Design of Novel Ni-based Superalloys

Abstract

Superalloys are unique high-temperature materials that display superior thermo-mechanical properties and excellent resistance to chemical degradation. These materials are widely used in hot-end applications, such as jet engines and industrial gas turbines.

Problem

There’s a constant need to develop better, stronger, more resistant materials while keeping the price comparable or even reducing it. The biggest challenge is to improve the multiple target properties, such as yield stress, oxidation resistance, thermal stability, etc., while simultaneously optimizing both composition and process parameters. That leads to thousands of possible experiments. The traditional “trial and error” approach is very time-consuming and inefficient.

Diverse data sources can be integrated within a unified Materials Knowledge Center. Both experimental results and theoretical calculations can be aggregated together allowing fast, permissions-based access to vast amounts of data.

Solution

Utilizing machine learning algorithms, the Predictive Co-Pilot identifies the most informative experiments, minimizes redundancy, and guides researchers to focus on the most promising candidates.

The Visual Analyzer enables rapid & interactive discovery of data-driven insights, allowing researchers to focus on the next experimental steps. In this case study, the yield strength of a superalloy was increased by optimizing its chemical composition and processing parameters.

MaterialsZone has significantly accelerated the design and discovery of novel superalloy materials and reduced by 70% experimental iterations.