New Machine Learning Algorithm Can Autonomously Find New Materials

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There is an urgent need for use of advanced materials in this era. Materials with anti-oxidation properties, and high tolerance find use in industries. Advanced materials are providing solutions to areas like human welfare, security, and clean energy. It has thus become essential to use a particular substance for a specific application.

A group of scientists at Texas A&M deployed the use of artificial intelligence (AI) in discovery of novel materials. An algorithm tests and explores new materials optimally, to fit a given set of conditions. The autonomous system adapts to find the best machine learning (ML) models to find the most efficient material for an application.

 Biomedicine to Find Application Using Algorithm

The Airforce Office of Scientific Research and the National Science Foundation funded this study. The team hopes that the use of this algorithm will reduce operational time and cost. The algorithm also finds application in other fields-such as biomedicine. Cost of clinical trials reduces as this solution can find effective therapeutics.

The experiment took place in a closed loop computational platform. MAX-phases were tested on the basis of their quantum mechanical properties, temperature tolerance, and resistance to oxidation. The material underwent tests for application as jet engine turbine blades.

Older algorithms used predefined models, but this solution is a step forward. This algorithm autonomously decided the most appropriate model from a set. This reduces the number of steps and resource required in the entire process.

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