The work within this proposal leverages previous advances to predict the persistence length, glass transition temperature and nematic-to-isotropic transition temperature. The proposed project aims to further advance computational materials design, by developing tools capable of accelerating the prediction of mechanical and conductive properties. Three computational tools will be developed: coarse-grained models based on force-matching to accelerate computational design of liquid crystalline semiflexible polymers, chain-shrinking simulations to predict the effect of liquid crystallinity on entanglement, and tight-binding models to explore the role of packing and disorder on charge transport. The combination of simulations and experiments will be crucial to generate accurate coarse-grained simulations capable of predicting liquid crystallinity through the Principal Investigators' approach that combines molecular dynamics simulations with self-consistent field theory calculations. This will enable the systematic computational exploration of backbone and side chain architectures that are validated with selected synthesized model materials. Simulations and experiment will also be crucial to incorporate nematic order in the Principal Investigators' unified theory of polymer entanglements, and thereby provide a tool capable of predicting rheological properties (e.g. mechanical properties) of conjugated polymers from the chemical structure. Furthermore, tight-binding models will predict the role of packing and local disorder on charge transport, to explore the hypotheses that layered disordered phases can play a crucial role in promoting efficient charge transport by facilitating pi-stacking. Such models will be validated by measurements of the charge mobility as a function of temperature and within various crystalline, liquid crystalline, or isotropic phases.