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Mechanical Control of Relaxation Using Intact Cardiac Trabeculae

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Kinetic activation-relaxation technique.

Laurent Karim Béland¹, Peter Brommer, Fedwa El-Mellouhi

¹Département de Physique and Regroupement Québécois sur les Matériaux de Pointe, Université de Montréal, C.P. 6128, Succursale Centre-Ville, Montréal, Québec, Canada H3C 3J7. laurent.karim.beland@umontreal.ca

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|December 21, 2011

Summary

We introduce kinetic activation-relaxation (k-ART), a novel self-learning kinetic Monte Carlo method for complex materials. This advanced algorithm efficiently models atomic behavior in off-lattice positions and during deformations.

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Area of Science:

Computational Materials Science
Atomistic Simulations
Materials Modeling

Background:

Standard kinetic Monte Carlo (KMC) methods struggle with complex materials.
Off-lattice atomic positions and elastic deformations pose challenges for traditional KMC.

Purpose of the Study:

To present a detailed description of the kinetic activation-relaxation technique (k-ART).
To demonstrate the general applicability of k-ART to challenging materials systems.

Main Methods:

k-ART combines topological classification with ART nouveau for unbiased transition state sampling.
It is an off-lattice, self-learning kinetic Monte Carlo (KMC) algorithm.
Features on-the-fly event search for efficient simulations.

Main Results:

k-ART successfully models self-defect annihilation in crystalline silicon (c-Si).
It accurately simulates self-interstitial diffusion in iron (Fe).
The algorithm effectively handles structural relaxation in amorphous silicon (a-Si).

Conclusions:

k-ART is a versatile and powerful tool for simulating complex materials.
The method overcomes limitations of standard KMC approaches.
It enables accurate atomistic simulations for systems with off-lattice atoms and deformations.