We are happy to announce we’ll be attending the Smithers Extractables & Leachables Europe’s Conference 2025 on November 3-5 in Amsterdam, Netherlands. Over the course of two days, attendees will engage in presentations on industry trends and participate in collaborative discussions.
Join our presentation: Use of the Retention Index to Secure Correct Identities in GC/MS
Check back here for the date, time and location.
Presenter: Piet Christiaens, PhD, Scientific Director, Nelson Labs
Abstract:
Organic extractables & leachables surfaced by GC/MS are often identified by mass spectral matching (MSM) in which the experimental mass spectrum is matched to reference spectra contained in a spectral library. The compound is “identified” as being the compound whose reference mass spectrum best matches the experimental spectrum, which often leads to flawed identifications.
A compound’s Retention Index (RI) is an independent means of corroborating the proposed MSM identities. A compounds’ analytical RI can be matched to reference RIs contained in a RI database (e.g., NIST23). The identity secured by MSM is corroborated when the experimental RI acceptably matches the reference RI of the compound proposed by MSM.
Practical use of RI matching requires that acceptance criteria be established to define when an acceptable RI match has been achieved. Acceptance criteria for RI for supporting, rejecting, or accepting proposed identities were established (based on a confusion matrix) using experimental values for RI for 3140 compounds, secured by Nelson Labs and reference RI values found in the commercially available NIST23 library.
Some of the conclusions:
For 71% of the 3140 compounds, the difference in Retention Index (between the NIST reference RI-value and the experimental RI-value) was less than ΔRI≤20. 96% of the candidate structures, obtained via mass spectral matching, were rejected correctly when applying a rejection criterion for the difference in Retention Index (between the NIST reference RI-value and the experimental RI-value) of ΔRI>50.
In addition, some other very interesting conclusions could be drawn from this large data set (eg what is an “acceptable” Match Factor? Where do the correct identifications rank in the proposed identifications?) which will be an eye opener to many GC/MS-practitioners.
To sign up please click here.
