH=7.0的磷酸盐缓冲溶液中,邻氯酚、间氯酚和对氯酚在碳纳米管修饰电极上均有一灵敏的不可逆氧化峰。采用微分脉冲溶出伏安法,在优化的实验条件下,邻氯酚、间氯酚和对氯酚的峰电位分别为624 mV、712 mV和632 mV,且浓度分别在2.07~103.66μmol/L、4.62~138.60μmol/L和2.71~108.48μmol/L范围内与峰电流呈良好的线性关系,检出限分别为0.9μmol/L、1.0μmol/L和0.8μmol/L。使用径向基人工神经网络(RBF-ANN)对一氯酚三种异构体混合物的伏安谱图进行分析,总预报误差为7.87%,而偏最小二乘法(PLS)总预报误差为15.57%。结果表明,所建立的方法可同时准确检测一氯酚的三种异构体。A method for simultaneous determination of the mixture of 2-,3-,4-chlorophenol(o-CP,m-CP and p-CP) by multi-walled carbon nanotubes(MWCNT) modified glassy carbon electrode with the aid of artificial neural network was proposed.In 0.1 mol/L phosphate buffer solution(PBS,pH=7.0),sensitive irreversible oxidation peaks for three target analytes were observed at the MWCNT modified glassy carbon electrode.Under the optimal conditions,the peak potentials of the differential pulse stripping voltammograms of o-CP,m-CP and p-CP were 624 mV,712 mV and 632 mV,respectively.The linear concentrations ranges of o-CP,m-CP and p-CP were 2.07~103.66 μmol/L,4.62~138.60 μmol/L and 2.71~108.48 μmol/L,with detection limits of 0.9 μmol/L,1.0 μmol/L and 0.8 μmol/L,respectively.Furthermore,radial basis function-artificial neural network(RBF-ANN) was used for simultaneous determination of those chlorophenols,and the relative prediction error(RPET) was 7.87%.In addition,the relative prediction error for both single component and total components of RBF-ANN were less than that of the partial least square(PLS) method.Therefore,the proposed method could be used to accurately simultaneous determination of o-CP,m-CP and p-CP.
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