Sampling in the multicanonical ensemble: Small He clusters in W

We carry out generalized-ensemble molecular dynamics simulations of the formation of small Helium (He) clusters in bulk Tungsten (W), a process of practical relevance for fusion energy production. We calculate formation free energies of small Helium clusters at temperatures up to the melting point of W, encompassing the whole range of interest for fusion-energy production. From this, parameters like cluster break-up or formation rates can be calculated, which help to refine models of microstructure evolution in He-irradiated Tungsten.Comment: 27th Annual CSP Workshop on Recent Developments in Computer Simulation Studies in Condensed Matter Physics, Athens, GA, 201

Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification

A massively parallel method to build large transition rate matrices from temperature accelerated molecular dynamics trajectories is presented. Bayesian Markov model analysis is used to estimate the expected residence time in the known state space, providing crucial uncertainty quantification for higher scale simulation schemes such as kinetic Monte Carlo or cluster dynamics. The estimators are additionally used to optimize where exploration is performed and the degree of temperature ac- celeration on the fly, giving an autonomous, optimal procedure to explore the state space of complex systems. The method is tested against exactly solvable models and used to explore the dynamics of C15 interstitial defects in iron. Our uncertainty quantification scheme allows for accurate modeling of the evolution of these defects over timescales of several seconds.Comment: 14 pages, 7 figure

Employee perceptions on service quality at a selected outsourcing company in Cape Town

Thesis (MTech (Business Administration))--Cape Peninsula University of Technology, 2019Over the last decade, business process outsourcing (BPO) has become increasingly important in the South African context. For economic and strategic reasons, organisations have embraced an outsourcing strategy as one of their core activities in order to be competitive in the business arena. On this matter, the standard of services delivered by BPOs is crucial to achieve customer satisfaction. However, the lack of effective quality management practices, which impact on service delivery negatively, ultimately paves the way for customer dissatisfaction with service quality in BPOs. This issue needs to be considered carefully by BPOs. Thus, this study has investigated employee perceptions in relation to the key measurements for service quality, namely reliability, responsiveness, assurance, empathy and tangibles through the SERVQUAL model to measure the quality of service delivery at a BPO in Cape Town, South Africa. A quantitative research method was applied and data were collected through a semi-structured survey questionnaire from the group of employees (n=188) at the selected BPO in Cape Town. The statistical software program SPSS Version 25 and Microsoft Excel were used for data analysis. Descriptive statistical results were generated as well as the validity and reliability of the dataset determined. The research findings revealed that the key factors to which particular attention needs to be given are reliability, responsiveness, assurance and empathy. It is revealed that it is imperative for the BPO to intensify continual training and skills development for their employees. Given the findings of these key factors as focus areas for good practice, this study has drawn special attention to the selected BPO and other BPOs in the South African context to advance their service quality to maintain their services up to standard and to remain competitive. The research could benefit BPOs in South Africa and Africa in general as more and more companies are outsourcing their services on the continent

Automated calculation and convergence of defect transport tensors

Defect transport is a key process in materials science and catalysis, but as migration mechanisms are often too complex to enumerate a priori, calculation of transport tensors typically have no measure of convergence and require significant end user intervention. These two bottlenecks prevent high-throughput implementations essential to propagate model-form uncertainty from interatomic interactions to predictive simulations. In order to address these issues, we extend a massively parallel accelerated sampling scheme, autonomously controlled by Bayesian estimators of statewise sampling completeness, to build atomistic kinetic Monte Carlo models on a state space irreducible under exchange and space group symmetries. Focusing on isolated defects, we derive analytic expressions for defect transport tensors and provide a convergence metric by calculating the Kullback-Leiber divergence across the ensemble of diffusion processes consistent with the sampling uncertainty. The autonomy and efficacy of the method is demonstrated on surface trimers in tungsten and hexa-interstitials in magnesium oxide, both of which exhibit complex, correlated migration mechanisms

Arbitrarily accurate, nonparametric coarse graining with Markov renewal processes and the Mori-Zwanzig formulation

Stochastic dynamics, such as molecular dynamics, are important in many scientific applications. However, accessing macroscopic dynamical behavior often requires inordinately long simulation times. Coarse graining is a popular technique for addessing this problem. While coarse graining provides computational tractability, it comes at the cost of accuracy. This article shows how to eliminate coarse-graining error using two key ideas. First, we represent coarse-grained dynamics as a Markov renewal process. Second, we outline a data-driven, non-parametric Mori-Zwanzig approach for computing jump times of the renewal process. Numerical tests on a small protein illustrate the method.Comment: 8 pages, 6 figure

Formation of field-induced breakdown precursors on metallic electrode surfaces

Understanding the underlying factors responsible for higher-than-anticipated local field enhancements that trigger vacuum breakdown on pristine metal surfaces is crucial for the development of devices capable of withstanding intense operational fields. In this study, we investigate the behavior of nominally flat copper electrode surfaces exposed to electric fields of hundreds of MV/m. Our novel approach considers curvature-driven diffusion processes to elucidate the formation of sharp breakdown precursors. To do so, we develop a mesoscale finite element model that accounts for driving forces arising from both electrostatic and surface-tension-induced contributions to the free energy. Our findings reveal a dual influence: surface tension tends to mitigate local curvature, while the electric field drives mass transport toward regions of high local field density. This phenomenon triggers the growth of sharper protrusions, ultimately leading to a rapid enhancement of local fields and, consequently, system instability. Furthermore, we delineate supercritical and subcritical regimes across a range of initial surface roughness. Our numerical results align closely with experimentally reported data, predicting critical precursor formation fields in the range of 200 MV/m to 500 MV/m.Comment: 8 pages, 5 figure