Issue 19, 2020

Evolutionary chemical space exploration for functional materials: computational organic semiconductor discovery

Abstract

Computational methods, including crystal structure and property prediction, have the potential to accelerate the materials discovery process by enabling structure prediction and screening of possible molecular building blocks prior to their synthesis. However, the discovery of new functional molecular materials is still limited by the need to identify promising molecules from a vast chemical space. We describe an evolutionary method which explores a user specified region of chemical space to identify promising molecules, which are subsequently evaluated using crystal structure prediction. We demonstrate the methods for the exploration of aza-substituted pentacenes with the aim of finding small molecule organic semiconductors with high charge carrier mobilities, where the space of possible substitution patterns is too large to exhaustively search using a high throughput approach. The method efficiently explores this large space, typically requiring calculations on only ∼1% of molecules during a search. The results reveal two promising structural motifs: aza-substituted naphtho[1,2-a]anthracenes with reorganisation energies as low as pentacene and a series of pyridazine-based molecules having both low reorganisation energies and high electron affinities.

Graphical abstract: Evolutionary chemical space exploration for functional materials: computational organic semiconductor discovery

Supplementary files

Article information

Article type
Edge Article
Submitted
29 Jan 2020
Accepted
21 Apr 2020
First published
22 Apr 2020
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY license

Chem. Sci., 2020,11, 4922-4933

Evolutionary chemical space exploration for functional materials: computational organic semiconductor discovery

C. Y. Cheng, J. E. Campbell and G. M. Day, Chem. Sci., 2020, 11, 4922 DOI: 10.1039/D0SC00554A

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements