Influence of polarizability on metal oxide properties studied by molecular dynamics simulations

We have studied the dependence of metal oxide properties in molecular dynamics (MD) simulations on the polarizability of oxygen ions. We present studies of both liquid and crystalline structures of silica (SiO2), magnesia (MgO) and alumina (Al2O3). For each of the three oxides, two separately optimized sets of force fields were used: (i) Long-range Coulomb interactions between oxide and metal ions combined with a short-range pair potential. (ii) Extension of force field (i) by adding polarizability to the oxygen ions. We show that while an effective potential of type (i) without polarizable oxygen ions can describe radial distributions and lattice constants reasonably well, potentials of type (ii) are required to obtain correct values for bond angles and the equation of state. The importance of polarizability for metal oxide properties decreases with increasing temperature.Comment: 8 pages, 7 figure

Understanding long-time vacancy aggregation in iron: a kinetic activation-relaxation technique study

Vacancy diffusion and clustering processes in body-centered-cubic (bcc) Fe are studied using the kinetic activation-relaxation technique (k-ART), an off-lattice kinetic Monte Carlo method with on-the-fly catalog building capabilities. For monovacancies and divacancies, k-ART recovers previously published results while clustering in a 50-vacancy simulation box agrees with experimental estimates. Applying k-ART to the study of clustering pathways for systems containing from one to six vacancies, we find a rich set of diffusion mechanisms. In particular, we show that the path followed to reach a hexavacancy cluster influences greatly the associated mean-square displacement. Aggregation in a 50-vacancy box also shows a notable dispersion in relaxation time associated with effective barriers varying from 0.84 to 1.1 eV depending on the exact pathway selected. We isolate the effects of long-range elastic interactions between defects by comparing to simulations where those effects are deliberately suppressed. This allows us to demonstrate that in bcc Fe, suppressing long-range interactions mainly influences kinetics in the first 0.3 ms, slowing down quick energy release cascades seen more frequently in full simulations, whereas long-term behavior and final state are not significantly affected.Comment: 11 pages, 12 figures. Updated to post-review manuscrip

A data-driven method for Higgs boson analyses in di-τ final states for the LHC Run II and beyond

Das τ-Embedding ist eine datenbasierte Methode zur Abschätzung des Beitrags von Prozessen mit zwei τ-Leptonen im Ereignis. Die Methode verwendet einen ereignisbasier- ten Ansatz, bei dem zwei rekonstruierte Myonen in den Daten ausgewählt werden, die durch zwei simulierte τ-Leptonenzerfälle ersetzt werden. Das daraus resultierende Ereignis vereint die simulierten τ-Leptonenzerfälle mit einem sonst unveränderten Ereignis. Das τ-Embedding führt zu einer verbesserten Beschreibung der Eigenschaften von Jets und von Pile-up-Kollisionen. Es ist die wichtigste Abschätzungsmethode für Untergründe mit zwei τ-Leptonen im Endzustand innerhalb der CMS-Kollaboration und wurde in den letzten Jahren in zahlreichen Higgs-Boson-Analysen in ττ-Endzuständen angewendet. In dieser Arbeit wird die neueste Implementierung der Methode beschrieben. In einem umfassenden, Analysebeispiel wird die Methode mit einem Modell verglichen, das auf vollständig simulierten Prozessen basiert. Mehr als 8 Millionen CPU-Stunden wurden auf- gewendet, um die neue Implementierung von τ-Embedding Ergebnisse für die LHC Run II Analysen zu erzeugen. Die vorgestellten Studien legen den Grundstein für die Verwendung von τ-Embedding in mehreren geplanten Higgs-Boson-Analysen in ττ-Endzuständen auf den kombinierten Datensätzen von Run II und III, die eines der wichtigsten Ergebnisse des LHC-Phase-1-Physikprogramms darstellen werden

Analyzing the Growing Islamic Radicalization in France

Islamic radicalization in European countries is becoming more and more prevalent, as evidenced by the number of recent attacks by Muslims in Europe. I argue that the social, religious, and psychological environment in France creates a unique opportunity for Islamic radicalization, particularly through social media and in prisons. After defining radicalization and explaining two radicalization processes as well as different types of radicals, I analyze the specific factors present in France that contribute to this radicalization. I use case study analysis to examine several French citizens who radicalized, either online or in prison, in order to show how the recruiter exacerbated the situation in France. Additionally, I evaluate primary sources from the Islamic State and the Levant, in order to show how it capitalizes on certain aspects of French society, such as the discriminatory laws banning the burka. I also apply both theories of radicalization, and analyze which one matches the processes found in the case studies and primary sources. My findings support my hypothesis that France is a unique case where Islamic radicalization is more easily achieved, and that the presence of a mentor is crucial in the radicalization process

