Chrome Extension
WeChat Mini Program
Use on ChatGLM

Enhanced Lithium Storage Performance Derived from Fe2Ti1-xNixO5 (0 ≤ X ≤ 0.1) As a Fast Charging Anode

JOURNAL OF ELECTROANALYTICAL CHEMISTRY(2024)

Riphah Int Univ | Quaid i Azam Univ | Chinese Acad Sci | King Saud Univ | Natl Ctr Phys

Cited 1|Views15
Abstract
Using iron titanate (Fe2TiO5) as an electrode provides high theoretical capacity and good cycling stability because of its multiple redox couples and unique crystal structure. The synthesis of the material is successfully carried out using the conventional ceramic method. The effect of Ni2+ substitution on the overall electrochemical performance of Fe2Ti1-xNixO5 anode material is explored. When Ni2+ replaces Ti4+ in the pseudobrookite Fe2TiO5 unit cell, the volume increases smoothly with the amount of nickel and the electrical conductivity is enhanced because of the higher Ti3+/Ti4+ ratio. With pore sizes of around 10 nm and specific surface areas of 330.81 m2 g-1, Fe2Ti1-xNixO5 can provide large contact areas between the electrode and electrolyte and shorten the lithium-ion diffusion distance. With discharge capacities of 368.6 mAh g-1 at the 100th cycle, Fe2Ti1-xNixO5 negative electrode exhibits outstanding electrochemical performance. Furthermore, it demonstrates excellent rate stability, with a discharge capacity of 310.6 mAh g-1 at a current rate of 5000 mA g-1. Over another 45 cycles, a high discharge capacity of 367.1 mAh g-1 was maintained at a current density of 100 mA g-1 even after the rate performance test. The Ni2+ doping results in faster Li+ insertion/extraction kinetics due to reduced Li+ diffusion paths, which leads to performance improvement.
More
Translated text
Key words
Fe2TiO5,Lithium-ion battery,Anode,Doping
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper

要点】:研究通过在Fe2TiO5中引入Ni2+,合成了Fe2Ti1-xNixO5材料,显著提高了其锂离子存储性能,特别是在快速充电方面表现出色。

方法】:采用传统的陶瓷方法成功合成了Fe2Ti1-xNixO5材料,并通过Ni2+取代Ti4+的方式调节材料的电化学性能。

实验】:通过电化学测试,使用数据集名称未提及的具体数据,发现Fe2Ti1-xNixO5在100次循环后放电容量达到368.6 mAh g-1,且在5000 mA g-1的电流率下放电容量为310.6 mAh g-1,说明材料具有优异的循环稳定性和率性能。在经过额外的45次循环后,材料在100 mA g-1的电流密度下仍保持367.1 mAh g-1的高放电容量。