FURI | Spring 2023

Hydrogen Embrittlement Prediction Using Machine Learning

With issues due to climate change rising, the global market is shifting to environmentally friendly energy sources. Hydrogen is a prime candidate because it does not give out any harmful emissions. When hydrogen is stored in metallic containers, the hydrogen molecules diffuse into the material, and this makes it more brittle by propagating cracks. This poses a great challenge to tackle as it needs to be stored easily for it to be used widely to fight climate change. With time, machine learning has paved its way into this field and various algorithms are being tested to predict hydrogen embrittlement, so that related issues can be avoided.