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Published on: April 29, 2020
Graphene Oxide as a Novel Evenly Continuous Phase Matrix for TOF-SIMS
Lesi Cai1, Linfeng Sheng2, Mengchan Xia1
1Department of Chemistry, Beijing Key Laboratory of Microanalytical Methods and Instrumentation, Tsinghua University, Beijing, 100084, People's Republic of China.
Graphene oxide (GO) enhances Time-of-Flight Secondary Ion Mass Spectrometry (TOF-SIMS) for biomolecule identification. This novel matrix improves lipid ion detection and spatial resolution in biological imaging.
Area of Science:
- Surface Science
- Analytical Chemistry
- Biotechnology
Background:
- Matrix crystallization in Time-of-Flight Secondary Ion Mass Spectrometry (TOF-SIMS) hinders biomolecule identification and spatial resolution in biological research.
- Enhancing molecular ion signals without compromising spatial integrity is crucial for TOF-SIMS applications in complex biological samples.
Purpose of the Study:
- To investigate graphene oxide (GO) as a novel matrix for TOF-SIMS to improve secondary ion yields of intact molecular ions.
- To assess the impact of GO on spatial resolution and the identification of high mass lipids (m/z >700) in biological samples.
- To demonstrate the capability of GO-assisted TOF-SIMS for high-resolution lipid mapping and distinguishing vesicles based on chemical composition.
Main Methods:
- Graphene oxide (GO) was employed as a matrix material for TOF-SIMS analysis.
- TOF-SIMS imaging was performed on biological samples utilizing the GO matrix.
- Analysis focused on improving secondary ion yields, particularly for intact molecular ions ([M + H]+) of lipids (m/z >700).
Main Results:
- Graphene oxide significantly enhanced secondary ion yields for intact molecular ions, simplifying lipid identification.
- GO facilitated homogeneous matrix layer formation, preserving high spatial resolution in TOF-SIMS imaging.
- Lipid mapping with GO revealed detailed morphology and distribution of 800 nm vesicles, distinguishing them by chemical composition.
Conclusions:
- Graphene oxide serves as an effective matrix for TOF-SIMS, enhancing biomolecule signal detection and maintaining spatial resolution.
- This GO-based approach enables straightforward identification and mapping of lipids in complex biological samples.
- The developed method shows significant potential for advanced analysis and imaging of biological systems using TOF-SIMS.
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