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

Highly ordered epitaxialinterfaces between organic semiconductorsare considered as a promising avenue for enhancing the performanceof organic electronic devices including solar cells and transistors,thanks to their well-controlled, uniform electronic properties andhigh carrier mobilities. The electronic structure of epitaxial organicinterfaces and their functionality in devices are inextricably linkedto their structure. We present a method for structure prediction ofepitaxial organic interfaces based on lattice matching followed bysurface matching, implemented in the open-source Python package, Ogre.The lattice matching step produces domain-matched interfaces, wherecommensurability is achieved with different integer multiples of thesubstrate and film unit cells. In the surface matching step, Bayesianoptimization (BO) is used to find the interfacial distance and registrybetween the substrate and film. The BO objective function is basedon dispersion corrected deep neural network interatomic potentials.These are shown to be in qualitative agreement with density functionaltheory (DFT) regarding the optimal position of the film on top ofthe substrate and the ranking of putative interface structures. Ogreis used to investigate the epitaxial interface of 7,7,8,8-tetracyanoquinodimethane(TCNQ) on tetrathiafulvalene (TTF), whose electronic structure hasbeen probed by ultraviolet photoemission spectroscopy (UPS), but whosestructure had been hitherto unknown [Organic Electronics 2017, 48, 371]. We find that TCNQ(001)on top of TTF(100) is the most stable interface configuration, closelyfollowed by TCNQ(010) on top of TTF(100). The density of states, calculatedusing DFT, is in excellent agreement with UPS, including the presenceof an interface charge transfer state.