Internal Calibration without Internal Calibrants by Mass Difference Analysis in FT-ICR Mass Spectrometry

We report an improved, fully automated method of mass spectral calibration that relies on mass differences instead of internal calibrants. First, we introduce the mass difference spectrum and note that confident elemental formulas can be assigned to the most abundant mass differences between 0 and 50 Daltons, even for poorly calibrated data. Second, we demonstrate recalibration to as low as 80 ppb rms error by optimizing the measured mass differences, without reference to any known masses in the spectrum. Finally, the improved global calibration facilitates a subsequent "walking" calibration that proceeds through simple matrix intersection calculations and ultimately yields confident molecular formula assignments. We apply the method to a variety of complex samples, including petroleum, dissolved organic matter (natural, pyrogenic, anthropogenic), biomass, biofuels, lithium-ion batteries, polymers, aerosols, and emerging environmental contaminants, and others that contain repeated series of mass differences (characteristic "building blocks"). Obvious for polymers, but less so for other sample types, the repeated mass spacings can arise from thermal/chemical degradation pathways, combustion/pyrolysis, molecular synthesis methodologies, and/or electrochemical reactions, which are exploited herein for mass spectral recalibration. The method is implemented in an open-source, Python-based, software platform, PyC2MC, which also enables automated batch file processing of time-resolved, complex mass spectral data.