A Computational Predictive Approach for Controlling the Morphology of Functional Molecular Aggregates on Substrates

Abstract

Full control of the growth dynamics and morphology of nanoscale molecular aggregates on substrates is a crucial factor for the development of novel materials and devices for technological applications. A novel computational approach based on molecular dynamics, which is able to predict the structure of nanoscale aggregates of organic small molecules on substrates as a function of growth and processing conditions, is presented. In the simulation protocol proposed, molecules are progressively added to the substrate, one by one, reproducing vacuum thermal deposition processes. The simulation parameters affect the structure of the configuration, and formation of molecular aggregates is spontaneously observed upon reaching a critical molecular density at the interface. Suitable simulation parameters allow to access different molecular aggregation morphologies on substrates, including crystalline phases, matching the structural variability observed in real fabrication conditions. This approach is benchmarked by simulating the morphology of aggregates of N,N′-ditridecylperylene-3,4,9,10-tetracarboxylic diimide (PTCDI-C13), a prototypical n-type semiconductor for organic electronics, on graphene, in different growth conditions. Simulations predict structural features of aggregates of PTCDI-C13 on graphene that are in excellent agreement with experiments and, at the same time, provide a rationale and quantitative relationship between molecular structure and observed aggregation morphologies.

On the Nature of Charge-Injecting Contacts in Organic Field-Effect Transistors

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3D versus 2D Electrolyte–Semiconductor Interfaces in Rylenediimide‐Based Electron‐Transporting Water‐Gated Organic Field‐Effect Transistors

“…[56] This computational approach reproduces the structure of molecular aggregates that are in excellent agreement with experiments. [57][58][59][60] The water molecules were simulated using the TIP4P model. The Berendsen thermostat was used for simulations in the NVT and NPT with time constants of 0.1 and 1.0 ps, respectively.…”