Metal-assisted secondary ion mass spectrometry using atomic (Ga+, In+) and fullerene projectiles

Area of Science:

• Surface science and analytical chemistry
• Mass spectrometry techniques
• Materials characterization

Background:

• Metal-assisted secondary ion mass spectrometry (MetA-SIMS) is a powerful technique for analyzing organic materials.
• The choice of primary ion and sample preparation, including metal deposition, significantly impacts spectral quality and ion yields.
• Understanding these influences is critical for optimizing MetA-SIMS analysis of diverse organic samples.

Purpose of the Study:

• To compare the effectiveness of monatomic (e.g., Ga+, In+) and buckminsterfullerene (C60+) primary ions in MetA-SIMS.
• To evaluate the role of gold metallization in enhancing ion yields and detecting specific molecular fragments.
• To provide guidelines for selecting optimal experimental conditions in MetA-SIMS.

Main Methods:

• Analysis of organic samples (additive molecules, polyolefins, peptides) using MetA-SIMS.
• Comparison of primary ions: monatomic (Ga+, In+) versus buckminsterfullerene (C60+).
• Gold deposition via sputter-coating and thermal evaporation, assessed by electron microscopy.
• Evaluation of fragment and parent-like ion yields under various experimental conditions.

Main Results:

• C60+ projectiles generally achieve high ion yields without gold metallization for most samples.
• Gold metallization is essential for observing large cationized polymer fragments (m/z ~1000-2000) with monatomic ions (Ga+/In+) on polyethylene and polypropylene.
• The dynamic enhancement of ion yields by gold nanoparticles is projectile-dependent, showing increased yields with Ga+ and decreased yields with C60+.

Conclusions:

• Buckminsterfullerene (C60+) ions are highly effective for MetA-SIMS, often negating the need for metal coating.
• Gold metallization is critical for specific applications, particularly for detecting large polymer fragments using monatomic ions.
• The study provides valuable insights and guidelines for optimizing MetA-SIMS experimental parameters based on sample type and desired ion species.