Genetic Algorithm Optimized Printed Circuit Board Ion Funnel Tandem Subambient Pressure Ionization with...

Area of Science:

• Analytical Chemistry
• Mass Spectrometry Instrumentation

Background:

• Tandem ion funnels (IF) enhance mass spectrometry sensitivity by minimizing ion losses.
• A key challenge with IF is inherent mass discrimination, limiting ion transmission efficiency (TE).
• Conventional optimization methods fail to address combined parameter effects, requiring extensive tuning.

Purpose of the Study:

• To design and evaluate a genetic algorithm (GA)-optimized printed circuit board ion funnel (PCBIF).
• To address ion loss during ion transfer in mass spectrometers at subambient pressure.
• To improve ion transmission efficiency (TE) over a wide mass range.

Main Methods:

• Designed and fabricated a GA-optimized PCBIF.
• Integrated the PCBIF into the SPIN interface for mass spectrometry.
• Utilized simulation studies to optimize characteristic parameters and assess TE.

Main Results:

• The GA effectively optimized PCBIF design, achieving 96% ion TE for m/z 50–700 within 4 hours.
• Preliminary tests of the SPIN-PCBIF-MS demonstrated a limit of detection (LOD) of 0.01 nM.
• Simulation results confirmed the GA's ability to find optimal parameters efficiently.

Conclusions:

• GA-optimized PCBIF significantly enhances ion transmission efficiency and mass spectrometry sensitivity.
• The proposed GA method provides an effective approach for designing ion funnels and similar devices.
• This automated optimization strategy reduces tuning time and improves performance across various mass ranges.