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Aug 28, 2022

Discovering materials for gas turbine engines through efficient predictive frameworks

Posted by in categories: robotics/AI, transportation

Gas turbines are widely used for power generation and aircraft propulsion. According to the laws of thermodynamics, the higher the temperature of an engine, the higher the efficiency. Because of these laws, there is an emerging interest in increasing turbines’ operating temperature.

A team of researchers from the Department of Materials Science and Engineering at Texas A&M University, in conjunction with researchers from Ames National Laboratory, have developed an artificial intelligence framework capable of predicting (HEAs) that can withstand extremely high temperature, oxidizing environments. This method could significantly reduce the time and costs of finding alloys by decreasing the number of experimental analyses required.

This research was recently published in Material Horizons.

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