Atomic masses and isotopic abundances are independent and complementary properties for discriminating among ion compositions. The number of possible ion compositions is greatly reduced by accurately measuring exact masses of monoisotopic ions and the relative isotopic abundances (RIAs) of the ions greater in mass by +1 Da and +2 Da. When both properties are measured, a mass error limit of 6-10 mDa (< 31 ppm at 320 Da) and an RIA error limit of 10% are generally adequate for determining unique ion compositions for precursor and fragment ions produced from small molecules (less than 320 Da in this study). 'Inherent interferences', i.e., mass peaks seen in the product ion mass spectrum of the monoisotopic [M+H]+ ion of an analyte that are -2, -1, +1, or +2 Da different in mass from monoisotopic fragment ion masses, distort measured RIAs. This problem is overcome using an ion correlation program to compare the numbers of atoms of each element in a precursor ion to the sum of those in each fragment ion and its corresponding neutral loss. Synergy occurs when accurate measurement of only one pair of +1 Da and +2 Da RIAs for the precursor ion or a fragment ion rejects all but one possible ion composition for that ion, thereby indirectly rejecting all but one fragment ion-neutral loss combination for other exact masses. A triple-quadrupole mass spectrometer with accurate mass capability, using atmospheric pressure chemical ionization (APCI), was used to measure masses and RIAs of precursor and fragment ions. Nine chemicals were investigated as simulated unknowns. Mass accuracy and RIA accuracy were sufficient to determine unique compositions for all precursor ions and all but two of 40 fragment ions, and the two corresponding neutral losses. Interrogation of the chemical literature provided between one and three possible compounds for each of the nine analytes. This approach for identifying compounds compensates for the lack of commercial ESI and APCI mass spectral libraries, which precludes making tentative identifications based on spectral matches.
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