## 4 Discussion  
The results presented in this paper are significant in demonstrating a simple technique to reproducibly print freestanding thin parts. In Figure 4, the relationship between programmed layer separation and measured sample thickness was shown. In this experiment, changes in \(L_{PLLA}\) are synonymous with deviations in the distance between the nozzle and the bed that occurs across misaligned printing surfaces or the inconsistencies that might be found between differently calibrated 3D printers. This reported variation, therefore, demonstrates that even relatively small deviations in bed offset, or tilt, yield proportional changes in sample geometry. For example, a miscalibration of around 50 \(\upmu\)m would yield a PLLA thickness difference of close to 45 \(\upmu\)m. Consider two printers which are built and calibrated by two different users. It would not be unreasonable to suggest that the absolute point at which either user determines to be z = 0 might vary by between 50 to 100 \(\upmu\)m. In this scenario, on moving from one machine to another a significant difference in layer  
Figure 10: Cross-sectional \(\upmu\)-CT images (**a**) end-on (**b**) side-on of 3D-printed PLLA layers (\(L_{PLLA}\) = 25 \(\upmu\)m and \(e_{PLLA}\) = 0.0025) after washing to remove PVA layer. Samples are mounted on a card. separation would be observed. Likewise, should the user need to replace and perform maintenance on their printer, such as unblocking and rebuilding the extruder, or replacing the nozzle, calibration must be reperformed. We found that between nozzle changes and recalibrations, layer thicknesses were noticeably different visually, and measured to vary on the order of 10 s of microns. This, however, is shown to be largely mitigated in Figure 8 through the incorporation of a sacrificial PVA layer. Here, for a PVA layer printed at \(e_{PVA}\) = 0.04, PLLA (\(e_{PILA}\) = 0.02, \(L_{PILA}\) = 200 \(\upmu\)m) thickness does not appear to vary significantly with PVA layer separation. There is a small variation (proportionality of 0.22 \(\pm\) 0.02) in PLLA thickness with a sacrificial layer of \(e_{PVA}\) = 0.06, but this is still a significant improvement over the susceptibility introduced in Figure 4.  
The sequential nozzle passes that deposit both the sacrificial PVA layer, and PLLA layer, are easier to visualise if the measured sample thicknesses are represented on an imagined sloped printing surface. This is depicted in Figure 11, reconstructed from the dataset introduced in Figure 8. Here, the lightly shaded region is 'filled' in with PVA, providing a flatter surface onto which PLLA can be printed. The height of the more heavily shaded parallelogram represents PLLA layer thickness, \(h_{PILA}\), and is consistent across the range of \(L_{PVA}\) sampled. There is, however, a discrepancy between the thicknesses of the peeled PVA layers in Figure 8a and the standalone layers printed in Figure 5, notably in a reduction of proportionality from 0.98 \(\pm\) 0.03 to 0.89 \(\pm\) 0.05 and shift of around 15 \(\upmu\)m for \(e_{PVA}\) = 0.04,  
Figure 11: A representation of the PVA and PLLA layer thicknesses previously presented in Figure 8. Layers are visualised on a 45\({}^{\circ}\) sloped printing surface. PVA and PLLA layers are represented by dashed and solid markers, respectively. The surface slope is shown to be drastically reduced in severity, with the heavily shaded region showing uniform PLLA thickness, \(h_{PILA}\). though these values still fall within the ranges of error set in Figure 5. Firstly, measurements of peeled samples (Figure 8a) should be prefaced by the fact the layers are printed PVA, hence are quite difficult to keep uniform during peeling, and are likely to be deformed, especially if air humidity is fairly high. Samples may also be deformed during sectioning.