Structure Prediction of Epitaxial Organic Interfaces with Ogre, Demonstrated for Tetracyanoquinodimethane (TCNQ) on Tetrathiafulvalene (TTF)

Highly ordered epitaxial interfaces between organic semiconductors could enhance the performance of organic devices thanks to their well-controlled, uniform electronic properties and high carrier mobility. The electronic structure of epitaxial organic interfaces and their functionality are inextricably linked to their structure. We present a method for structure prediction of epitaxial organic interfaces based on lattice matching followed by surface matching, implemented in the open-source code, Ogre. The lattice matching step produces domain-matched interfaces, where commensurability is achieved with different integer multiples of the substrate and film unit cells. In the surface matching step, dispersion corrected deep neural network (DNN) interatomic potentials are used to find the interfacial distance and registry between the substrate and film. The DNN potentials are in agreement with density functional theory (DFT) for the optimal position of the film on the substrate and the ranking of putative interface structures. We investigate the epitaxial interface of TCNQ on TTF, whose electronic structure has been probed by ultraviolet photoemission spectroscopy (UPS), but whose structure had been hitherto unknown. We find that TCNQ(001) on top of TTF(100) is the most stable interface configuration, closely followed by TCNQ(010) on top of TTF(100). The density of states, calculated using DFT, is in excellent agreement with UPS, including the presence of an interface charge transfer state.