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Updated: Jun 12, 2026

Imaging of Biological Tissues by Desorption Electrospray Ionization Mass Spectrometry
Published on: July 12, 2013
Matrix Effects in Desorption Electrospray Ionization across Mineral and Rock Substrates
Mingtan Dong1,2, Wei Yang1, Jialong Hao1
1Key Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China.
Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) of geological samples is affected by substrate properties. Surface roughness and mineralogy systematically alter ion signal intensity and form, impacting quantitative analysis.
Area of Science:
- Geochemistry
- Analytical Chemistry
- Planetary Science
Background:
- Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is a powerful tool for in situ chemical analysis of geological and planetary materials.
- Quantitative DESI-MSI studies are often hindered by matrix effects, particularly those related to substrate properties.
Purpose of the Study:
- To systematically evaluate the impact of mineral and rock substrates on DESI-MSI signal response.
- To understand how substrate physical and chemical properties influence quantitative chemical imaging.
Main Methods:
- Investigated 25 mineral and rock substrates using DESI-MSI.
- Continuously infused a six-component internal-standard mixture into the spray solvent.
- Quantified ion responses across different substrates to assess matrix effects.
Main Results:
- Signal intensities decreased with increasing surface roughness, indicating physical sampling efficiency is critical.
- Different mineral classes showed systematic response variations even at similar roughness, influenced by crystal chemistry and interfacial effects.
- Substrates altered ion-form distributions (protonated/deprotonated species and adducts).
Conclusions:
- Substrate properties significantly influence DESI-MSI signal behavior, affecting ion yield and ion-form partitioning.
- Normalization using internal standards can mitigate substrate-driven variability in geological and planetary DESI-MSI.
- Findings provide a practical framework for improving quantitative accuracy in substrate-based DESI-MSI analyses.
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