A5100435798- Advancements in Battery Materials
- Supercapacitor Materials and Fabrication
- Advanced Battery Materials and Technologies
- Extraction and Separation Processes
- Advanced Battery Technologies Research
- Spam and Phishing Detection
- Web Data Mining and Analysis
- Graphene research and applications
- Text and Document Classification Technologies
- Metal and Thin Film Mechanics
- Semiconductor materials and devices
- Advanced Sensor and Energy Harvesting Materials
Hunan University
2003-2019
Changsha University
2016
Recent progress, including storage mechanisms, synthetic methods, advanced strategies and electrochemical performance of Zn-based anodes in LIBs, is reviewed.
Porous ultrathin carbon nanobubbles formed nanofiber webs exhibit 94.1% capacitance retention after 35 000 cycles at a current density of 10 A g<sup>−1</sup>.
CuO/Cu ultra-uniformly dispersed in N-doped carbon nanofibers as anode materials for Li-ion batteries delivered excellent long-term cycling stability.
Abstract For applications in lithium‐ion batteries, carbon based materials possess high conductivity, whereas transition metal oxides usually show theoretical lithium ion storage capabilities. Therefore, engineering into three‐dimensional (3D) networks as anodes is expected to achieve long cycling life and excellent rate performance. Here, we report a facile environmental friendly method for the in‐situ synthesis of 3D coated bimetallic with porous network structure. The matrix originates...
Abstract In terms of Fe 3 O 4 ‐based anodes, enormous academic progress has been achieved over the past two decades; however, even with excellent half‐cell performance, relatively high lithiation potential and unsatisfactory initial coulombic efficiency (ICE) represent major barriers to their commercial application, at present. We propose partially phosphorized (P−Fe ) interior void spaces induced by phosphorization enhance Li + storage property anodes. P−Fe anodes offer a much higher...
A new algorithm of filtering junk-mail based on the Cognition-Learning Bayes is proposed in this paper, which can improve accuracy mail conspicuously by using method to assure that category's feature vector will always stand for it's real features. The experimental result shows gains obviously high precision and recall, a promising junk mail.