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The Raman spectroscopy technique is a powerful and non-invasive technique for molecular fingerprint detection which has been widely used in many areas, such as food safety, drug safety, and environmental testing. But Raman signals can be easily corrupted by a fluorescent background, therefore we presented a baseline correction algorithm to suppress the fluorescent background in this paper. In this algorithm, the background of the Raman signal was suppressed by fitting a curve called a baseline using a cyclic approximation method. Instead of the traditional polynomial fitting, we used the B-spline as the fitting algorithm due to its advantages of low-order and smoothness, which can avoid under-fitting and over-fitting effectively. In addition, we also presented an automatic adaptive knot generation method to replace traditional uniform knots. This algorithm can obtain the desired performance for most Raman spectra with varying baselines without any user input or preprocessing step. In the simulation, three kinds of fluorescent background lines were introduced to test the effectiveness of the proposed method. We showed that two real Raman spectra (parathionmethyl and colza oil) can be detected and their baselines were also corrected by the proposed method.

An integrated optical system with high sensitivity and resolution was presented. This was made possible by coupling a probe to a monochromator directly, using an aspheric lens and an achromatic lens in the coupling path, using a dichroic filter with high transmission and a steep transitional zone as a beam splitter, increasing the throughput of the monochromator, and optimizing its structural parameters. This optical system has a high sensitivity; the tested spectrogram of a glass rod demonstrated that the signal-to-noise ratio measured by the integrated optical system was almost 4 times as high as an independent probe and monochromator. The optical system also has the advantages of high resolution (4  cm^-1 or 0.28 nm), low cost, and portable size. This work lays a good groundwork for the development of a high sensitivity, high resolution, and low cost integrated portable Raman spectrometer.

The technology that CuCl residue from Zn hydrometallurgy was dried by microwave heating was studied. The influence of the drying duration, drying temperature and material thickness on dehydration rate was investigated. The response surface methodology (RSM) technique was utilized to optimize the process conditions. The optimum conditions for drying CuCl residue have been identified to be an drying temperature of 80°C, drying duration of 11 min and material thickness of 16 mm. The optimum conditions resulted in an CuCl residue with moisture content of 4.97%, which could ensure remove chlorine of CuCl residue by microwave roasting.