Building a kinetic Monte Carlo model with a chosen accuracy

Area of Science:

• Computational Materials Science
• Chemical Physics
• Materials Modeling

Background:

• The kinetic Monte Carlo (KMC) method is crucial for simulating materials at large length and time scales.
• KMC model accuracy is compromised by missing atomic processes, leading to erroneous dynamics.
• Previous work established an error measure for KMC, dependent on estimating the rate of missing processes.

Purpose of the Study:

• To present an improved procedure for estimating the missing rate in KMC models.
• To enhance the accuracy of KMC error quantification.
• To determine the operational time limit of a KMC model before significant dynamic errors accumulate.

Main Methods:

• Development of a novel procedure for estimating the rates of atomic processes omitted from KMC simulations.
• Quantitative comparison of the new estimation procedure against a prior approach.
• Analysis of KMC model validity over time based on the refined error measure.

Main Results:

• The improved procedure yields missing rate estimates within an order of magnitude of the true values.
• This represents a significant improvement over the previous method, which overestimated rates by orders of magnitude.
• The study identifies the time duration for which KMC models remain reliable before reaching a maximum acceptable error.

Conclusions:

• The enhanced missing rate estimation significantly improves the accuracy of KMC error assessment.
• This advancement allows for more reliable application of KMC simulations in materials science.
• The findings provide critical insights into the temporal limitations of KMC models.