Table 1.   Identification methods

1

Co-analysis of samples and analytical standards (substances/reference materials)

Matching analytical signals of the analyte and the reference substance* when using two or more independent techniques of analysis, primarily MS and chromatography, and varying analysis conditions

Fully exploiting the capabilities of on-demand synthesis of chemical compounds [13] expands the scope of application of this most reliable identification method

2

Comparison of analytical results with reference data of experimental origin

Data represent mass spectra and retention parameters recorded under similar but not identical experimental conditions (different times, different conditions for recording spectra and chromatograms, different laboratory, different instrument models)

Identification is enabled by the expansion of mass spectral libraries, summaries of chromatographic retention parameters and collision cross-section(CCS) values in IMS, and the emergence of molecular networks

3

Comparison with natural physical constants

HRMS: Relative molecular masses and isotope pattern

The widespread use of HRMS ensures the implementation of this identification method by clarifying the molecular formulas of candidates for identification

4

Comparison of analysis results with predicted reference data

Mass spectra, retention parameters, and other characteristics are calculated primarily using machine learning methods and used as reference data

Prediction methods are being improved, prediction accuracy is increasing

5

Interpretation of mass spectra

Conclusions about the structure (substructures) of analytes are made based on the rules and patterns of fragmentation and/or using appropriate computer programs

Methods for computer interpretation of mass spectra are being widely developed, in parallel with the development of methods for their prediction based on the expected structure of the analyte (no. 4)