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Adjacent Sink Strengths Used in Multiscale Kinetic Rate Equation Simulations of Defects and Impurities in Solids

Submitted:

05 March 2026

Posted:

09 March 2026

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Abstract
Kinetic Rate Equation (kRE) modeling is widely used to simulate defect and impurity evolution in solids over experimentally relevant time and length scales. However, conventional kRE formulations include only random-position sink strengths, which adequately describe trapping of defects created at random lattice sites but fail to capture the enhanced retrapping of defects released directly adjacent to traps during detrapping or dissociation events. This omission leads to systematic errors, including underestimated thermal desorption (TDS) peak temperatures and incorrect kinetic parameters when fitting to experimental data. In this work, we derive for the first time analytical expressions for the adjacent sink strength, including correction for finite impurity diffusion jump length. We provide a practical implementation strategy for integrating these expressions into kRE simulations. Comparisons with kinetic Monte Carlo (kMC) benchmarks demonstrate that adjacent sink strengths dominate the retrapping probability and are essential for reproducing the correct temperature dependence of TDS release peaks. Simulations that employ only random sink strengths can still be tuned to match TDS spectra; however, the resulting fitted trapping energies, detrapping frequencies, and diffusion parameters are often physically inconsistent. The adjacent sink strength formulation introduced here significantly improves the predictive capability of kRE modeling, enabling accurate multiscale simulations of defect and impurity behavior in materials. This framework also establishes a foundation for future extensions, including adjacent sink strengths associated with extended defects such as dislocations and grain boundaries, offering new opportunities to resolve persistent discrepancies between experimental and simulated trapping energetics.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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