RESUMEN

A methodology for predictive kinetic self-assembly modeling of bottom-up chemical synthesis of nanographene is proposed. The method maintains physical transparency in using a novel array format to efficiently store molecule information and by using array operations to determine reaction possibilities. Within a minimal model approach, the parameter space for the bond activation energies (i.e. molecule functionalization) at fixed reaction temperature and initial molecule concentrations is explored. Directed self-assembly of nanographene from functionalized tetrabenzanthracene and benzene is studied with regions in the activation energy phase-space showing length-to-width ratio tunability. The degree of defects and reaction reproducibility in the simulations is also determined, with the rate of functionalized benzene addition providing additional control of the dimension and quality of the nanographene. Comparison of the reaction energetics to available density functional theory data suggests the synthesis may be experimentally tenable using aryl-halide cross-coupling and noble metal surface-assisted catalysis. With full access to the intermediate reaction network and with dynamic coupling to density functional theory-informed tight-binding simulation, the method is proposed as a computationally efficient means towards detailed simulation-driven design of new nanographene systems.