Computational Alloy Design and Discovery

External Member



Engineering alloys are a blend of elements, often a combination of more than 10 deliberate alloying additions. As a consequence, the number of possible alloys that can be produced is (empirically speaking) nearly infinite……..    For example, if one takes 30 elements, and uses factorial analysis, that means a possible 2.6525286 x 1032 alloys are possible…….. Needless to say, materials engineers have barely scratched the surface of the possible alloys that may be produced. This means a future full of wonderful materials – lies in the waiting. 

The project herein therefore relies on the use of computational methods to aid in the prediction of alloy compositions that are potentially useful for future metallic alloys.  Future alloys will need to be designed for specific properties, using the following approachee (the selection of whiich will be up to student preference or project reequirement).

1) Machine learning, to assist in the development of A.I.


2) High throughput digital screeing 


3) The use of thermodynamic databases

The project will involve some coding, and the use of machine learning / artificial intelligence tools. Students eager to explore data science (and who are not afraid to learn to code if they cannot code already) are encouraged to apply. 


Some experience in coding and an interest in machine learning is essential.

Updated:  10 August 2021/Responsible Officer:  Dean, CECS/Page Contact:  CECS Marketing