Organic materials repurposing, a data set for theoretical predictions of new applications for existing compounds

Omar, Ömer H. and Nematiaram, Tahereh and Troisi, Alessandro and Padula, Daniele (2022) Organic materials repurposing, a data set for theoretical predictions of new applications for existing compounds. Scientific Data, 9. 54. ISSN 2052-4463 (https://doi.org/10.1038/s41597-022-01142-7)

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Abstract

We present a data set of 48182 organic semiconductors, constituted of molecules that were prepared with a documented synthetic pathway and are stable in solid state. We based our search on the Cambridge Structural Database, from which we selected semiconductors with a computational funnel procedure. For each entry we provide a set of electronic properties relevant for organic materials research, and the electronic wavefunction for further calculations and/or analyses. This data set has low bias because it was not built from a set of materials designed for organic electronics, and thus it provides an excellent starting point in the search of new applications for known materials, with a great potential for novel physical insight. The data set contains molecules used as benchmarks in many fields of organic materials research, allowing to test the reliability of computational screenings for the desired application, “rediscovering” well-known molecules. This is demonstrated by a series of different applications in the field of organic

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