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Carbon Skeleton In Situ Co-precipitation Preparation Of Lifepo <sub> 4 </ Sub> Cathode Material

Posted on:2008-01-16Degree:MasterType:Thesis
Country:ChinaCandidate:M PengFull Text:PDF
GTID:2192360215985010Subject:Non-ferrous metallurgy
Abstract/Summary:PDF Full Text Request
Lithium-ion battery is the third generation following by nickel-cadminm battery and metal-hydrogen nickel battery. Secondary lithium batteries have been the primary power supply components for various portable electronic devices, such as cell phones and notebook computers. However, as the weight and volume of the portable devices continuously decrease, the search for smaller, lighter, and higher power density power sources has never stopped.The precursor was prepared by aqueous co-precipitation method. The LiFePO4/C was synthesized by thermal-treated. Based on the experimental study, the influence of technological conditions on the chemical composition and the powder characteristics, such as structure, morphology and electrochemical performance was systematically investigated by modern analytical methods of chemical analysis, X-ray diffraction (XRD), thermogravimetric (TG) and differential thermal analyzer (DTA), scanning electron microscope (SEM), constant-current charge-discharge test and so on.The electrochemical tests showed that the material obtained has a steady charge voltage on 3.5V and 3.4V discharge flat. In this paper, we also studied several carbon sources, activated acetylene black is suitable to prepare LiFePO4/C with high electronic conductivity and good rate capability. The resultant product can delivered capacity as high as 157mAh/g at current density 0.1C. The influence of metal sources,carbon content,rotate speed,temperature,concentration and time on the structure, morphology and electrochemical performance of the final products was examined.In the last, The basic procedures of designing BP neural network utilizing Matlab neural network toolbox were introduced. BP model was applied by the authors in the field of electrochemistry, and a neural network forecasting model for electrochemistry based on the resultant, the computation results showed that the BP model had good quality on forecasting precision and generalization ability. Besides, we studied the relationship of specific capacity and carbon content,rotate speed,temperature,concentration,time.
Keywords/Search Tags:lithium-ion battery, cathode, LiFePO4, co-precipitation, BP neural network
PDF Full Text Request
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