## 1 Introduction
Moreover, this study reported enhancements in the tensile strength, yield strength, and Young's modulus equal to 10%, 83%, and 66%, respectively, for a MWCNT loading of 0.3 wt%. Cyclic stretch/release tests on these nanocomposites conducted by applying a strain amplitude of 50% showed good strain-sensing recoverability and reproducibility at up to 100 cycles. Fused Filament Fabrication (FFF) is one of the most popular additive manufacturing technologies [14]. The 3D-printed object is built up layer by layer, controlling the deposition of the molten feed stock material. Several investigations have recently been undertaken to explore the realm of additive manufacturing, with an additional focus on the fabrication of polymer/MWCNT nanocomposite structures through the FFF technique [15]. Many of these studies have delved into the intricate details of this additive manufacturing technology, seeking to unravel its potential for producing multifunctional complex-shape structures by seamlessly merging polymer matrices with the exceptional electrical and mechanical properties provided by MWCNTs [16; 17; 18; 19; 20; 21]. Therefore, in the last few years, researchers have explored the integration of sensing capabilities into soft robotics using 3D-printed flexible TPU/MWCNT composites. [PERSON] et al. employed multi-material FFF to print these composites and investigated their microstructures, electrical conductivity, capacitive-sensing, and piezoresistive-sensing properties [22]. The effect of layer height on conductivity varied with the MWCNT content. For the TPU-2 wt.% MWCNT samples, layer height had no significant effect on conductivity, likely due to the proximity to the percolation threshold. In contrast, the TPU-3 wt.% MWCNT samples showed a strong correlation between layer height and conductivity, with decreasing layer height increasing conductivity by reducing interfacial resistance. Both through-line and in-line samples with 4 wt.% MWCNTs exhibited an overall increase in conductivity with an increasing layer height, a property attributed to the larger cross-sectional area creating more percolation pathways. The effect of raster pattern and sample size on conductivity was evident in the TPU-3 wt.% MWCNTs samples at different layer heights. [23]. While bed temperature could affect internal void fraction and bond neck growth between rasters, the low glass transition temperature of TPU (\(-\)38 \({}^{\circ}\)C) made the practical range of bed temperatures (35-95 \({}^{\circ}\)C) insignificant with respect to raster-to-raster bonding and conductivity. Similarly, [PERSON] et al. developed 3D-printable, flexible, and conductive thermoplastic materials for strain-sensing applications [24]. They combined TPU with MWCNTs, and the extruded filaments were processed through FFF to produce 3D-printed sensors. Their investigation revealed enhanced stiffness due to the inclusion of MWCNTs and excellent interlayer adhesion, accompanied by a modest decrease in elastic modulus (\(-\)14%). The electrical conductivity trends in both the through-layer and cross-layer directions of the 3D-printed samples closely resembled those of hot-pressed samples. Interestingly, increasing the MWCNT content in the printed samples led to slightly higher cross-layer conductivity, likely due to orientation effects imparted during printing. This effect was more significant near the percolation threshold. Exceptional piezoresistive gauge factors of up to 176 were achieved under a strain level of 100%, with high repeatability under cyclic loading conditions. Therefore, TPU/MWCNT systems were determined to be a promising 3D-printing material for applications in wearable electronics, soft robotics, and prosthetics, allowing complex shape design and elevated customization potential. [PERSON] et al. introduced an innovative method for the direct fabrication of 3D multiaxial force sensors using FFF applied to functionalized nanocomposite filaments [25]. Their approach involved creating a 3D cubic cross-shaped force sensor capable of measuring forces along three axes.