Reduced-order kinetic Monte Carlo model to simulate water diffusion in biodegradable polymers

Abstract A viable fusion power station is reliant on the development of plasma facing materials that can withstand the combined effects of high temperature operation and high neutron doses. In this study we focus on W, the most promising candidate material. Re is the primary transmutation product and has been shown to induce embrittlement through cluster formation and precipitation below its predicted solubility limit in W. We investigate the mechanism behind this using a kinetic Monte Carlo model, implemented into Stochastic Parallel PARticle Kinetic Simulator (SPPARKS) code and parameterised with a pairwise energy model for both interstitial and vacancy type defects. By introducing point defect sinks into our simulation cell, we observe the formation of Re rich clusters which have a concentration similar to that observed in ion irradiation experiments. We also compliment our computational work with atom probe tomography (APT) of ion implanted, model W-Re alloys. The segregation of Re to grain boundaries is observed in both our APT and KMC simulations. Graphical abstract

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An Experimental Validation of a 3D Kinetic, Monte Carlo Model for Microstructural Evolution during Sintering

Advances in Science and Technology ◽

10.4028/www.scientific.net/ast.45.522 ◽

2006 ◽

Vol 45 ◽

pp. 522-529 ◽

Cited By ~ 2

Author(s):

Veena Tikare ◽

Michael V. Braginsky ◽

Didier Bouvard ◽

Alexander Vagnon

Keyword(s):

Monte Carlo ◽

Microstructural Evolution ◽

Copper Powder ◽

Experimental Validation ◽

Kinetic Monte Carlo ◽

Monte Carlo Model ◽

Statistical Mechanical Model ◽

Powder Particles ◽

Statistical Mechanical ◽

Curvature Driven

An experimental validation of a 3D kinetic, Monte Carlo model for simulation of microstructural evolution during solid state sintering will be presented. The model – a statistical mechanical model, which can simulate curvature-driven grain growth, pore migration, and vacancy formation, diffusion and annihilation – is validated by comparing microstructural evolution obtained experimentally for a copper powder compact. The 3D microstructural evolution of copper powder particles sintering was imaged in-situ by microtomography. The images show particles with internal porosity percolating through the particles. Microstructural features – e.g., neck formation and growth – from the experimental images as well as the overall densification rates are compared to the simulations.

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Self-learning kinetic Monte Carlo model for arbitrary surface orientations

MRS Proceedings ◽

10.1557/opl.2013.691 ◽

2013 ◽

Vol 1559 ◽

Cited By ~ 1

Author(s):

Andreas Latz ◽

Lothar Brendel ◽

Dietrich E. Wolf

Keyword(s):

Monte Carlo ◽

Specific Surface ◽

Kinetic Monte Carlo ◽

Monte Carlo Model ◽

Three Dimensional ◽

The Self ◽

Transition Rates ◽

Local Orientation ◽

Realistic Potential ◽

Self Learning

ABSTRACTWhile the self-learning kinetic Monte Carlo (SLKMC) method enables the calculation of transition rates from a realistic potential, implementations of it were usually limited to one specific surface orientation. An example is the fcc (111) surface in Latz et al. 2012, J. Phys.: Condens. Matter 24, 485005. This work provides an extension by means of detecting the local orientation, and thus allows for the accurate simulation of arbitrarily shaped surfaces. We applied the model to the diffusion of Ag monolayer islands and voids on a Ag(111) and Ag(001) surface, as well as the relaxation of a three-dimensional spherical particle.

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