Revealing Silicon’s Delithiation Behaviour through Empirical Analysis of Galvanostatic Charge–Discharge Curves

The galvanostatic charge–discharge (GCD) behaviour of silicon (Si) is known to depend strongly on morphology, cycling conditions and electrochemical environment. One common method for analysing GCD curves is through differential capacity, but the data processing required necessarily degrades the res...

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Bibliographic Details
Published in:Batteries (Basel) 2023-01, Vol.9 (5), p.251
Main Authors: Huld, Frederik T., Mæhlen, Jan Petter, Keller, Caroline, Lai, Samson Y., Eleri, Obinna E., Koposov, Alexey Y., Yu, Zhixin, Lou, Fengliu
Format: Article
Language:English
Subjects:
Amorphous silicon
Carbon black
Chemical properties
Chemical Sciences
Data analysis
Data processing
Data smoothing
Design and construction
differential capacity
Discharge
Electric power
Electric properties
Electrodes
Electrolytes
Empirical analysis
Energy storage
Engineering Sciences
Equilibrium
Equilibrium conditions
Graphite
incremental capacity analysis
Lithium
Lithium compounds
Materials
Methods
Microscopy
Morphology
Nanowires
NMR
Nuclear magnetic resonance
Other
Silicon
silicon anodes
Structure
Thin films
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Summary:The galvanostatic charge–discharge (GCD) behaviour of silicon (Si) is known to depend strongly on morphology, cycling conditions and electrochemical environment. One common method for analysing GCD curves is through differential capacity, but the data processing required necessarily degrades the results. Here we present a method of extracting empirical information from the delithiation step in GCD data for Si at C-rates above equilibrium conditions. We find that the function is able to quickly and accurately determine the best fit to historical half-cell data on amorphous Si nanowires and thin films, and analysis of the results reveals that the function is capable of distinguishing the capacity contributions from the Li3.5Si and Li2Si phases to the total capacity. The method can also pick up small differences in the phase behaviour of the different samples, making it a powerful technique for further analysis of Si data from the literature. The method was also used for predicting the size of the reservoir effect (the apparent amount of Li remaining in the electrode), making it a useful technique for quickly determining voltage slippage and related phenomena. This work is presented as a starting point for more in-depth empirical analysis of Si GCD data.
ISSN:2313-0105
2313-0105
DOI:10.3390/batteries9050251