The potential of conjugated polymers to compete with inorganic materials in the field of semiconductor is conditional on fine-tuning of the charge carriers mobility. The latter is closely related to the material morphology, and various studies have shown that the bottleneck for charge transport is the connectivity between well-ordered crystallites, with a high degree of π -π stacking, dispersed into a disordered matrix. However, at this time there is a lack of theoretical descriptions accounting for this link between morphology and mobility, hindering the development of systematic material designs. Here we propose a computational model to predict charge carriers mobility in conducting polymer PEDOT depending on the physicochemical properties of the system. We start by calculating the morphology using molecular dynamics simulations. Based on the calculated morphology we perform quantum mechanical calculation of the transfer integrals between states in polymer chains and calculate corresponding hopping rates using the Miller-Abrahams formalism. We then construct a transport resistive network, calculate the mobility using a mean-field approach, and analyze the calculated mobility in terms of transfer integrals distributions and percolation thresholds. Our results provide theoretical support for the recent study [Noriega et al., Nat. Mater. 12, 1038] explaining why the mobility in polymers rapidly increases as the chain length is increased and then saturates for sufficiently long chains. Our study also provides the answer to the long-standing question whether the enhancement of the crystallinity is the key to designing high-mobility polymers. We demonstrate, that it is the effective π -π stacking, not the long-range order that is essential for the material design for the enhanced electrical performance. This generic model can compare the mobility of a polymer thin film with different solvent contents, solvent additives, dopant species or polymer characteristics, providing a general framework to design new high mobility conjugated polymer materials.

Deposition dynamics, crystallization, molecular packing, and electronic mobility of poly(3,4-ethylenedioxythiophene) (PEDOT) thin films are affected by the nature of the substrate. Computational microscopy has been carried out to reveal the morphology-substrate dependence for PEDOT thin films doped with molecular tosylate deposited on different substrates including graphite, SiN, silicon, and amorphous SiO. It is shown that the substrate is instrumental in formation of the lamellar structure. PEDOT films on the ordered substrates (graphite, SiN, and silicon) exhibit preferential face-on orientation, with graphite showing the most ordered and pronounced face-on packing. In contrast, PEDOT on amorphous SiO exhibits the dominant edge-on orientation, except in the dry state where both packings are equally presented. The role of water and the porosity of the substrate in formation of the edge-on structure on SiO is outlined. On the basis of the calculated morphology, the multiscale calculations of the electronic transport and percolative analysis are performed outlining how the character of the substrate affects the electron mobility. It is demonstrated that good crystallinity (PEDOT on graphite substrate) and high content of edge-on (PEDOT on SiO substrate) are not enough to achieve the highest electrical in-plane mobility. Instead, the least ordered material with lower degree of the edge-on content (PEDOT on silicon substrate) provides the highest mobility because it exhibits an efficient network of π-π stacked chain extending throughout the entire sample.

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Cellulose being the most widely available biopolymer on Earth is attracting significant interest from the industry and research communities. While molecular simulations can be used to understand fundamental aspects of cellulose nanocrystal selfassembly, a model that can perform on the experimental scale is currently missing. In our study we develop a supra coarse-grained (sCG) model of cellulose nanocrystal which aims to bridge the gap between molecular simulations and experiments. The sCG model is based on atomistic molecular dynamics simulations and it is developed with the forcematching coarse-graining procedure. The validity of the model is shown through comparison with experimental and simulation results of the elastic modulus, self-diffusion coefficients and cellulose fiber twisting angle. We also present two representative case studies, self-assembly of nanocrystal during solvent evaporation and simulation of a chiral nematic phase ordering. Finally, we discuss possible future applications for our model.