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您的检索式：作者名="Ligao Yang"
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| 1 | Insights into Ti doping for stabilizing the Na_(2/3)Fe_(1/3)Mn_(2/3)O_(2)cathode in sodium ion battery显示文摘Iron-and manganese-based layered metal oxides,as cathodes for sodium ion batteries,have received widespread attention because of the low cost and high specific capacity.However,the Jahn-teller effect of Mn^(3+)ions and the resulted unstable structure usually lead to continuously capacity decay.Herein,Titanium(Ti)has been successfully doped into Na_(2/3)Fe_(2/3)Mn_(2/3)O_(2)to suppress the Jahn-Teller distortion and improve both cycling and rate performance of sodium ion batteries.In situ high-energy synchrotron X-ray diffraction study shows that Ti-doped compound(Na_(2/3)Fe_(1/3)Mn_(0.57)Ti_(0.1)O_(2))can maintain the single P2 phase without any phase transition during the whole charging/discharging process.Various electrochemical characterizations are also applied to explore the better kinetics of sodium ions transfer in the Na_(2/3)Fe_(1/3)Mn_(0.5)7 Ti_(0.1)O_(2).This work provides a comprehensive insight into the Ti-doping effects on the performance from both structural and electro kinetic perspectives. | Tingting Yang Yalan Huang Jian Zhang He Zhu Jincan Ren Tianyi Li Leighanne C.Gallington Si Lan Ligao Yang Qi Liu | 2022 | Journal of Energy Chemistry2022，31，10： | 1 |
| 2 | An Optimized Chinese Filtering Model Using Value Scale Extended Text Vector显示文摘With the development of Internet technology,the explosive growth of Internet information presentation has led to difficulty in filtering effective information.Finding a model with high accuracy for text classification has become a critical problem to be solved by text filtering,especially for Chinese texts.This paper selected the manually calibrated Douban movie website comment data for research.First,a text filtering model based on the BP neural network has been built;Second,based on the Term Frequency-Inverse Document Frequency(TF-IDF)vector space model and the doc2vec method,the text word frequency vector and the text semantic vector were obtained respectively,and the text word frequency vector was linearly reduced by the Principal Component Analysis(PCA)method.Third,the text word frequency vector after dimensionality reduction and the text semantic vector were combined,add the text value degree,and the text synthesis vector was constructed.Experiments show that the model combined with text word frequency vector degree after dimensionality reduction,text semantic vector,and text value has reached the highest accuracy of 84.67%. | Siyu Lu Ligao Cai Zhixin Liu Shan Liu Bo Yang Lirong Yin Mingzhe Liu Wenfeng Zheng | 2023 | Computer Systems Science & Engineering2023，47，11： | 0 |
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