National Center for Materials Service Safety , University of Science and Technology Beijing , Beijing 100083 , China.
Materials Genome Initiative Center , Shanghai Jiao Tong University , Shanghai 200240 , China.
ACS Comb Sci. 2019 Dec 9;21(12):833-842. doi: 10.1021/acscombsci.9b00149. Epub 2019 Nov 12.
The combinatorial materials chip approach is vastly superior to the conventional one that characterizes one sample at a time in the efficiency of composition-phase map construction. However, the resolution of its high-throughput characterization and the correct rate of automated composition-phase mapping are often affected by inherent experimental limitations and imperfect automated analyses, respectively. Therefore, effective data preprocessing and refined automated analysis methods are required to automatically process huge amounts of experiment data to score a higher correct rate. In this work, the pixel-by-pixel structural and compositional characterization of the Fe-Cr-Ni combinatorial materials chip annealed at 750 °C was performed by microbeam X-ray at a synchrotron light source and by electron probe microanalysis, respectively. The severe baseline drift and system noise in the X-ray diffraction patterns were successfully eliminated by the three-step automated preprocessing (baseline drift removal, noise elimination, and baseline correction) proposed, which was beneficial to the subsequent quantitative analysis of the patterns. Through the injection of human experience, hierarchy clustering analyses, based on three dissimilarity measures (the cosine, Pearson correlation coefficient, and Jenson-Shannon divergence), were further accelerated by the simplified vectorization of the preprocessed X-ray diffraction patterns. As a result, a correct rate of 91.15% was reached for the whole map built automatically in comparison with the one constructed manually, which confirmed that the present data processing could assist humans to improve and expedite the processing of X-ray diffraction patterns and was feasible for composition-phase mapping. The constructed maps were generally consistent with the corresponding isothermal section of the Fe-Cr-Ni ternary alloy system in the ASM Alloy Phase Diagram Database except the inexistence of the σ phase under insufficient annealing.
组合材料芯片方法在构建成分-相图的效率方面大大优于传统的每次对一个样品进行特征化的方法。然而，其高通量表征的分辨率和自动成分-相映射的正确率通常分别受到固有实验限制和不完善的自动分析的影响。因此，需要有效的数据预处理和改进的自动化分析方法，以便自动处理大量实验数据，从而提高正确率。在这项工作中，通过同步加速器光源的微束 X 射线和电子探针微分析，分别对在 750°C 下退火的 Fe-Cr-Ni 组合材料芯片进行了逐像素的结构和组成特性分析。通过提出的三步自动化预处理（基线漂移去除、噪声消除和基线校正）成功消除了 X 射线衍射图谱中的严重基线漂移和系统噪声，这有利于后续对图谱的定量分析。通过注入人类经验，基于三种不相似性度量（余弦、皮尔逊相关系数和杰恩-香农散度）的层次聚类分析通过预处理 X 射线衍射图谱的简化矢量化得到了进一步加速。结果，与手动构建的图谱相比，自动构建的整个图谱的正确率达到了 91.15%，这证实了目前的数据处理可以帮助人类改进和加速 X 射线衍射图谱的处理，并且对于成分-相映射是可行的。构建的图谱与 ASM 合金相图数据库中 Fe-Cr-Ni 三元合金系统的相应等温截面基本一致，除了在退火不足的情况下不存在 σ 相。
