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Updated: May 7, 2026

Sample Preparation for Probe Electrospray Ionization Mass Spectrometry
Published on: February 19, 2020
Multi-Laboratory Assessment Reveals Variable Ion Species Profiles in Electrospray Ionization Mass Spectrometry
Melanie T Odenkirk1, Jacqueline M Chaparro1,2, Nathan T Montgomery2
1Department of Horticulture and Landscape Architecture, Colorado State University, Fort Collins, Colorado 80521, United States.
None:
Electrospray ionization (ESI) is a foundational technique in mass spectrometry (MS) widely applied to measure nonvolatile molecules in diverse chemical and biological samples. Yet variation in ESI-MS instrumentation, operating settings, and parameters such as solvent composition creates specific, local ionization environments that drive the formation of select ion species for individual analytes. As ESI continues to advance analytical discovery, understanding the extent to which variation in ion species formation impacts intra- and inter-experimental results is essential. Here, we assessed ion species formation by analyzing an internal retention time standard (IRTS) mixture across ten laboratories employing high-resolution ESI-MS instrumentation from four vendors (Agilent Technologies, ThermoFisher Scientific, Shimadzu Corporation, and Waters Corporation). Instrument vendors were considered not as a benchmark of performance, but as a practical framework to capture differences in source design, ion optics, and analyzer/detectors that are inherently coupled to commercial platforms. Despite the use of standardized extraction and chromatographic protocols, differences in instrument configuration, source conditions, and method execution resulted in variation in ion species formation across vendors, among laboratories using instruments from the same vendor, and even within individual laboratories. These findings demonstrate that, even with standardized methods, the collective influence of local ionization environments on ion species formation remains a critical obstacle for interpreting LC-MS small molecule data and improving reproducibility and comparability across studies.
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