Efficient ab initio calculation of electronic stopping in disordered systems via geometry pre-sampling: Application to liquid water.
Bin GuBrian CunninghamDaniel Muñoz-SantiburcioFabiana Da PieveEmilio ArtachoJorge J KohanoffPublished in: The Journal of chemical physics (2020)
Knowledge of the electronic stopping curve for swift ions, Se(v), particularly around the Bragg peak, is important for understanding radiation damage. Experimentally, however, the determination of such a feature for light ions is very challenging, especially in disordered systems such as liquid water and biological tissue. Recent developments in real-time time-dependent density functional theory (rt-TDDFT) have enabled the calculation of Se(v) along nm-sized trajectories. However, it is still a challenge to obtain a meaningful statistically averaged Se(v) that can be compared to observations. In this work, taking advantage of the correlation between the local electronic structure probed by the projectile and the distance from the projectile to the atoms in the target, we devise a trajectory pre-sampling scheme to select, geometrically, a small set of short trajectories to accelerate the convergence of the averaged Se(v) computed via rt-TDDFT. For protons in liquid water, we first calculate the reference probability distribution function (PDF) for the distance from the proton to the closest oxygen atom, ϕR(rp→O), for a trajectory of a length similar to those sampled experimentally. Then, short trajectories are sequentially selected so that the accumulated PDF reproduces ϕR(rp→O) to increasingly high accuracy. Using these pre-sampled trajectories, we demonstrate that the averaged Se(vp) converges in the whole velocity range with less than eight trajectories, while other averaging methods using randomly and uniformly distributed trajectories require approximately ten times the computational effort. This allows us to compare the Se(vp) curve to experimental data and assess widely used empirical tables based on Bragg's rule.
Keyphrases
- depressive symptoms
- density functional theory
- molecular dynamics
- ionic liquid
- oxidative stress
- quantum dots
- machine learning
- magnetic resonance imaging
- magnetic resonance
- mass spectrometry
- photodynamic therapy
- radiation induced
- molecular dynamics simulations
- computed tomography
- water soluble
- contrast enhanced
- monte carlo