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. † Electronic supplementary information (ESI) available: Full details of computational methods, tting of molecular to solid-state electron affinities, ESF maps of all molecules, low energy predicted crystal structures and calculated properties. See

Flickering Polarons Extending over Ten Nanometres Mediate Charge Transport in High‐Mobility Organic Crystals

“…Nevertheless, the quantities appearing in rules (2)-(3) can be relatively straightforwardly calculated from DFT and used to refine high throughput screening studies that have previously focused on rule (1) alone. [49,50] In conclusion, we have reported the full 2D charge mobility tensors for six organic crystals and uncovered the real-time dynamics of the charge carriers using a powerful non-adiabatic molecular dynamics simulation methodology. We find that the charge carrier wavefunction forms a flickering, highly dynamic polaron that is delocalized over about 5 nm on average in the most conductive crystals and of finite size due to thermal energetic disorder.…”

“…Nevertheless, the quantities appearing in rules (2)–(3) can be relatively straightforwardly calculated from DFT and used to refine high throughput screening studies that have previously focused on rule (1) alone. [ 49,50 ]…”

Multifidelity Statistical Machine Learning for Molecular Crystal Structure Prediction

“…The uncertainties in relative energies can also be incorporated in probabilistic interpretations of structure-energy-property maps that have been developed for materials discovery using CSP. [18][19][20]…”

“…Applications of CSP are also developing in the area of functional materials discovery by linking molecular structure to likely materials structures and, hence, to properties of interest; this process can be used to screen and prioritise potential synthetic targets. [17][18][19][20] CSP is usually approached as a problem in global optimization. Possible crystal structures correspond to local minima on a high dimensional energy surface determined by the structural degrees of freedom defining a crystal structure (unit cell dimensions, molecular positions and orientations, and intramolecular degrees of freedom).…”

Bridging photochemistry and photomechanics with NMR crystallography: the molecular basis for the macroscopic expansion of an anthracene ester nanorod

“…Given how even small changes in molecular structure can lead to completely different packing motifs, computational crystal structure prediction could be helpful. 81 Crystal structure prediction has recently been employed to discover materials with desired porosity 82 or organic semiconducting properties, 83,84 for example. The photomechanical materials described here would provide an even 18 stiffer challenge, since knowledge of the crystal structure before and after the photochemical reaction is required.…”