Ion-molecule reactions are ubiquitous. They are important in the emergence of primordial life as solar wind falls onto chemicals turning them into the prebiotic building blocks of life. Ion-molecule reactions are also the basic process underlying the proton-biomolecule collisions relevant in proton therapies in cancer. To better understand these mechanisms, a new study provides novel data on low-energy proton collisions with furan and its derivative molecules, which are models for the deoxyribose sugar unit found in biological processes. These findings have been published in EPJ D by Tomasz Wasowicz from Gdansk University of Technology, Poland, and colleagues, as part of the topical issue "Low-Energy Interactions related to Atmospheric and Extreme Conditions."
Specifically, the authors investigate the interactions of positively charged ions such as protons, carbon and oxygen cations entering collision with gas molecules of furan and the hydrogenated derivatives of furan, called tetrahydrofuran (THF), in the energy range of 50 to 1,000 electronVolts. To do so, they identify the reaction products by detecting their luminescence via collision-induced emission spectroscopy. They also trace the evolution of the underlying collisional processes.
Based on the detection of unusually strong atomic lines of the hydrogen Balmer series, the study shows that the creation of the excited hydrogen depends on the type of projectile selected and its velocity. They believe that collision processes are dominated by electron transfer from the target molecules to protons. First, the proton captures an electron from the target molecule to form an excited hydrogen atom, then this excited hydrogen atom decays by emitting a photon of certain wavelength.
They found that the values of the depopulation factors depend on the collision energies and show major depopulation of higher lying states of hydrogen. By comparing the depopulation factors obtained for different cations, they are able to distinguish between different collisional processes. The findings of the study, the authors believe, can be directly applied to develop software-based diagnostics that are more accurate than currently available solutions.
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