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Predicting ion mobility collision cross sections directly from standard quantum chemistry software.

Arshad Mehmood1, Benjamin G Janesko1

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A new method predicts ions' collision cross-sectional area using standard quantum chemistry calculations. This simplifies the analysis of ion-mobility mass spectrometry data.

Keywords:
collision cross-sectional areadensity functional theoryion-mobilityisodensity surface areasolvent cavity area

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Area of Science:

  • Computational chemistry
  • Physical chemistry
  • Analytical chemistry

Background:

  • Ion-mobility mass spectrometry (IM-MS) is a powerful analytical technique.
  • Accurate prediction of collision cross-sectional areas (CCSAs) is crucial for IM-MS data interpretation.
  • Existing methods for CCSA prediction can be computationally intensive or require specialized software.

Purpose of the Study:

  • To develop a simplified and accurate method for predicting ions' collision cross-sectional areas.
  • To leverage readily available data from standard quantum chemistry software.
  • To facilitate the assignment of peaks in ion-mobility mass spectra.

Main Methods:

  • Utilizing computed molecular isodensity surface areas from standard quantum chemistry software.
  • Employing computed solvent cavity areas as an alternative predictive metric.
  • Comparing the accuracy of these computed areas against existing projection approximations.

Main Results:

  • Computed molecular isodensity surface areas effectively reproduce predictions from established projection approximations.
  • Computed solvent cavity areas demonstrate comparable accuracy to isodensity surface areas.
  • The proposed method offers a streamlined workflow for CCSA prediction.

Conclusions:

  • The developed method provides an efficient approach to predict ion collision cross-sectional areas.
  • This technique integrates seamlessly with standard quantum chemistry workflows.
  • The simplified prediction of CCSAs aids in the routine assignment of ion-mobility mass spectra.