Numerical exploration of plastic deformation mechanisms of copper nanowires with surface defects

Based on the molecular dynamics simulation, plastic deformation mechanisms associated with the zigzag stress curves in perfect and surface defected copper nanowires under uniaxial tension are studied. In our previous study, it has found that the surface defect exerts larger influence than the centro-plane defect, and the 45o surface defect appears as the most influential surface defect. Hence, in this paper, the nanowire with a 45o surface defect is chosen to investigate the defect’s effect to the plastic deformation mechanism of nanowires. We find that during the plastic deformation of both perfect and defected nanowires, decrease regions of the stress curve are accompanied with stacking faults generation and migration activities, but during stress increase, the structure of the nanowire appears almost unchanged. We also observe that surface defects have obvious influence on the nanowire’s plastic deformation mechanisms. In particular, only two sets of slip planes are found to be active and twins are also observed in the defected nanowire.

Accelerated leap methods for simulating discrete stochastic chemical kinetics

Biologists are increasingly conscious of the critical role that noise plays in cellular functions such as genetic regulation, often in connection with fluctuations in small numbers of key regulatory molecules. This has inspired the development of models that capture this fundamentally discrete and stochastic nature of cellular biology - most notably the Gillespie stochastic simulation algorithm (SSA). The SSA simulates a temporally homogeneous, discrete-state, continuous-time Markov process, and of course the corresponding probabilities and numbers of each molecular species must all remain positive. While accurately serving this purpose, the SSA can be computationally inefficient due to very small time stepping so faster approximations such as the Poisson and Binomial τ-leap methods have been suggested. This work places these leap methods in the context of numerical methods for the solution of stochastic differential equations (SDEs) driven by Poisson noise. This allows analogues of Euler-Maruyuma, Milstein and even higher order methods to be developed through the Itô-Taylor expansions as well as similar derivative-free Runge-Kutta approaches. Numerical results demonstrate that these novel methods compare favourably with existing techniques for simulating biochemical reactions by more accurately capturing crucial properties such as the mean and variance than existing methods.

Supplement : Efficient weak second-order stochastic Runge-Kutta methods for non-commutative Stratonvich stochastic differential equations

This paper gives a modification of a class of stochastic Runge–Kutta methods proposed in a paper by Komori (2007). The slight modification can reduce the computational costs of the methods significantly.