Session: Parallel session 1 - environmental analysis

Porous silicon nanostructures in Laser Desorption Ionization Mass Spectrometry

Clara WHYTE FERREIRA^1,2,3, Bastien CABRERA-TEJERA¹, Yannick COFFINIER³, Romain TUYAERTS², Gilles SCHEEN², Gauthier EPPE¹, Edwin DE PAUW¹

¹Mass Spectrometry Laboratory, University of Liège, Belgium, Liège, Belgium
²Incize, Louvain-la-Neuve, Belgium
³University of Lille, CNRS, UMR 8520 - IEMN, Lille, France

Introduction

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is widely used for analyzing thermally unstable and non-volatile molecules. However, MALDI-MS has limitations, including matrix deposition quality and interference at lower masses (<700 m/z). Surface-Assisted LDI-MS (SALDI-MS) is a technique that uses inorganic nanostructure subtstrates to overcome some of the MALDI limitations. This study investigates porous silicon (PSi) surfaces with varying morphological characteristics as substrates in LDI-MS.

Methodology

PSi substrates were produced by electrochemical etching of boron-doped silicon wafers, with different ethcing conditions to achieve various porosities and pore sizes. Substituted benzylpyridinium (BP) ions served as thermometer ions to evaluate the effective temperature associated with the different PSi surfaces. The survival yield (SY) of the thermometer ions was calculated from mass spectra aquired in a rapifleX (Bruker) instrument. Effective temperatures were derived from SY data and dissciation energy of the ions (from DFT simulations).

Results

Porosity significantly impacts effective temperature and analyte fragmentation. A porosity of around 50% was optimal for softer desorption/ionization, facilitating better analysis of intact molecules. Preliminary results showed successful detection of small metabolites such as carbohydrates, peptides, and lipids, demonstrating the potential of PSi substrates in LDI-MS.

Conclusion

This study highlights the importance of PSi substrate porosity on LDI-MS performance. Optimal porosity levels reduce analyte fragmentation, enhancing the analysis of small metabolites. These findings advance the understanding of LDI mechanisms in porous silicon, suggesting optimization pathways for broader research and industrial applications. Future work will focus on correlating material properties (such as surface absorbance and thermal conductivity) with LDI performance to further refine this technique.