Atomistic models for disordered nanoporous carbons using reactive force fields

Abstract Optimization of disordered nanoporous carbons (DNCs) for specific applications remains a challenge due to the difficulty in accurately characterizing their nanostructures with current experimental methods. We describe how atomistic simulation techniques can be used to build structural models of DNCs and subsequently elucidate the structure–function relationship in these complex porous materials. In particular, two state-of-the-art approaches that use methods based in statistical mechanics to predict the structure of DNCs are described. The quench molecular dynamics method is a pseudo-mimetic approach that captures the effect of synthesis temperature on the structural morphology of disordered carbons, while the hybrid reverse Monte Carlo method is a reconstruction approach that builds realistic replicas of DNCs from experimental diffraction data. Both of these methods use reactive force fields to capture the formation and disassociation of chemical bonds during the simulations, allowing for the structural and porous features of DNCs to be predicted. We describe the principles behind these methods and provide illustrative examples that demonstrate their utility in modeling DNCs. Finally, we also discuss their current limitations and future avenues for improving their predictive capabilities.