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Updated: May 19, 2026
11:03
An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
Published on: December 4, 2017
Self-evolving atomistic kinetic Monte Carlo: fundamentals and applications
Haixuan Xu1, Yuri N Osetsky, Roger E Stoller
1Materials Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6114, USA. xuh1@ornl.gov
Summary
Self-evolving atomistic kinetic Monte Carlo (SEAKMC) simulates dynamic processes with atomistic detail over long timescales. This method accurately predicts diffusion correlation factors, offering an alternative to molecular dynamics (MD) for complex material simulations.
Area of Science:
- Materials Science
- Computational Physics
- Chemical Kinetics
Background:
- Atomistic simulations are crucial for understanding material dynamics.
- Molecular dynamics (MD) offers high fidelity but is limited by timescale.
- Longer timescale simulations are needed for many dynamic processes.
Purpose of the Study:
- Introduce and detail the self-evolving atomistic kinetic Monte Carlo (SEAKMC) framework.
- Demonstrate SEAKMC's capability for atomistic simulations on extended timescales.
- Validate SEAKMC against established methods like MD.
Main Methods:
- Development and application of the SEAKMC framework.
- Investigation of saddle point (SP) finding with the dimer method.
- Proposal and application of a criterion for simulation fidelity and accuracy.
- Comparative studies with molecular dynamics (MD) simulations.
Main Results:
- SEAKMC achieves atomistic fidelity comparable to MD but on much longer timescales.
- The dimer method's lowest energy saddle point (SP) prediction is accurate only for high-symmetry defects.
- SEAKMC accurately simulates interstitial and vacancy diffusion in bcc iron.
- SEAKMC successfully predicts the correlation factor for interstitial diffusion in the dumbbell configuration.
Conclusions:
- SEAKMC is a powerful technique for simulating dynamic processes at the atomistic level over extended timescales.
- The method provides a valuable alternative to MD for complex materials simulations.
- SEAKMC offers unique predictive capabilities and detailed technical insights into atomistic dynamics.
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