Confluence Detection for Transformations of Labelled Transition Systems

The development of complex component software systems can be made more manageable by first creating an abstract model and then incrementally adding details. Model transformation is an approach to add such details in a controlled way. In order for model transformation systems to be useful, it is crucial that they are confluent, i.e. that when applied on a given model, they will always produce a unique output model, independent of the order in which rules of the system are applied on the input. In this work, we consider Labelled Transition Systems (LTSs) to reason about the semantics of models, and LTS transformation systems to reason about model transformations. In related work, the problem of confluence detection has been investigated for general graph structures. We observe, however, that confluence can be detected more efficiently in special cases where the graphs have particular structural properties. In this paper, we present a number of observations to detect confluence of LTS transformation systems, and propose both a new confluence detection algorithm and a conflict resolution algorithm based on them.Comment: In Proceedings GaM 2015, arXiv:1504.0244

Analysing the Performance of GPU Hash Tables for State Space Exploration

In the past few years, General Purpose Graphics Processors (GPUs) have been used to significantly speed up numerous applications. One of the areas in which GPUs have recently led to a significant speed-up is model checking. In model checking, state spaces, i.e., large directed graphs, are explored to verify whether models satisfy desirable properties. GPUexplore is a GPU-based model checker that uses a hash table to efficiently keep track of already explored states. As a large number of states is discovered and stored during such an exploration, the hash table should be able to quickly handle many inserts and queries concurrently. In this paper, we experimentally compare two different hash tables optimised for the GPU, one being the GPUexplore hash table, and the other using Cuckoo hashing. We compare the performance of both hash tables using random and non-random data obtained from model checking experiments, to analyse the applicability of the two hash tables for state space exploration. We conclude that Cuckoo hashing is three times faster than GPUexplore hashing for random data, and that Cuckoo hashing is five to nine times faster for non-random data. This suggests great potential to further speed up GPUexplore in the near future.Comment: In Proceedings GaM 2017, arXiv:1712.0834

First-principles calculations of the crystal structure, electronic structure, and thermodynamic stability of Be(BH4)2

Alanates and boranates are intensively studied because of their potential use as hydrogen storage materials. In this paper, we present a first-principles study of the electronic structure and the energetics of beryllium boranate BeBH42. From total energy calculations, we show that—in contrast to the other boranates and alanates—hydrogen desorption directly to the elements is likely and is at least competitive with desorption to the elemental hydride BeH2. The formation enthalpy of BeBH42 is only −0.14 eV/H2 at T=0 K. This low value can be rationalized by the participation of all atoms in the covalent bonding, which is in contrast to the ionic bonding observed in other boranates. From calculations of thermodynamic properties at finite temperature, we estimate a decomposition temperature of 162 K at a pressure of 1 bar

Ab initio study on the effects of transition metal doping of Mg2NiH4

Mg2NiH4 is a promising hydrogen storage material with fast (de)hydrogenation kinetics. Its hydrogen desorption enthalpy, however, is too large for practical applications. In this paper we study the effects of transition metal doping by first-principles density functional theory calculations. We show that the hydrogen desorption enthalpy can be reduced by ~0.1 eV/H2 if one in eight Ni atoms is replaced by Cu or Fe. Replacing Ni by Co atoms, however, increases the hydrogen desorption enthalpy. We study the thermodynamic stability of the dopants in the hydrogenated and dehydrogenated phases. Doping with Co or Cu leads to marginally stable compounds, whereas doping with Fe leads to an unstable compound. The optical response of Mg2NiH4 is also substantially affected by doping. The optical gap in Mg2NiH4 is ~1.7 eV. Doping with Co, Fe or Cu leads to impurity bands that reduce the optical gap by up to 0.5 eV.Comment: 8 pages, 4 figure

Interactions of adsorbed CO2_2 on water ice at low temperatures

We present a computational study into the adsorption properties of CO$_2$ on amorphous and crystalline water surfaces under astrophysically relevant conditions. Water and carbon dioxide are two of the most dominant species in the icy mantles of interstellar dust grains and a thorough understanding of their solid phase interactions at low temperatures is crucial for understanding the structural evolution of the ices due to thermal segregation. In this paper, a new H$_2$O-CO$_2$ interaction potential is proposed and used to model the ballistic deposition of CO$_2$ layers on water ice surfaces, and to study the individual binding sites at low coverages. Contrary to recent experimental results, we do not observe CO$_2$ island formation on any type of water substrate. Additionally, density functional theory calculations are performed to assess the importance of induced electrostatic interactions.Comment: Accepted for publication in Physical Chemistry Chemical Physic

Atomistic models of hydrogenated amorphous silicon nitride from first principles

We present a theoretical study of hydrogenated amorphous silicon nitride (a-SiNx:H), with equal concentrations of Si and N atoms (x=1), for two considerably different densities (2.0 and 3.0 g/cm3). Densities and hydrogen concentration were chosen according to experimental data. Using first-principles molecular-dynamics within density-functional theory the models were generated by cooling from the liquid. Where both models have a short-range order resembling that of crystalline Si3N4 because of their different densities and hydrogen concentrations they show marked differences at longer length scales. The low-density nitride forms a percolating network of voids with the internal surfaces passivated by hydrogen. Although some voids are still present for the high-density nitride, this material has a much denser and uniform space filling. The structure factors reveal some tendency for the nonstoichiometric high-density nitride to phase separate into nitrogen rich and poor areas. For our slowest cooling rate (0.023 K/fs) we obtain models with a modest number of defect states, where the low (high) density nitride favors undercoordinated (overcoordinated) defects. Analysis of the structural defects and electronic density of states shows that there is no direct one-to-one correspondence between the structural defects and states in the gap. There are several structural defects that do not contribute to in-gap states and there are in-gap states that do only have little to no contributions from (atoms in) structural defects. Finally an estimation of the size and cooling rate effects on the amorphous network is reported.