A computational thermodynamics model for the oxygen bottom-blown copper smelting process(Shuikoushan,SKS process)was established,based on the SKS smelting characteristics and theory of Gibbs free energy minimization.T...A computational thermodynamics model for the oxygen bottom-blown copper smelting process(Shuikoushan,SKS process)was established,based on the SKS smelting characteristics and theory of Gibbs free energy minimization.The calculated results of the model show that,under the given stable production condition,the contents of Cu,Fe and S in matte are71.08%,7.15%and17.51%,and the contents of Fe,SiO2and Cu in slag are42.17%,25.05%and3.16%.The calculated fractional distributions of minor elements among gas,slag and matte phases are As82.69%,11.22%,6.09%,Sb16.57%,70.63%,12.80%,Bi68.93%,11.30%,19.77%,Pb19.70%,24.75%,55.55%and Zn17.94%,64.28%,17.79%,respectively.The calculated results of the multiphase equilibrium model agree well with the actual industrial production data,indicating that the credibility of the model is validated.Therefore,the model could be used to monitor and optimize the industrial operations of SKS process.展开更多
The precise measurement of Al, Mg, Ca, and Zn composition in copper slag is crucial for effective process control of copper pyrometallurgy. In this study, a remote laser-induced breakdown spectroscopy(LIBS) system was...The precise measurement of Al, Mg, Ca, and Zn composition in copper slag is crucial for effective process control of copper pyrometallurgy. In this study, a remote laser-induced breakdown spectroscopy(LIBS) system was utilized for the spectral analysis of copper slag samples at a distance of 2.5 m. The composition of copper slag was then analyzed using both the calibration curve(CC) method and the partial least squares regression(PLSR) analysis method based on the characteristic spectral intensity ratio. The performance of the two analysis methods was gauged through the determination coefficient(R^(2)), average relative error(ARE), root mean square error of calibration(RMSEC), and root mean square error of prediction(RMSEP). The results demonstrate that the PLSR method significantly improved both R^(2) for the calibration and test sets while reducing ARE, RMSEC, and RMSEP by 50% compared to the CC method. The results suggest that the combination of LIBS and PLSR is a viable approach for effectively detecting the elemental concentration in copper slag and holds potential for online detection of the elemental composition of high-temperature molten copper slag.展开更多
基金Project(51620105013)supported by the National Natural Science Foundation of China
文摘A computational thermodynamics model for the oxygen bottom-blown copper smelting process(Shuikoushan,SKS process)was established,based on the SKS smelting characteristics and theory of Gibbs free energy minimization.The calculated results of the model show that,under the given stable production condition,the contents of Cu,Fe and S in matte are71.08%,7.15%and17.51%,and the contents of Fe,SiO2and Cu in slag are42.17%,25.05%and3.16%.The calculated fractional distributions of minor elements among gas,slag and matte phases are As82.69%,11.22%,6.09%,Sb16.57%,70.63%,12.80%,Bi68.93%,11.30%,19.77%,Pb19.70%,24.75%,55.55%and Zn17.94%,64.28%,17.79%,respectively.The calculated results of the multiphase equilibrium model agree well with the actual industrial production data,indicating that the credibility of the model is validated.Therefore,the model could be used to monitor and optimize the industrial operations of SKS process.
基金supported by funding for research activities of postdoctoral researchers in Anhui Provincespecial funds for developing Anhui Province’s industrial “three highs” and high-tech industries。
文摘The precise measurement of Al, Mg, Ca, and Zn composition in copper slag is crucial for effective process control of copper pyrometallurgy. In this study, a remote laser-induced breakdown spectroscopy(LIBS) system was utilized for the spectral analysis of copper slag samples at a distance of 2.5 m. The composition of copper slag was then analyzed using both the calibration curve(CC) method and the partial least squares regression(PLSR) analysis method based on the characteristic spectral intensity ratio. The performance of the two analysis methods was gauged through the determination coefficient(R^(2)), average relative error(ARE), root mean square error of calibration(RMSEC), and root mean square error of prediction(RMSEP). The results demonstrate that the PLSR method significantly improved both R^(2) for the calibration and test sets while reducing ARE, RMSEC, and RMSEP by 50% compared to the CC method. The results suggest that the combination of LIBS and PLSR is a viable approach for effectively detecting the elemental concentration in copper slag and holds potential for online detection of the elemental composition of high-temperature molten copper slag.
