Additive manufacturing of Diels-Alder self-healing polymers: Separate heating system to enhance mechanical, healing properties and assembly-free smart structures

Over the past decades, self-healing polymers have become increasingly popular due to their unique ability to recover mechanical and functional properties after sustaining structural damage, which significantly extends their lifespan compared to traditional polymers. Material Extrusion (MEX) 3D printing has recently emerged as a possible manufacturing approach for processing self-healing polymers; however, commercial MEX 3D printers lack of the flexibility to fabricate complex and functional structures based on such materials. In this work, an innovative MEX setup for extruding self-healing polymer networks based on a thermo-reversible reaction is presented. The proposed approach is based on the leverage of a separate heating system (SHS), enabling the degelation of the self-healing polymer network into a printable ink. This SHS regulates both the syringe-barrel, and nozzle temperatures during the processing (degelation and extrusion) of self-healing inks, leading to enhanced mechanical performance (Young modulus, tensile strength), and extrusion accuracy of 3D printed structures. The effectiveness of the SHS-based approach is demonstrated by an improved geometrical accuracy (filament deviation reduced by 26 %), which is directly correlated to the mitigation of the extrusion force (variability reduced by 77 %). Moreover, the SHS approach also improved both the mechanical properties and the self-healing performance of the printed parts. Finally, two different self-healing polymers a dielectric and an electrically conductive were extruded in a single manufacturing cycle to fabricate a self-sensing structure. This structure is capable of detecting bending with a sensitivity of 3.10 Ω/degree, even after healing. This paper aims to advance the role of MEX beyond its current limitations by enabling processing of high-quality self-healing structures with embedded sensors.