Computational Scanning of lmidazolium-based Anion Exchange Membrane materials

One promising approach for the advancement of both fuel cells and electrolyzers is the incorporation of anion exchange membranes. These would provide many potential benefits, such as a significantly decrease cost as they do not rely on expensive precious metal catalysts. However, anion exchange membranes still face multiple challenges, one of them being their chemical stability. The properties of these membranes can be greatly influenced by the exact structure of the organic molecules used in their production. The number of possible structures is too large for any exhaustive search to find structures with the desired properties. To handle the incredibly large search space, the combination of quantum chemical simulations and machine learning models is applied to the problem through constructing a materials discovery tool. In the scope of this project, a valuable collaboration with experimentalist will enable the enhancement of this tool. A direct insight into the workflows and challenges of the experientialists working on these materials will be given to the intern. Importantly, the unmediated evaluation of the tool will be made possible through synthesis and characterization of the compounds proposed by the tool.

Faculty Supervisor:

Steven Holdcroft

Student:

Partner:

Rheinisch-Westfälische Technische Hochschule Aachen

Discipline:

Computer science

Sector:

Green/Alternative Energy; Artificial Intelligence; Technology; Quantum Science

University:

Simon Fraser University

Program: