Modeling Equilibration Dynamics of Hyperthermal Products of Surface Reactions Using Scalable Neural Network Potential with First-Principles Accuracy.

Equilibration dynamics of hot oxygen atoms following the dissociation of O on Pd(100) and Pd(111) surfaces are investigated by molecular dynamics simulations based on a scalable neural network potential enabling first-principles description of the interaction of O and O interacting with variable Pd supercells. By analyzing hundreds of trajectories with appropriate initial sampling, the measured distance distribution of equilibrated atom pairs on Pd(111) is well reproduced. However, our results on Pd(100) suggest that the ballistic motion of hot atoms predicted previously is a rare event under ideal conditions, while initial molecular orientation and surface thermal fluctuation could significantly affect the overall postdissociation dynamics.

Searching Configurations in Uncertainty Space: Active Learning of High-Dimensional Neural Network Reactive Potentials.

Neural network (NN) potential energy surfaces (PESs) have been widely used in atomistic simulations with ab initio accuracy. While constructing NN PESs, their training data points are often sampled by molecular dynamics trajectories. This strategy can be however inefficient for reactive systems involving rare events.

Automatically growing global reactive neural network potential energy surfaces: A trajectory-free active learning strategy.

An efficient and trajectory-free active learning method is proposed to automatically sample data points for constructing globally accurate reactive potential energy surfaces (PESs) using neural networks (NNs). Although NNs do not provide the predictive variance as the Gaussian process regression does, we can alternatively minimize the negative of the squared difference surface (NSDS) given by two different NN models to actively locate the point where the PES is least confident. A batch of points in the minima of this NSDS can be iteratively added into the training set to improve the PES.

Effects of chironomid larvae and Limnodrilus hoffmeisteri bioturbation on the distribution and flux of chromium at the sediment-water interface.

The impacts of chironomid larvae and the tubificid worm Limnodrilus hoffmeisteri on the distribution and flux of the heavy metal chromium (Cr) across the sediment-water interface were investigated with a 21-day laboratory microcosm experiment. The two studied species feature different bioturbation modes involving bioirrigation and upward bioconveyance. The Cr concentrations in the overlying water and pore water were measured and compared using treatments with bioturbation by a single species and by combinations of both species and a treatment with no organisms.