石墨烯
材料科学
氧化石墨烯纸
拉曼光谱
氧化物
石墨
分析化学(期刊)
微观结构
透射电子显微镜
磁场
纳米技术
化学工程
复合材料
光学
冶金
化学
物理
工程类
色谱法
量子力学
作者
Pankaj Kumar Singh,Kamal Sharma,Pradeep Kumar Singh
出处
期刊:International Journal of Modern Physics B
[World Scientific]
日期:2023-03-31
标识
DOI:10.1142/s0217979224500917
摘要
The control over microstructural characteristics of graphene oxide (GO) is one of the most serious issues in the domain of graphene synthesis as this affects the graphene’s properties, and functionality. In this study, the primary objective is electrochemical synthesis graphene in the presence of magnetic field that is applied externally. During the synthesis process, the magnetic field was applied in a direction that was perpendicular to the applied potential. This causes the electrolyte to spin flow around the cell. Subsequently, the goal is to provide a comparative analysis between the microstructural characteristics of graphene that has been synthesized in situ and ex situ magnetic field. The cylindrical graphite was used as an anode, and a carbon electrode that had been recovered from a waste dry cell battery was used as a cathode. The pre-oxidized graphite was sonicated (synthesized under magnetic field, and without magnetic field) in sterilized water for 10[Formula: see text]min with a probe-type sonicator and thermally reduced at same temperature i.e., 850 ∘ C followed by furnace cooling. The findings of the Raman spectroscopy, atomic force microscopy (AFM), field emission scanning electron microscopy (FESEM) and transmission electron microscopy (TEM) characterizations indicate that the magnetic flux that was applied has a significant influence on the surface height and roughness, microstructure, and surface state, a structural disorder in comparison to when there was no magnetic field applied to the thermally reduced graphene oxide (rGO). On the other side, from the data obtained by XRD and TGA analysis, the applied magnetic field seems to have very little effect on phase, lattice parameter and thermal stability.
科研通智能强力驱动
Strongly Powered by AbleSci AI