Copolymer-Enabled Viscosity Modification and Experimental Verification of Melt Extrusion Printing of Conducting Thermoplastic/rGO Nanocomposites

Functional polymer-based materials are essential for expanding the application range for polymer additive manufacturing. Challenges associated with integration of reduced graphene oxide (rGO) into the engineering thermoplastic acrylonitrile–styrene–acrylate (ASA) are overcome by incorporating a plasticizing copolymer (PC), poly(cyclohexyl acrylate- random -styrene) (p(CHA- r -Sty)), which enables melt extrusion-based printing of electrically conducting filaments. Highly loaded filaments with 5 and 10 wt % rGO exhibit conductivities of 0.053 S/cm and 0.321 S/cm, respectively, placing them within the semiconducting range. The inherent aggregation and brittleness resulting from rGO incorporation hinders melt extrusion printing, but the addition of p(CHA- r -Sty) PCs that are specifically designed to have low glass transition temperatures ( T g ) and miscibility with ASA improves rGO dispersion and alters viscoelastic properties, enabling melt extrusion printing. Melt flow index measurements and parallel plate rheology reveal a molecular weight-dependent trade-off between PC composition, flow behavior, and printability, with lower-molecular-weight PCs more effectively mitigating processing challenges. A continuum mechanics-based model describing melt extrusion printing captures these trade-offs with the ASA/rGO and ASA/rGO/PC nanocomposites and, more significantly, the model’s predictions of printability are experimentally verified. The addition of PC does not compromise mechanical strength as ASA/rGO/PC blends exhibit modest improvements in Young’s modulus compared to unfilled ASA. These findings highlight the potential of ASA/rGO/PC nanocomposites as printable, electrically conducting materials. This work also underscores the role of polymer-based plasticizers that are designed to promote processability and compatibilization without sacrificing mechanical integrity and exemplifies how a simple model parametrized with material properties can guide melt extrusion-based printing of functional systems.