The absence of scalable and environmentally sustainable methods for producing electronic-grade graphene nanoplatelets remains a barrier to the industrial-scale application of graphene in printed electronics and conductive composites. To address this unmet need, here we report the utilization of carboxylated cellulose nanocrystals (CNCs) extracted from the perennial tall grass Miscanthus × giganteus as a biorenewable dispersant for the aqueous liquid-phase exfoliation of few-layer graphene nanoplatelets. This CNC-based exfoliation procedure was optimized using a Bayesian machine learning model, resulting in a significant graphite-to-graphene conversion yield of 13.4% and a percolating graphene thin-film electrical conductivity of 3.4 × 104 S m-1. The as-exfoliated graphene dispersions were directly formulated into an aerosol jet printing ink using cellulose-based additives to achieve high-resolution printing (∼20 μm line width). Life cycle assessment of this CNC-based exfoliation method showed substantial improvements for fossil fuel consumption, greenhouse gas emissions, and water consumption compared to incumbent liquid-phase exfoliation methods for electronic-grade graphene nanoplatelets. Mechanistically, potential mean force calculations from molecular dynamics simulations reveal that the high exfoliation yield can be traced back to the favorable surface interactions between CNCs and graphene. Ultimately, the use of biorenewable CNCs for liquid-phase exfoliation will accelerate the scalable and eco-friendly manufacturing of graphene for electronically conductive applications.
Keywords: Bayesian optimization; aerosol jet printing; cellulose nanocrystals; graphene; life cycle assessment; liquid-phase exfoliation; printed electronics.