Investigations on conductivity of nitrogen-doped reduced graphene oxide/Li2FeSiO4 cathode material prepared by microwave-assisted method for lithium-ion batteries
Year: 2025
Type: article
Abstract: Li2FeSi04 is a promising cathode active material for lithium-ion batteries due to its significant theoretical capacity (332 mAhg-1). Nevertheless, its practical electrochemical performance faces significant hurdles due to low electron conductivity. In the research, a simple solid-state technique was used to synthesize the high-purity cathode material Li2FeSi04. Additionally, nitrogen-doped reduced graphene oxide nanosheets were fabricated using a household microwave-assisted process and then selectively deposited to coat the active cathode material to increase conductivity and significantly improve electrocatalysis. The properties of the as-prepared nanosheets and Li2FeSi04/ nitrogen-doped reduced graphene oxide nanocomposites are studied using X-ray diffraction, high-resolution transmission electron microscopy, field emission scanning electron microscopy, RAMAN spectrometry, and Fourier transform infrared spectroscopy techniques. The study investigated the influence of different amounts of as-prepared nanosheet coatings on the electrical conductivity of the Li2FeSi04 by comparing their band gap energy value. Accordingly, a lower band gap, indicates higher and better electronic conductivity in the cathode of lithium-ion batteries. Therefore, diffusion reflectance spectroscopy and electrochemical impedance spectroscopy were used to determine the band gap size and conductivity. Studies show that coating Li2FeSi04 particles with only 5 wt% nitrogen-doped nanosheets reduced the bandgap energy value by about 0.78 eV and increased the electrical conductivity by 54.31%. It is concluded that Li2FeSi04/ nitrogen-doped reduced graphene oxide nanocomposites can be a promising candidate as a high-performance cathode material for lithium-ion batteries.
Authors: Saba Zomorrodi, Seyed Pirouz Hoveida Marashi, Zahra Sadeghian, Soheila Javadian
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7106811065