In the present study, we show that time-consuming manual tuning of parameters in the Rietveld method, one of the most frequently used crystal structure analysis methods in materials science, can be automated by considering the entire trial-and-error process as a blackbox optimisation problem. The automation is successfully achieved using Bayesian optimisation, which outperforms both a human expert and an expert-system type automation despite the absence of expertise. This approach stabilises the analysis quality by eliminating human-origin variance and bias, and can be applied to various analysis methods in other areas which also suffer from similar tiresome and unsystematic manual tuning of extrinsic parameters and human-origin variance and bias.

在本研究中，我们表明，Rietveld方法（材料科学中最常用的晶体结构分析方法之一）中耗时的手动参数调整可以通过将整个反复试验过程视为黑匣子来实现自动化优化问题。使用贝叶斯优化技术可以成功实现自动化，尽管缺乏专业知识，但贝叶斯优化技术的性能优于人类专家和专家系统类型的自动化。这种方法通过消除人为来源的方差和偏差来稳定分析质量，并且可以应用于其他领域的各种分析方法，这些方法也遭受外部参数和人源方差和偏差的类似繁琐且非系统的手动调整。