five

Data_Sheet_1_Local Substrate Heterogeneity Influences Electrochemical Activity of TEM Grid-Supported Battery Particles.PDF

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://figshare.com/articles/dataset/Data_Sheet_1_Local_Substrate_Heterogeneity_Influences_Electrochemical_Activity_of_TEM_Grid-Supported_Battery_Particles_PDF/14246045
下载链接
链接失效反馈
官方服务:
资源简介:
Understanding how particle size and morphology influence ion insertion dynamics is critical for a wide range of electrochemical applications including energy storage and electrochromic smart windows. One strategy to reveal such structure–property relationships is to perform ex situ transmission electron microscopy (TEM) of nanoparticles that have been cycled on TEM grid electrodes. One drawback of this approach is that images of some particles are correlated with the electrochemical response of the entire TEM grid electrode. The lack of one-to-one electrochemical-to-structural information complicates interpretation of genuine structure/property relationships. Developing high-throughput ex situ single particle-level analytical techniques that effectively link electrochemical behavior with structural properties could accelerate the discovery of critical structure-property relationships. Here, using Li-ion insertion in WO3 nanorods as a model system, we demonstrate a correlated optically-detected electrochemistry and TEM technique that measures electrochemical behavior of via many particles simultaneously without having to make electrical contacts to single particles on the TEM grid. This correlated optical-TEM approach can link particle structure with electrochemical behavior at the single particle-level. Our measurements revealed significant electrochemical activity heterogeneity among particles. Single particle activity correlated with distinct local mechanical or electrical properties of the amorphous carbon film of the TEM grid, leading to active and inactive particles. The results are significant for correlated electrochemical/TEM imaging studies that aim to reveal structure-property relationships using single particle-level imaging and ensemble-level electrochemistry.
创建时间:
2021-03-19
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作