Abstract
Synthetic graphites have been widely used in industrial applications, including as anodes in lithium-ion batteries. Because they are produced at temperatures above 3000 °C, which generate highly ordered graphitic domains, there is typically no discernible evidence of their precursor materials. In this study, three types of graphite, coal tar based anisotropic graphite, petroleum fluid oil based anisotropic graphite, and coal tar based isotropic graphite, were prepared. Conventional characterization techniques such as X-ray diffraction, Raman spectroscopy, transmission electron microscopy, and even electrochemical performance were unable to distinguish their precursors. Therefore, we introduced laser desorption/ionization time-of-flight mass spectrometry (LDI-MS) combined with multivariate statistical analysis to characterize three graphites prepared from different synthetic precursors as well as two commercial graphites. The resulting LDI-MS spectra were analyzed using principal component, hierarchical cluster, and heatmap analyses, which are widely used in clinical mass spectrometric diagnostics. Notably, LDI-MS coupled with multivariate statistics successfully classified the graphites depending on their precursor materials and processing parameters, such as heat-treatment temperature, whereas conventional analytical tools failed to reveal these differences. These results clearly demonstrate the strong potential of LDI-MS and statistical analysis for the precise characterization of carbon materials and for distinguishing their origins and processing routes.
| Original language | English |
|---|---|
| Article number | 21 |
| Journal | Nano Convergence |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Anode
- LDI MS
- Lithium ion battery
- Multivariate analysis
- Synthetic graphite
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