Abstract
The identification and measurement of intermediate species that occur after ionization but before fragmentation is an ongoing challenge. These intermediates give insight into the multi-channel reaction mechanisms that occur following ionization, mechanisms which may aid in the prediction of mass spectra. We find that coherent oscillations in the ion yields as a function of femtosecond pump-probe delay can be used to identify these intermediates and trace several ions to their originating intermediate. Additionally, the relative phase of the coherent oscillations between different fragments helps untangle the interplay between the dissociation channels and gives further mechanistic insight. Here, we apply this method to endo-dicyclopentadiene (DCPD) and identify two intermediates that occur following ionization: an intact intermediate of the DCPD cation, and a “broken-bridge” intermediate where one of the cyclopentadiene bridging bonds is broken. These two intermediates contain distinct vibrational signatures which get mapped onto their subsequent product ion yields. Comparison of the experimentally derived frequencies with ab initio calculations help elucidate the identity and spectra of these intermediates. Additionally, ab initio molecular dynamics simulations confirm the existence of both intermediates following ionization and assesses their lifetimes. These results exhibit the power of being able to track the time-dependent yield of all ions simultaneously and gains a deeper understanding of one of the fundamental reactions in mass spectrometry: the retro-Diels Alder reaction.
*S.K acknowledges Air Force Office of Scientific Research under award number FA9550-21-1-0428. J.S. acknowledges funding from the Department of Energy, Office of Basic Energy Sciences, Atomic, Molecular, and Optical Sciences Program under award number SISGR (DE-SC0002325). This work used the SDSC Expanse GPU at San Diego Supercomputer Center through allocation CHE230046 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296. This work was supported in part through computational resources and services provided by the Institute for Cyber-Enabled Research at Michigan State University. BGL gratefully acknowledges support from the National Science Foundation CHE-1954519.