Good question. I'd like to know the answer as well.
Anyone more experienced would help us?
Hello guys.
In this book chapter we explained how to do that: https://link.springer.com/chapter/10.1007/978-1-0716-2107-3_6#DOI
Basically here is what you need to do:
Create a table with the following information to find the internal standards in data efficiently: Name, m/z (MZ), retention time (RT), Adduct, InChiKey, Formula, Smiles, and Ontology. An example for PC 15:0_18:1(d7) is showed below. Save the table as .txt. Go to Advanced in the “Identification” tab, and select this .txt file. Set 100 min to “Retention time tolerance”, 0.01 Da as “Accurate mass tolerance”, and 80% to “Identification score cut off”.
Name PC 15:0_18:1(d7)
RT 12.75
MZ 775.59531
Adduct [M+Na]+
InChiKey ZEWLMKXMNQOCOQ-GCHPQBSENA-N
Formula C41H73D7NO8P
Smiles [C@](COP(=O)(
- )OCC[N+](C)(C)C)([H])(OC(CCCCCCC/C=C\CCCCCC([2H])([2H])C([2H])([2H])C([2H])([2H])[2H])=O)COC(CCCCCCCCCCCCCC)=O
Ontology PC
I hope it helps you!