Populatieontwikkeling wortelknobbelaaltjes in aardappel : Meloidogyne chitwoodi en M. fallax

PPO onderzocht de levenscyclus en ontwikkeling van de wortelknobbelaaltjes Meloidogyne chitwoodi (maïswortelknobbelaaltje) en M. fallax (bedrieglijk maïswortelknobbelaaltje) op aardappel, om vast te stellen hoeveel generaties van deze aaltjessoorten onder Nederlandse omstandigheden per groeiseizoen mogelijk zijn en welke generatie de nieuw gevormde knollen daadwerkelijk infecteert. Er worden minimaal twee generaties gevormd en de tweede generatie is verantwoordelijk voor de schade aan de knollen. Bestrijdingsstrategieën die uitgaan van het voorkomen van de tweede generatie juvenielen bieden de beste mogelijkhede

Uncertainty quantification for classical effective potentials: an extension to potfit

Effective potentials are an essential ingredient of classical molecular dynamics (MD) simulations. Little is understood of the consequences of representing the complex energy landscape of an atomic configuration by an effective potential or force field containing considerably fewer parameters. The probabilistic potential ensemble method has been implemented in the potfit force matching code. This introduces uncertainty quantification into the interatomic potential generation process. Uncertainties in the effective potential are propagated through MD to obtain uncertainties in quantities of interest, which are a measure of the confidence in the model predictions. We demonstrate the technique using three potentials for nickel: two simple pair potentials, Lennard-Jones and Morse, and a local density dependent embedded atom method (EAM) potential. A potential ensemble fit to density functional theory (DFT) reference data is constructed for each potential to calculate the uncertainties in lattice constants, elastic constants and thermal expansion. We quantitatively illustrate the cases of poor model selection and fit, highlighted by the uncertainties in the quantities calculated. This shows that our method can capture the effects of the error incurred in quantities of interest resulting from the potential generation process without resorting to comparison with experiment or DFT, which is an essential part to assess the predictive power of MD simulations.Comment: 10 pages, 3 figure

Reducing the loss of genetic diversity associated with assisted colonization -like introductions of animals

Peer reviewe

A Hybrid Decomposition Parallel Implementation of the Car-Parrinello Method

We have developed a flexible hybrid decomposition parallel implementation of the first-principles molecular dynamics algorithm of Car and Parrinello. The code allows the problem to be decomposed either spatially, over the electronic orbitals, or any combination of the two. Performance statistics for 32, 64, 128 and 512 Si atom runs on the Touchstone Delta and Intel Paragon parallel supercomputers and comparison with the performance of an optimized code running the smaller systems on the Cray Y-MP and C90 are presented.Comment: Accepted by Computer Physics Communications, latex, 34 pages without figures, 15 figures available in PostScript form via WWW at http://www-theory.chem.washington.edu/~wiggs/hyb_figures.htm

Dislocation dynamics in Ni-based superalloys: Parameterising dislocation trajectories from atomistic simulations

Nanoscale precipitates in the microstructure of nickel-based superalloys hinder dislocation motion, which results in an extraordinary strengthening effect at elevated temperatures. We used molecular dynamics (MD) with classical effective potential to observe the movement of an $\frac{a}{2}\langle110\rangle\{111\}$ edge dislocation under shear in pure Ni, which represents the Ni solid solution matrix, and extracted the locations of the dislocations. We show how a Differential Evolution Monte Carlo (DE-MC) analysis is an effective way to find the parameters of an equation of motion for the dislocation lines with quantified uncertainties. The parameters of interest were the effective mass, drag coefficient, and force experienced by the dislocation. The marginal parameter and joint posterior distributions were estimated from the accepted samples produced by the DE-MC algorithm. The equation of motion and parameter distributions were used to predict the dislocation positions and velocities at the simulation timesteps, and the mean fit was found to match the MD trajectories with a root mean square error (RMSE) of \SI{0.2}{\nano\metre}. We also discuss how the selected model can be extended to account for the presence of multiple dislocations as well as dislocation-precipitate interactions. This work serves as the first step towards building a predictive surrogate model that describes the deformation behaviour of Ni-based superalloys.Comment: 19 pages, 7 figure