Surface-enhanced IR absorption spectroscopy in attenuated-total reflection（ATR-SEIRAS） configuration was extended for the first time to a cadmium electrode with the adsorption of pyridine as the model system. The SE...Surface-enhanced IR absorption spectroscopy in attenuated-total reflection（ATR-SEIRAS） configuration was extended for the first time to a cadmium electrode with the adsorption of pyridine as the model system. The SEIRAS active Cd film electrode was prepared by electrodeposition of Cd mulitlayers onto a underlying Au nanofilm on Si in 0.01 mol/L CdSO 4 +0.1 mol/L KClO 4. The morphology of the as-prepared Cd film exhibits an island structure. In the potential range of -1.2 to -0.8 V（vs. SCE）, only in-plane vibrations belonging to the A1 symmetry were detected whereas those to the B1 symmetry virtually were not, suggesting that pyridine coordinates vertically or at a little angle to the Cd electrode surface via its nitrogen end without edge-tilted rotation of its ring plane. The Py adsorption configuration is closed to that found on a Au electrode, but different from that on a Ni or Pt electrode, which may be assigned to different structures of valence electron shells for the substrate metals.展开更多
目的在近红外光谱(near infrared spectroscopy,NIR)与表面增强拉曼光谱(surface-enhanced Raman spectroscopy,SERS)特征层数据融合的基础上构建偏最小二乘回归(partial least squares regression,PLSR)模型实现花生油中黄曲霉毒素B_(1...目的在近红外光谱(near infrared spectroscopy,NIR)与表面增强拉曼光谱(surface-enhanced Raman spectroscopy,SERS)特征层数据融合的基础上构建偏最小二乘回归(partial least squares regression,PLSR)模型实现花生油中黄曲霉毒素B_(1)(aflatoxin B_(1),AFB_(1))含量的快速检测。方法首先,分别采集待测样本的NIR与SERS光谱。其次,将采集的NIR与SERS光谱分别进行光谱预处理。然后,采用基于希尔伯特-施密特独立准则的变量空间迭代优化算法(Hilbert-Schmidt independence criterion based variable space iterative optimization,HSIC-VSIO)分别筛选NIR与SERS光谱的特征变量。最后,将筛选的特征变量进行融合并构建PLSR模型用于定量检测花生油中AFB_(1)含量。结果与NIR光谱数据、SERS光谱数据以及NIR与SERS光谱直接融合数据构建的PLSR模型相比,NIR与SERS光谱特征层融合数据构建的PLSR模型具有最佳的预测性能:校正集均方根误差(root mean squared error of calibration set,RMSEC)为0.1569,校正集决定系数(coefficient of determination of calibration set,R_(c)^(2))为0.9908,预测集均方根误差(root mean squared error of prediction set,RMSEP)为0.1827,预测集决定系数(coefficient of determination of prediction set,R_(c)^(2))为0.9854,性能偏差比(ratio of performance to deviation,RPD)为8.2761。将本方法与标准方法分别检测真实含有AFB_(1)的花生油样本,结果表明两者的检测性能无显著性差异(P=0.84>0.05)。结论本方法可实现花生油中AFB_(1)含量的快速、高精度定量检测,也验证了NIR与SERS光谱融合的可行性与有效性。展开更多
文摘Surface-enhanced IR absorption spectroscopy in attenuated-total reflection（ATR-SEIRAS） configuration was extended for the first time to a cadmium electrode with the adsorption of pyridine as the model system. The SEIRAS active Cd film electrode was prepared by electrodeposition of Cd mulitlayers onto a underlying Au nanofilm on Si in 0.01 mol/L CdSO 4 +0.1 mol/L KClO 4. The morphology of the as-prepared Cd film exhibits an island structure. In the potential range of -1.2 to -0.8 V（vs. SCE）, only in-plane vibrations belonging to the A1 symmetry were detected whereas those to the B1 symmetry virtually were not, suggesting that pyridine coordinates vertically or at a little angle to the Cd electrode surface via its nitrogen end without edge-tilted rotation of its ring plane. The Py adsorption configuration is closed to that found on a Au electrode, but different from that on a Ni or Pt electrode, which may be assigned to different structures of valence electron shells for the substrate metals.
文摘目的在近红外光谱(near infrared spectroscopy,NIR)与表面增强拉曼光谱(surface-enhanced Raman spectroscopy,SERS)特征层数据融合的基础上构建偏最小二乘回归(partial least squares regression,PLSR)模型实现花生油中黄曲霉毒素B_(1)(aflatoxin B_(1),AFB_(1))含量的快速检测。方法首先,分别采集待测样本的NIR与SERS光谱。其次,将采集的NIR与SERS光谱分别进行光谱预处理。然后,采用基于希尔伯特-施密特独立准则的变量空间迭代优化算法(Hilbert-Schmidt independence criterion based variable space iterative optimization,HSIC-VSIO)分别筛选NIR与SERS光谱的特征变量。最后,将筛选的特征变量进行融合并构建PLSR模型用于定量检测花生油中AFB_(1)含量。结果与NIR光谱数据、SERS光谱数据以及NIR与SERS光谱直接融合数据构建的PLSR模型相比,NIR与SERS光谱特征层融合数据构建的PLSR模型具有最佳的预测性能:校正集均方根误差(root mean squared error of calibration set,RMSEC)为0.1569,校正集决定系数(coefficient of determination of calibration set,R_(c)^(2))为0.9908,预测集均方根误差(root mean squared error of prediction set,RMSEP)为0.1827,预测集决定系数(coefficient of determination of prediction set,R_(c)^(2))为0.9854,性能偏差比(ratio of performance to deviation,RPD)为8.2761。将本方法与标准方法分别检测真实含有AFB_(1)的花生油样本,结果表明两者的检测性能无显著性差异(P=0.84>0.05)。结论本方法可实现花生油中AFB_(1)含量的快速、高精度定量检测,也验证了NIR与SERS光谱融合的可行性与有效性。
