"Exploring the Compositional Space of Materials via Classical and Quantum Computers"
Feb 9, 2022 Schedule:
- Tea Time - Virtual ( Zoom)
- 03:00 to 03:30 PM Eastern Time (US and Canada)
- Colloquium - F2F ( 499 DSL) / Virtual ( Zoom)
- 03:30 to 04:30 PM Eastern Time (US and Canada)
Computational materials design often starts with selecting elements and determining their concentrations. This process is tantamount to exploring the vast compositional space, which is a daunting task if it is performed by the traditional trial-and-error manner. In this talk, I will use multi-principal component alloys (also known as high-entropy alloys) as an example to show our recent results of using classical and quantum computers to explore the compositional space of these alloys. Specifically, my group trained a classical deep neural network to achieve the goal that given a certain combination of elements and concentrations, the trained model is capable of efficiently predicting the resulting atomic arrangement. I will also show our recent efforts of using quantum computers to accomplish the same goal.