Protonentransfer in Wasser an Grenzflächen
Computergestütztes Werkstoffdesign und Simulation von Werkstoffverhalten von atomistischer bis mikroskopischer Skala
Theoretische Chemie: Moleküle, Materialien, Oberflächen
Zusammenfassung der Projektergebnisse
Despite its simple appearance, water is a complicated liquid. If we look at it at a molecular level, we notice that it is not only made up of water molecules, but has the tendency to form charged defects where one hydrogen atom is transferred to another water molecule, leaving an excess proton (H3 O+) and hydroxide ion (OH−) behind. These two species are linked to diverse processes and applications for example in fuel cells, the proton transfer along biological channels, the acidification of our oceans, and enzyme catalysis. This research project focused on understanding the behavior of these charge defects near technologically relevant surfaces such as graphene - a two-dimensional material of great importance. Through the development and use of atomistic simulation techniques, the project aimed at providing detailed insight into the mechanism of proton transfer of these species in water near interfaces as well as their propensity to the interface. Our approach involved developing a machine learning model to describe the underlying interactions at an accurate level with atom scale resolution. This model was trained using data from quantum mechanical calculations to ensure the correct description of bond breaking and forming events. Afterwards, the model was used in molecular dynamics simulations that propagate the system in time. Through multiple of these virtual experiments, it is possible to analyse the motion of the charged defects in the liquid water environment and establish their propensity to the interface. The simulations using this model revealed noteworthy findings. Protons showed a preference for staying close to the surface, while hydroxide ions tended to stay in the bulk water region. This observation challenged existing assumptions and indicated a more intricate relationship between these charged species and surfaces. In a simplified manner, this could be summarised by saying that the graphene/water interface is acidic, with a pH similar to that of a lemon. In essence, the project’s main achievement was the development and application of the machine learning model, providing insights into the behavior of charged defects near surfaces. This understanding has implications for fields such as surface chemistry and materials science, offering a more accurate description of microscopic interactions with potential real-world applications for batteries or catalytic processes.
Projektbezogene Publikationen (Auswahl)
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Origin of dielectric polarization suppression in confined water from first principles. Chemical Science, 15(2), 516-527.
Dufils, T.; Schran, C.; Chen, J.; Geim, A. K.; Fumagalli, L. & Michaelides, A.
