Towards the prediction of properties in large clusters of ionic liquids with quantum chemical methods

Ionic liquids have many potential applications such as a green alternative to electrolytes in batteries. This thesis develops computational models that can be used to predict their properties such that task-specific ionic liquids can be identified.
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