Construction of a Mass Spectrum Library Containing Predicted Electron Ionization Mass Spectra Prepared Using a Machine Learning Model and the Development of an Efficient Search Method.

Electron ionization (EI) mass spectrum library searching is usually performed to identify a compound in gas chromatography/mass spectrometry. However, compounds whose EI mass spectra are registered in the library are still limited compared to the popular compound databases. This means that there are compounds that cannot be identified by conventional library searching but also may result in false positives.

Integrated qualitative analysis of polymer sample by pyrolysis-gas chromatography combined with high-resolution mass spectrometry: Using accurate mass measurement results from both electron ionization and soft ionization.

Rationale: Gas chromatography/mass spectrometry (GC/MS) is a powerful analytical tool used to separate and then identify volatile compounds through library database searches. However, as not all compounds are registered in these databases, it is not uncommon to detect unregistered components. Therefore, new analytical techniques were developed that utilize methods of identification beyond database searches alone.