Mineral processing operation is a critical step in any recycling process to realize liberation, separation and concentration of the target parts. Developing effective recycling methods to recover all the valuable parts from spent lithium-ion batteries is in great necessity. The aim of this study is to carefully undertake chemical and process mineralogical characterizations of spent lithium-ion batteries by coupling several analytical techniques to provide basic information for the researches on effective mechanical crushing and separation methods in recycling process. The results show that the grade of Co, Cu and Al is fairly high in spent lithium ion batteries and up to 17.62 wt.%, 7.17 wt.% and 21.60 wt.%. Spent lithium-ion batteries have good selective crushing property, the crushed products could be divided into three parts, they are Al-enriched fraction (+2 mm), Cu and Al-enriched fraction (?2 + 0.25 mm) and Co and graphite-enriched fraction (?0.25 mm). The mineral phase and chemical state analysis reveal the electrode materials recovered from ?0.25 mm size fraction keep the original crystal forms and chemical states in lithium-ion batteries, but the surface of the powders has been coated by a certain kind of hydrocarbon. Based on these results a flowsheet to recycle spent LiBs is proposed. 相似文献
In recent 2 years, the incidence of influenza showed a slight upward trend in Guangxi; therefore, some joint actions should be done to help preventing and controlling this disease. The factors analysis of affecting influenza and early prediction of influenza incidence may help policy-making so as to take effective measures to prevent and control influenza. In this study, we used the cross correlation function (CCF) to analyze the effect of climate indicators on influenza incidence, ARIMA and ARIMAX (autoregressive integrated moving average model with exogenous input variables) model methods to do predictive analysis of influenza incidence. The results of CCF analysis showed that climate indicators (PM2.5, PM10, SO2, CO, NO2, O3, average temperature, maximum temperature, minimum temperature, average relative humidity, and sunshine duration) had significant effects on the incidence of influenza. People need to take good precautions in the days of severe air pollution and keep warm in cold weather to prevent influenza. We found that the ARIMAX (1,0,1)(0,0,1)12 with NO2 model has good predictive performance, which can be used to predict the influenza incidence in Guangxi, and the predicted incidence may be useful in developing early warning systems and providing important evidence for influenza control policy-making and public health intervention.
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