Improved Indicator Algorithms for Tracking a Hydrated Proton as A Local Structural Defect in Grotthuss Diffusion in...

Modeling hydrated proton behavior in water is a complex task due to the proton's delocalized nature. Prior research has shown that proton movement follows the Grotthuss mechanism, where protons hop between water molecules. However, tracking these movements accurately remains a challenge. Established methods use pseudo-atoms to approximate proton positions, but these often fail during donor switch events. No prior work had resolved how to minimize displacement artifacts in such simulations. This gap motivated the development of improved algorithms. Existing methods struggle with trajectory smoothness and accuracy. That uncertainty drove the need for a structural defect-based approach. No prior work had fully addressed how to represent proton delocalization in simulations. This uncertainty limited the accuracy of proton tracking in aqueous systems.

The aim of this study is to improve proton tracking in simulations by refining the proton indicator algorithm. The specific problem is the large displacement artifacts that occur during donor switch events. The motivation is to provide smoother and more accurate trajectories for hydrated proton movement. The original method fails to capture proton delocalization effectively. The authors propose a structural defect-based approach to better represent proton dynamics. This method should reduce trajectory artifacts and improve simulation accuracy. The goal is to enhance the Grotthuss mechanism modeling in aqueous systems. The study focuses on refining the pseudo-atom approach to better approximate proton positions.

The researchers developed two revised algorithms for the proton indicator. These methods model the proton as a structural defect in the water network. The algorithms track the proton's position using a pseudo-atom representation. The simulations involve hydrated proton movement in bulk water. The structural defect approach captures proton delocalization more effectively. The new methods avoid large displacement artifacts during donor switch events. The simulations test the performance of the revised algorithms against the original scheme. The study evaluates trajectory smoothness and proton movement accuracy.

The new algorithms significantly outperform the original scheme in tracking proton movement. The revised methods reduce large displacements in indicator positions during donor switch events. Trajectory smoothness improves, leading to more accurate proton movement modeling. The structural defect approach better captures proton delocalization. Simulations show smoother proton trajectories in bulk water. The new methods minimize artifacts caused by donor switch events. The improved algorithms provide more reliable proton position tracking. These results suggest better modeling of the Grotthuss mechanism in aqueous systems.

The authors propose that the structural defect-based approach improves proton tracking in simulations. The revised algorithms reduce displacement artifacts during donor switch events. These findings suggest better modeling of proton dynamics in aqueous systems. The new methods provide smoother and more accurate proton trajectories. The structural defect representation captures proton delocalization effectively. The improved algorithms enhance the Grotthuss mechanism modeling. The study demonstrates the benefits of refining the pseudo-atom approach. These results may guide future proton tracking in aqueous simulations.