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Related Concept Videos

Electrospray Ionization (ESI) Mass Spectrometry01:12

Electrospray Ionization (ESI) Mass Spectrometry

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Higher molecular weight biomolecules are nonvolatile compounds that may decompose before ionizing or vaporizing during mass analysis with conventional electron impact ionization methods. Accordingly, electrospray ionization (ESI) is the favored method for vaporizing and ionizing biomolecules as it circumvents rapid fragmentation and enables the recording of mass signals for the entire biomolecule.
ESI utilizes electrical energy to transfer ions from the liquid phase of the sample into the...
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Mass Spectrometers01:16

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This lesson details the instrumentation of a mass spectrometer—a physical instrument to perform mass spectrometry on analyte molecules and record the characteristic mass spectra. This is achieved via three chief functions:
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Mass Spectrometry: Overview01:19

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Mass spectrometry is an analytical technique used to determine the molecular mass and molecular formula of a compound. The basic principle of mass spectrometry is to generate ions from the analyte molecule and measure these ion abundances against their molecular mass.  One common type of ionization, known as electrospray ionization or EI, bombards the analyte molecules in the gas phase with high-energy electron beams. The electron beams displace an electron from the molecule and leave...
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Mass Spectrum: Interpretation01:24

Mass Spectrum: Interpretation

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An unknown compound can be established by identifying the molecular ion peak in the mass spectrum. The molecular ion peak is often weak or absent due to the predominance of fragmentation in high-energy electron beams. In such cases, a low-energy electron beam can be used to scan the spectrum to enhance the intensity of the molecular ion peak. Additionally, chemical ionization, field ionization, and desorption ionization spectra are used to obtain a relatively intense molecular ion peak.
To...
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Chemical Ionization (CI) Mass Spectrometry01:21

Chemical Ionization (CI) Mass Spectrometry

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The molecular ion peak of a molecule in the mass spectrum provides vital information for molecular identification. However, conventional electron impact ionization can lead to the rapid dissociation of some molecular ions before they reach the detector. A milder ionization method is required to increase the lifetime of such ionized analyte molecules. Chemical ionization (CI) is a gas-phase protonation reaction useful for mass-analyzing analyte molecules that are easily protonated to yield the...
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Mass Spectrum01:23

Mass Spectrum

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A mass spectrum is the graphical representation of the relative abundance of the charged fragments in an analyte plotted against their mass-to-charge ratio (m/z). The plot's x axis represents the ratio of the mass of the charged fragment to the elementary charge it carries. The y axis of the plot represents the relative abundance of each charged species. The relative abundance is calculated from the signal intensity of each charged species recorded at the detector. The most intense signal...
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Updated: Aug 12, 2025

Sample Preparation for Probe Electrospray Ionization Mass Spectrometry
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Rapid Approximate Subset-Based Spectra Prediction for Electron Ionization-Mass Spectrometry.

Richard Licheng Zhu1, Eric Jonas2

  • 1Committee on Computational and Applied Mathematics, Department of Statistics, University of Chicago, 5747 South Ellis Avenue, Chicago, Illinois60637, United States.

Analytical Chemistry
|January 25, 2023
PubMed
Summary

We developed a new deep learning method, RASSP, to predict electron ionization-mass spectra (EI-MS) for small molecules. This computational approach significantly improves spectral database accuracy and aids in identifying unknown chemical structures.

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Area of Science:

  • Analytical Chemistry
  • Computational Chemistry
  • Machine Learning

Background:

  • Mass spectrometry is crucial for identifying compounds and determining chemical structures.
  • Accurate mass spectral data is essential for compound identification.
  • Computational prediction of mass spectra can expand spectral databases for unmeasured molecules.

Purpose of the Study:

  • To present a novel computational method for predicting electron ionization-mass spectra (EI-MS) of small molecules.
  • To improve the accuracy and utility of spectral databases for chemical analysis.
  • To develop deep learning models that can predict mass spectra from chemical structures.

Main Methods:

  • Developed two deep learning models: FormulaNet and SubsetNet, combined as rapid approximate subset-based spectra prediction (RASSP).
  • FormulaNet predicts subformulae, while SubsetNet predicts vertex subsets of molecular graphs.
  • Models were trained and evaluated using the NIST 2017 Mass Spectral Library and PubChem data.

Main Results:

  • FormulaNet achieved 92.9% weighted dot product accuracy and 98.0% recall (top 10).
  • SubsetNet demonstrated strong generalization, particularly in high-resolution, low-data scenarios.
  • The best model reduced spectral database lookup error rate by 2.9x (from 5.7% to 2.0% in top 10).

Conclusions:

  • RASSP significantly enhances the accuracy of EI-MS prediction compared to previous methods.
  • The developed models offer superior performance and generalization for spectral database applications.
  • Freely accessible source code and 73.2 million predicted spectra will benefit the scientific community.