Automated Extraction of Data from Binary Phase Diagrams for Discovery of Metallic Glasses

Abstract

We present a study on automated analysis of phase diagrams that attempts to lay the groundwork for a large-scale, indexable, digitized database of phases at different thermodynamic conditions and compositions for a wide variety of materials. For this work, we concentrate on approximately 80 thermodynamic phase diagrams of binary metallic alloy systems which give phase information of multi-component systems at varied temperatures and mixture ratios. We use image processing techniques to isolate phase boundaries and subsequently extract areas of the same phase. Simultaneously, document analysis techniques are employed to recognize and group the text used to label the phases; text present along the axes is identified so as to map image coordinates (x, y) to physical coordinates. Labels of unlabeled phases are inferred using standard rules. Once a phase diagram is thus digitized we are able to providethe phase of all materials present in our database at any given temperature and alloy mixture ratio. Using the digitized data, more complex queries may also be supported in the future. We evaluate our system by measuring the correctness of labeling of phase regions and obtain an accuracy of about 94%. Our work was then used to detect eutectic points and angles on the contour graphs which are important for some material design strategies, which aided in identifying 38 previously unexplored metallic glass forming compounds - an active topic of research in materials sciences.