## 3 Results and Discussion  
### Structure and Morphology  
A homogeneous dispersion of MWCNT and GNP in polymeric melts is essential to prepare enhanced filler-based filaments, since heterogeneity can be detrimental to Fused Deposition Modeling technology (FDM), possibly causing blockages at the nozzle and flux instability while printing. Thus, current research has focused on determining the concentration of carbon nanofillers that would surpass the percolation threshold (the transition between an insulating and conductive polymer) while maintaining the parameters for 3D printing. The homogeneity of GNP dispersion directly affects the composite's printability ability and other physical properties. TEM and SEM is a common tool used to distinguish carbon nanofillers from the polymer matrix due to different contrasts and filler specific morphologies. Figure 1a-d presents SEM images of cryo-fractured surfaces of the mono-filler and bi-filler composites containing (a) PLA/6 wt.% MWCNT; (b) PLA/6 wt.% GNP; (c) PLA/1.5% GNP/1.5% MWCNT and (d) PLA/3% GNP/3% MWCNT, respectively. All images are at the same magnification of 20,000\(\times\), for comparison. Figure 1a clearly shows the good distribution of carbon nanotubes (protruding white dots on the cryo-fractured surface) in the polymer matrix at the maximum mono-filler concentration of 6 wt.% and no aggregates were found. Figure 2b presents randomly dispersed single GNP platelets and small aggregates at a maximum mono-filler content of 6 wt.% GNP. Figure 1c,d revealed a distribution of MWCNTs and GNP in the polymer matrix for bi-filler systems, containing the same quantity of each nanofiller PLA/1.5% GNP/1.5% MWCNT and PLA/3% GNP/3% MWCNT. In this case images show randomly distributed single carbon nanotubes, small aggregates of nanotubes and GNP packages. Figure 2a,b presents TEM images of the bi-filler composites with a total filler content of 6 wt.% (a) PLA/1.5 wt.% GNP/4.5 wt.% MWCNT and (b) PLA/3 wt.% GNP/3 wt.% MWCNT, respectively. A good bi-filler distribution can be observed at both combined concentrations on Figure 2a,b. Both fillers seem to form an interconnected network, where the single nanotubes, small MWCNT aggregates and GNPs creates an interpenetrated network of particles and small aggregates. Obviously, the combination of the two nanofillers in the PLA matrix led created the possibility of unique synergetic effect for the improvement of the electrical and mechanical properties as described below. Figure 1: Scanning Electron Microscopy (SEM) images of cryo-fractured surfaces of the mono-filler composites, containing (**a**) 6 wt.% multi-walled carbon nanotubes (MWCNT) and (**b**) 6 wt.% of graphene nanoplates (GNP) and bi-filler composites, containing (**c**) 1.5% GNP/1.5% MWCNT and (**d**) 3% GNP/3% MWCNT, respectively at magnification 20,000 \(\times\). Figure 2: Transmission Electron Microscopy (TEM) images of the bi-filler composites containing (**a**) polylactic acid (PLA)/1.5 wt.% GNP/4.5 wt.% MWCNT and (**b**) PLA/3 wt.% GNP/3 wt.% MWCNT, respectively. Raman spectroscopy can be used as a quick and unambiguous method to determine the number of graphene layers (flakes or walls in nanotubes) and its structural quality either at a pure state or dispersed in the polymer matrix. Graphene spectrums are characterized by three bands: G, D and 2D. The G band is related to the in-plane vibrational mode that involves sp\({}^{2}\) hybridized carbon atoms of graphene sheets; its position is highly sensitive to the number of layers (shifts to lower wavenumber with an increased number of layers). The D band represents defects in the graphene carbon lattice. Additionally, intensity ratios: I\({}_{\text{D}}\)/I\({}_{\text{G}}\) and I\({}_{\text{2D}}\)/I\({}_{\text{G}}\); give an insight of structural disorder degree and quality of graphene, where defect-free graphene ratio is equal 2. The single and sharp second-order Raman band (2D) has been widely used as a simple and efficient way to confirm the presence of single layer graphene.