The lack of standards to identify oligomeric molecules is a challenge for the analysis of complex organic mixtures. High-resolution mass spectrometry-specifically, Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS)-offers new opportunities for analysis of oligomers with the assignment of formulae (Cx Hy Oz ) to detected peaks. However, matching a specific structure to a given formula remains a challenge due to the inability of FT-ICR MS to distinguish between isomers. Additional separation techniques and other analyses (e.g., NMR spectroscopy) coupled with comparison of results to those from pure compounds is one route for assignment of MS peaks. Unfortunately, this strategy may be impractical for complete analysis of complex, heterogeneous samples. In this study we use computational stochastic generation of lignin oligomers to generate a molecular library for supporting the assignment of potential candidate structures to compounds detected during FT-ICR MS analysis. This approach may also be feasible for other macromolecules beyond lignin.
Keywords: analytical methods; biomass; lignin; mass spectrometry; simulations.
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