Cellulose nanocrystals: Advancements and applications in 3D printing

Cellulose nanocrystals (CNCs) are sustainable nanomaterials exhibiting high mechanical strength, thermal stability, biocompatibility, and tunable surface chemistry. Derived from renewable sources such as wood, cotton, hemp, agro-industrial residues, algae, and bacterial cellulose, they are produced through chemical, mechanical, or enzymatic processes, each offering distinct advantages and limitations related to crystallinity, yield, processing efficiency, and environmental impact such as waste generation and handling of concentrated acids. Post-treatment strategies, including esterification, silanization, and grafting, further enhance compatibility with diverse polymeric matrices and enable the incorporation of targeted functionalities. This review provides a comprehensive overview of CNC sources, extraction and isolation methods, surface modifications, and fundamental physical and chemical properties, establishing the basis for their application in additive manufacturing (AM). Particular attention is given to recent progress in CNC-reinforced composites fabricated via fused deposition modelling, direct ink writing, and vat photopolymerization methods. Reported improvements include higher mechanical strength, tunable rheological behavior, enhanced thermal resistance, and advanced functionalities such as shape-memory effects, self-healing, antibacterial performance, and controlled biodegradation. Despite these advances, challenges remain in dispersion control, interfacial adhesion, optimal CNC loading, and balancing processing conditions with final material performance. Strategies addressing these issues involve tailored surface chemistry, matrix design, and process optimization. Although current research on CNC applications in AM has been primarily material-oriented, optimizing printing processes remains essential for achieving consistent performance and structural integrity. To address this need, future studies should focus on real-time process monitoring and artificial intelligence-assisted control to mitigate process-related issues arising from CNC properties and to expand CNC-based materials into biomedical and dental devices, other AM technologies, and sustainable food production. Integrating CNC material science with process-specific optimization positions CNCs as versatile bio-based additives for next-generation AM systems.