A Quantum Dot Fluorescence Sensor System Design for Hg²âº Trace Detection.

The detection of Hg²âº ions usually requires large laboratory equipment, which encounters difficulties for rapid field test in most applications. In this paper, we design a reflective sensor for trace Hg²âº analysis based on the fluorescent quenching of Quantum dots, which contains two major modules, i. e. the fluorescent sensing module and the signal processing module. The fluorescence sensing module is composed of a laser source, a light collimated system and a photo-detector, which enables the realization of the fluorescence excitation as well as its detection. The signal processing module realized the further amplification of the detected signal and hereafter the filtering of noises. Furthermore, the Hg²âº concentration will displayed on the QT interface using a Linux embedded system. The sensor system is low cost and small, which makes it available for rapid field test or portable applications. Experimental results show that the sensor has a good linear relationship for the Hg²âº concentration range from 15.0 x 10⁻9 to 1.8 x 10⁻6 mol · L⁻¹. The regression equation is V0/V = 1.309 13 + 3.37c, where c is Hg²âº concentration, and V0 is the voltage value for the blank case. In our work, the linearity is determined as 0. 989 26. The experiments exhibit that Ca²âº, Mn²âº and Pb²âº ions have small influence on the Hg²âº detection, and the interfere of other common ions can be neglected, which indicates a good selectivity of the sensor. Finally, it shows that our sensor has a rapid response time of 35 s and a good repeatability, thus it is potential for field test of trace Hg²âº.

[Quantitative detection of ethyl paraoxon based on SERS and PCA-SLR].

In the present paper, the surface-enhanced Raman spectroscopy (SERS) was used to build the model for the quantitative detection of ethyl paraoxon by the principal component analysis and segmented linear regression (PCA-SLR). Firstly, SERS in 820-1630 cm(-1) of ethyl paraoxon solution were measured and the spectra in 820-1630 cm(-1)(complete range) and 845-875 cm(-1) (characteristic range) of ethyl paraoxon solution were preprocessed by standard normal transformation (SNV), multiplicative scatter correction (MSC), the absolute values of first derivative and the second derivative respectively. Additionally, the number of dimensions of the spectra was reduced by PCA. Finally, the models were established by SLR It was found that the model developed with MSC preprocessed spectroscopy of characteristic range performed best (RMSEP: 0.33) by comparing the predictive accuracy of the different models. The result could meet with the needs in the quantitative detection of ethyl paraoxon.