Thin-film UV–vis spectroscopy as a chemically-sensitive monitoring tool for copper etching bath

2022

Front. Chem.

Aiming at the problems of low accuracy and large prediction errors caused by the serious overlap of multi-metal spectral signals in zinc smelting industrial wastewater, a characteristic interval modeling method is proposed. First, according to the absorption spectra of mixed solution, the characteristic intervals of copper and nickel are preliminarily screened by using different partition lengths. Second, take the smallest root mean squares error of cross validation and the largest correlation coefficient as the evaluation indicators, compare the full-spectral model and each local model, and select the optimal feature sub-intervals of copper and nickel. Last, the partial least squares method is used to model the combined wavelengths of the optimal sub-intervals to realize the simultaneous detection of copper and nickel. The linear determination ranges are 0.3–3.0 mg/L for copper and nickel. the correlation coefficients of copper and nickel are 0.9974 and 0.9966, respectively. The results show that the method reduces the complexity of the wavelength variable screening process, improves the accuracy of the model, and lays the foundation for the accurate analysis of polymetallic ions in zinc smelting industrial wastewater.

Section: Introductionmentioning

confidence: 99%

A Characteristic Interval Modeling Method for Simultaneous Detection of Multiple Metal Ions

2022

Front. Chem.

“…In recent years, the commonly used methods for on-line detection of metal ions include potentiometric titration (Attimarad 2012), polarography (Duran Meras et al, 2002), inductively coupled plasma mass spectrometry (Rastogi et al, 2015), ultraviolet visible spectroscopy (Lambert et al, 2017) and laser-induced breakdown spectroscopy (Fedenko et al, 2017). As a conventional quantitative analysis method, ultraviolet visible spectroscopy is widely used in the field of analysis and detection due to its advantages of simplicity, accuracy, rapidity, multifunction and low cost (Lepane et al, 2015;Lee and Oh, 2017).…”

Section: Introductionmentioning

confidence: 99%

A Nonlinear Integrated Modeling Method of Extended Kalman Filter Based on Adaboost Algorithm

2021

Front. Chem.

In the zinc hydrometallurgical purification process, the concentration ratio of zinc ion to trace nickel ion is as high as 105, so that the nickel spectral signal is completely covered by high concentration zinc signal, resulting in low sensitivity and nonlinear characteristics of nickel spectral signal. Aiming at the problem that it is difficult to detect nickel in zinc sulfate solution, this paper proposes a nonlinear integrated modeling method of extended Kalman filter based on Adaboost algorithm. First, a non-linear nickel model is established based on nickel standard solution. Second, an extended Kalman filter wavelength optimization method based on correlation coefficient is proposed to select wavelength variables with high signal sensitivity, large amount of information and strong nonlinear correlation. Finally, a nonlinear integrated modeling method based on Adaboost algorithm is proposed, which uses extended Kalman filter as a basic submodel, and realizes the stable detection of trace nickel through the weighted combination of multiple basic models. The results show that the average relative error of this method for detecting nickel is 4.56%, which achieves accurate detection of trace nickel in zinc sulfate solution.

“…Ultraviolet-visible spectroscopy is a fast analytical method, which has developed rapidly in recent years [1][2][3][4][5]. Because of its advantages of many kinds of measurable substances, wide range of measurable concentrations, fast detection speed, good reproducibility, simple instrument and low analysis cost, it is widely used in qualitative and quantitative analysis of substances [6][7][8][9][10]. At present, largescale and precise ultraviolet-visible spectrometers have been widely used in the fields of industry, agriculture, medicine and biology, and are the main analytical equipment in analytical and testing laboratories [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Development of a Miniature Spectrometer Based on Ultraviolet-Visible Spectroscopy for Quantitative Analysis of Copper and Cobalt

2020

IEEE Access

Considering the requirements of miniaturization, integration, digitization and high precision of online detection instrument, a miniature spectrometer based on ultraviolet-visible spectroscopy is developed for the on-line detection of copper and cobalt in the purification process of zinc hydrometallurgy. Firstly, the serial port protocol of spectrometer is developed to realize remote online acquisition of spectral signal. Then, a wavelet threshold denoising method is proposed to eliminate the noise interference caused by the spectrometer and the circuit system. Next, based on the invariance of the dual-wavelength light intensity ratio in the spectral detection, an error correction algorithm is proposed to dynamically eliminate the systematic measurement error caused by light source fluctuations. Finally, the partial least squares method is used to detect the concentration of copper and cobalt, and the detection performance of online miniature spectrometer is compared with that of dual-beam spectrometer. The results show that the developed online analysis instrument can detect polymetal ions in less than 5 min, the average relative error is less than 10%, and the detection accuracy is higher than 94.74%, which is suitable for the online acquisition and analysis of polymetal ions in high concentration zinc solution.