Dataset on statistical convergence of generated microstructures in diffusion studies

This dataset provides measurements of effective diffusion coefficients in polycrystalline networks with different grain sizes and attribution methods. Four attribution methods—random, constrained triple junction, closed grains, and hybrid—were applied to networks with grain sizes of 7 μm and 0.7 μm. For each combination, 50 simulations were performed to obtain stable average effective diffusion coefficients and their standard deviations. The dataset includes tables summarizing the average diffusion coefficients and standard deviations for all attribution methods and grain sizes. These data can be reused to validate diffusion models, optimize computational simulations, and support studies of grain boundary effects on diffusion in polycrystalline materials.

本数据集提供了不同晶粒尺寸的多晶网络的有效扩散系数测量结果，同时涵盖四类归因方法的应用数据。四类归因方法分别为随机法、约束晶界三重结法、闭合晶粒法与混合法，均应用于晶粒尺寸为7 μm和0.7 μm的多晶网络。针对每一种归因方法与晶粒尺寸的组合，均开展了50次模拟，以获取稳定的平均有效扩散系数及其标准差。本数据集包含汇总了所有归因方法与晶粒尺寸组合下的平均扩散系数及标准差的表格。这些数据可用于验证扩散模型、优化计算模拟，并支撑多晶材料中晶界效应对扩散过程影响的相关研究。