Abstract
Fourier Transform is a low-cost method for improving duty cycle, resolving power, and signal-to-noise ratio in the Ion Mobility Spectrometry (IMS) experiment in a 2-gate IMS cell. By simultaneously pulsing both gates through a frequency sweep, the resulting data may be deconvoluted into a time-based mobility spectrum through a Fast Fourier Transform (FT). However, inconsistencies common in low-cost function generators result in spectral artifacts. In this work, an asynchronous stepped frequency FTIMS method is demonstrated, which uses a simple, software timed pulse generator compatible with any modern Analog-Digital Converter (ADC) system. By unlinking the frequency initiation and data collection using a long rise-time amplifier circuit, a stand-alone FTIMS with Faraday Plate detection was characterized in both single gate and FT modes of operation using the same IMS cell. Asynchronous stepped FTIMS parameters were investigated for system optimization with respect to resolving power, signal-to-noise ratio, and experimental time. Once optimized, asynchronous FTIMS demonstrated significant improvements in resolving power and signal-to-noise ratios without a significant increase in experimental time. By unlinking the frequency generation and data analysis, a simple Python script was demonstrated using a variety of commercially available ADC systems ranging in cost from several thousand to several hundred dollars (USD) without sacrificing spectral fidelity. A custom circuit was developed to allow a Raspberry Pi 4 Single Board Computer (SBC) to function as the data acquisition and control (DAC) interface for a low-cost stand-alone FTIMS solution.