In Materials Science and Engineering, we dissect the relationships that permeate and define material selection and design. Correspondingly, the observation, description, and ultimate prediction of causal connections between processing and emerging macroscopic properties stand at the heart of our activities. This exercise is deductive and traditionally bases all associations on physical parameters and their interpretation. For instance, we routinely investigate the effects of manufacturing variables on the resulting mechanical properties, such as hardness, toughness, or fatigue life. To that end, the microstructure is the subject of intense examination, as it is ultimately responsible for the observed emergent behavior. Many of the scientific or technical questions that we strive to answer boil down to quantitatively studying the—sometimes subtle—effects of processing on the microstructure in terms of known or hypothesized thermodynamic and kinetic phenomena. Then, we scrutinize the microstructure as the thermomechanical interaction of its microconstituents to explain observed or expected measurable macroscopic properties.
Incorporating Data Science and Informatics into the rigorous framework of Materials Science and Engineering is the quintessence of Integrated Computational Materials Engineering and Materials Informatics. In Materials Engineering, the challenge lies in developing information-based principles that emphasize physical meaning. In other words, technological applications set feasibility boundary conditions that cannot be circumvented. Data-based methods require careful adaptation and implementation to ensure applicability and relevance in application-oriented research.
In this contribution, we show one of our efforts toward increasing speed and reliability in repetitive microstructural analysis tasks through deep learning: A convolutional neural network image classifier embedded in a quantitative metallography and stereology workflow to characterize the solidification structures associated with inert gas powder atomization of high-alloy tool steels.