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2199
2023
Solid state hydrogen storage: Decoding the path through machine learning
Published:
In this work we have developed HEART (HydrogEn storAge propeRty predicTor), a machine learning framework to discover new metal alloys for efficient hydrogen storage. Our framework includes two ML models that predict the HYdrogen Storage capaciTy as function of temperature (HYST) and the enTHalpy of hydride fORmation (THOR) of multi-component metal alloys. These models helps us to explore millions of possibilities and identify promising materials for hydrogen storage, accelerating the path towards a sustainable future. hashtag#renewableenergy hashtag#hydrogeneconomy hashtag#hydrogenstorage hashtag#machinelearning <!– Headings are cool ======
2015
Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
2014
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
2013
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.