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NSCC NewsBytes April 2021
Traditional pathways in the development of new alloys often occur through several empirical observations and optimising the composition and fabrication methodology. Such conventional methods may take up to 20 years of work before the alloy is ready for deployment.
A team of researchers at the Institute of High Performance Computing (IHPC), A*STAR are leveraging NSCC’s supercomputing resources to perform high-throughput computations and experiments coupled with machine learning techniques. This helps accelerate the process of alloy development to just 3 years in the case of fabricating a novel high entropy alloy (HEA).
To achieve this, IHPC is leveraging various domain expertise that covers first-principles simulations, molecular dynamics, and computational thermodynamics to generate a database that is used to train the machine learning model. Such a database holds a huge amount of data and requires large-scale, highperformance computing resources to analyse.
By using NSCC’s resources, the team has been able to generate more than 1 million data points that have been used to train machine learning models that predict the microstructural phase of an HEA for a given composition.
