化学
阴极
电化学
可扩展性
格子(音乐)
钠
化学计量学
晶格常数
氧化物
电极
电池(电)
氧化钠
衍射
电化学电池
分析化学(期刊)
光电子学
化学物理
工艺工程
想象
纳米技术
作者
Xiao‐Chuan Su,Ruo-Xi Jin,Xiaodong Qi,Hao-Ran Chen,Jingchen Lian,Lin‐Bo Huang,Xing Zhang,Lirong Zheng,Jing Zhang,Yu‐Jie Guo,Sen Xin,Yu‐Guo Guo
摘要
Abstract The precise control of lattice sodium stoichiometry in cathodes is paramount for sodium-ion battery performance, as it constitutes the sole charge carrier inside the battery during the charge/discharge process. However, precisely tracking the lattice sodium inventory within Na-layered oxide cathodes, particularly during manufacturing, remains a significant challenge. Here, we propose a reliable descriptor, the diffraction peak intensity ratio (α = I(003)/I(104)), which allows the rapid, accurate, and nondestructive quantification of lattice sodium and distinguishes it from inactive sodium. In particular, a rational correlation can be established among the α value, lattice sodium content, and electrochemical properties to enable the α value to predict the electrochemical performance of the as-prepared Na-layered oxides. To achieve continuous and scalable online lattice sodium quantification during manufacturing, we design an industrial automated testing platform applicable to the cathode material production lines with high efficiency and accuracy. Our work provides a universal solution for the prediction and adjustment of material performance during the synthesis and processing, which ultimately accelerates the sustainable development of sodium-ion batteries.
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