研究目的
Investigating the structural and electrochemical changes in silicon nanowire anodes during lithiation and delithiation cycles using in situ Raman spectroscopy to understand SEI formation and identify new signals.
研究成果
In situ Raman spectroscopy effectively differentiates between SEI formation and structural changes in silicon nanowire anodes. A new signal at 1859 cm?1 is detected, attributed to an unknown SEI component, with carbon coating reducing its intensity. The method complements operando XRD and provides insights into amorphous and liquid species.
研究不足
Challenges include reduced Raman signal due to SEI layer thickness and fluorescence, potential sample irradiation damages, and difficulty in focusing due to electrolyte changes. The new Raman signal at 1859 cm?1 remains unassigned.
1：Experimental Design and Method Selection:
The study uses in situ Raman spectroscopy and operando X-ray diffraction to analyze silicon nanowire anodes in lithium ion batteries. The setup includes a modified coin cell with a quartz window for spectroscopic observation from the back side.
2：Sample Selection and Data Sources:
Silicon nanowires (uncoated and carbon-coated) grown on carbon fiber networks via chemical vapor deposition. Electrolyte used is LP30 with EC/DMC and LiPF
3：List of Experimental Equipment and Materials:
Raman microscope (Renishaw Invia), Ar ion laser (Reliant 150 Select), potentiostat (Biologic SP50), synchrotron XRD at ALBA, CVD furnace (LPCVD PEO603), carbon fiber networks (Sigracet GDL 25AA), and various chemicals.
4：Experimental Procedures and Operational Workflow:
Electrodes prepared by depositing Au nanoparticles and growing SiNWs. Batteries assembled in an argon glove box, cycled galvanostatically between
5：2 V and 01 V. Raman measurements performed with 514 nm laser, 2 mW power, 20 s exposure time. XRD measurements with 1 min exposure per measurement. Data Analysis Methods:
Raman spectra analyzed for peak intensities and shifts; XRD data analyzed for integrated intensities and structural changes using curve fitting.
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