Mechanisms of Auger-induced chemistry derived from wave packet dynamics

To understand how core ionization and subsequent Auger decay lead to bond breaking in large systems, we simulate the wave packet dynamics of electrons in the hydrogenated diamond nanoparticle C_(197)H_(112). We find that surface core ionizations cause emission of carbon fragments and protons through a direct Auger mechanism, whereas deeper core ionizations cause hydrides to be emitted from the surface via remote heating, consistent with results from photon-stimulated desorption experiments [Hoffman A, Laikhtman A, (2006) J Phys Condens Mater 18:S1517–S1546]. This demonstrates that it is feasible to study the chemistry of highly excited large-scale systems using simulation and analysis tools comparable in simplicity to those used for classical molecular dynamics

Task decomposition using pattern distributor

In this paper, we propose a new task decomposition method for multilayered feedforward neural networks, namely Task Decomposition with Pattern Distributor in order to shorten the training time and improve the generalization accuracy of a network under training. This new method uses the combination of modules (small-size feedforward network) in parallel and series, to produce the overall solution for a complex problem. Based on a “divide-and-conquer” technique, the original problem is decomposed into several simpler sub-problems by a pattern distributor module in the network, where each sub-problem is composed of the whole input vector and a fraction of the output vector of the original problem. These sub-problems are then solved by the corresponding groups of modules, where each group of modules is connected in series with the pattern distributor module and the modules in each group are connected in parallel. The design details and implementation of this new method are introduced in this paper. Several benchmark classification problems are used to test this new method. The analysis and experimental results show that this new method could reduce training time and improve generalization accuracy

Excited Electron Dynamics Modeling of Warm Dense Matter

We present a model (the electron force field, or eFF) based on a simplified solution to the time-dependent Schrödinger equation that with a single approximate potential between nuclei and electrons correctly describes many phases relevant for warm dense hydrogen. Over a temperature range of 0 to 100 000 K and densities up to 1 g/cm^3, we find excellent agreement with experimental, path integral Monte Carlo, and linear mixing equations of state, as well as single-shock Hugoniot curves from shock compression experiments. In principle eFF should be applicable to other warm dense systems as well

An interactive multi-block grid generation system

A grid generation procedure combining interactive and batch grid generation programs was put together to generate multi-block grids for complex aircraft configurations. The interactive section provides the tools for 3D geometry manipulation, surface grid extraction, boundary domain construction for 3D volume grid generation, and block-block relationships and boundary conditions for flow solvers. The procedure improves the flexibility and quality of grid generation to meet the design/analysis requirements