Electrochemical performance investigation of LiFePO4/C0.15-x (x=0.05, 0.1, 0.15 CNTs) electrodes at various calcination temperatures: Experimental and Intelligent Modelling approach

• Published in: Electrochimica acta 2020-01, Vol.330, p.135314, Article 135314
• Main Authors: Li, Wei, Garg, Akhil, Le, My Loan Phung, Ruhatiya, C., Gao, Liang, Tran, Van Man
• Format: Article
• Language: English
• Subjects: Artificial neural network; Artificial neural networks; Carbon; Carbon black; Carbon nanotubes; Electrochemical analysis; Electrodes; Electrons; Galvanostatic cyclic testing; Investigations; Li ion batteries; LiFePO4; Modelling; Morphology; Nanocomposites; Photoelectrons; Raman spectroscopy; Roasting; Spectrum analysis; Synthesis; X ray photoelectron spectroscopy; X-ray diffraction
• ISSN: 0013-4686; 1873-3859
• DOI: 10.1016/j.electacta.2019.135314

To investigate the combined effects of calcination temperature and carbon nanotube (CNT) proportion, we have synthesized LiFePO4 (LFP) using hydrothermal process using glucose at various calcination temperatures (600 °C, 700 °C, 800 °C). The morphology of the synthesized LFP was investigated by Scanning electron microscope (SEM). Structural changes of the synthesized LFP were studied by X-Ray diffraction (XRD), Raman spectroscopy and X-ray photoelectron spectroscopy. In Li half cells containing 15% carbon, carbon black ratio was replaced by CNTs in proportions of 5%, 10%, and 15%. Through the cyclic voltammetry (CV) curves, the diffusion coefficients of Li ions were determined, which shows an increasing trending with the increase of the proportion of CNTs. Intelligent Modelling approach of Artificial neural network (ANN) was then applied on the obtained specific capacity to predict the trend of change in specific capacity with temperature and CNT proportion. The composite electrode LFP-800 °C/C/10%CNT was predicted to be the best performer by ANN approach and also validated. In the galvanostatic cycling test, this nanocomposite showed the highest specific capacity of 160.8 mAh/g. The ANN results predicted the specific capacity of every proportion of CNT (0–15%) and temperature (600–800 °C) thus reducing experimental needs as well. •Effects of calcination temperature and CNT for LiFePO4 batteries was studied.•Morphology was studied by SEM, XRD, Raman and X-RAY photoelectron spectroscopy.•ANN was applied and predicted specific capacity accurately based on CNT Proportion.•The highest specific capacity of 160.8 mAh/g was found.