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Knowledge discovery through chemical space networks: the case of organic electronics

  • Christian Kunkel
  • Christoph Schober
  • Harald OberhoferEmail author
  • Karsten Reuter
Original Paper
Part of the following topical collections:
  1. Tim Clark 70th Birthday Festschrift

Abstract

Modern materials discovery and design studies often rely on the computational screening of large databases. Complementing experimental databases, virtual databases are thereby increasingly established through the first-principles calculation of computationally inexpensive, but for a given application, decisive microscopic quantities of the system. These so-called descriptors are calculated for vast numbers of candidate materials. In general, the sheer volume of datapoints generated in such studies precludes an in depth human analysis. To this end, smart visualization techniques, based e.g., on so-called chemical space networks (CSN), have been developed to extract general design rules connecting structural modifications to changes in the target functionality. In this work, we generate and visualize the CSN of possible crystalline organic semiconductors based on an in-house database of > 64,000 molecular crystals that we extracted from the exhaustive Cambridge Structural Database and for which we computed prominent charge-mobility descriptors. Our CSN thereby links clusters of molecular crystals based on the chemical similarity of the scaffolds of their molecular building blocks and thus groups communities of similar molecules. Including each cluster’s median descriptor values, the CSN visualization not only reproduces known trends of good organic semiconductors but also allows us to extract general design rules for organic molecular scaffolds. Finally, the local environment of each scaffold in our visualization shows how thoroughly its local chemical space has already been explored synthetically. Of special interest here are those clusters with promising descriptor values, yet with little or no connections in the sampled chemical space, as these offer the most room for scaffold optimization.

Keywords

Organic electronics Materials design Chemical space networks 

Notes

Acknowledgements

We acknowledge support from the Solar Technologies Go Hybrid initiative of the State of Bavaria and the Leibniz Supercomputing Centre for high-performance computing time at the SuperMUC facility. We further acknowledge support by Deutsche Forschungsgemeinschaft (DFG) through TUM International Graduate School of Science and Engineering (IGSSE), GSC 81.

Supplementary material

894_2019_3950_MOESM1_ESM.pdf (707 kb)
(PDF 707 KB)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Chair for Theoretical Chemistry and Catalysis Research CenterTechnische Universität MünchenGarchingGermany

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