High-Throughput Nanoindentation Mapping of Additively Manufactured T91 Steel

This work aims to adapt nanoindentation mapping combined with a k-means algorithm as a high-throughput technique to study the nano-scale spatial changes in mechanical properties for a heterogeneous material. This technique can also classify the individual data points based on their properties. Hundreds to thousands of indents were performed on additively manufactured T91 at room temperature, 300 degrees C, 400 degrees C, and 500 degrees C across a square area with a side length of 120 mu m to 400 mu m. From this data, the hardness and reduced modulus at each point could be calculated and mapped. Using k-means clustering, we were able to arrange the data into three or four clusters corresponding roughly to the ferritic and martensitic phases as well as one or two intermediate clusters sampling both the phases. The hardness of these two phases appears to be quite stable as a function of temperature. Nanoindentation mapping and the k-means algorithm can therefore be used to rapidly assess the feasibility of heterogeneous materials under extreme conditions, such as nuclear reactor steels.

Automated summary

This work combines nanoindentation mapping with k-means algorithm to develop a high-throughput technique for studying the nano-scale spatial changes in mechanical properties of heterogeneous materials. It also allows for classification of data points based on their properties. This technique is important for assessing the feasibility of special materials under extreme conditions.