Predictive computational methods have the potential to significantly accelerate the discovery of new materials with targeted properties by guiding the choice of candidate materials for synthesis. Work in this area has benefitted from increased speed and reliability of computational methods, developments in how we interpret the landscapes of predicted crystal structures and greater confidence from the material synthesis community in making decisions based on computational predictions.<br/><br/>The presentation will describe several approaches that we are developing for how best to use crystal structure prediction within an integrated computational-experimental workflow, using examples from applications in the discovery of porous molecular crystals and small molecule organic semiconductor materials. The methodologies that we have explored involve high throughput calculations on sets of related molecules, and evolutionary calculations where the exploration of molecules is guided by the fitness functions describing the potential for a candidate molecule to form a crystal structure with the desired properties. A crucial measure in these studies is how molecules are ranked, for which we explore single molecule calculations and quantities describing the property distribution of low energy predicted crystal structures.<br/>

Crystal structure prediction and the guided discovery of functional molecular materials

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.