# Solution Extrusion Additive Manufacturing of Biodegradable Polycaprolactone
## Materials and Methods
### Empirical Parameters  
To estimate the influence of possible residual solvent on fabricated parts, a few specimens were first fabricated. The weights of the specimens were measured after placement in a ventilation chamber at room temperature (25 \({}^{\circ}\)C) for various periods of time (0-6 days). Five parameters were selected for the analysis: the PCL/DCM ratio, fill density, moving speed of the dispensing tip, and print orientation of infill of the extruded strips (Figure 3C). Before the experiments, a few test trials were first completed to determine the range of processing parameters that can successfully manufacture the parts. The processable range was then subdivided so as to examine the influence of each factor on the fabricated part's quality. The PCL/solvent (DCM) ratio (_w/v_) was 5 g/6.8 mL, 5 g/7.0 mL, 5 g/7.1 mL, or 5 g/7.2 mL. The fill density was 65%, 70%, 75%, or 80%. The moving speed of the dispensing tip ranged from 40 to 70 mm/s. The strips' print orientation of infill was set as 30\({}^{\circ}\), 45\({}^{\circ}\), 75\({}^{\circ}\), or 90\({}^{\circ}\) (see Figure 3C). Table 1 lists the parameters and parameter levels used in the experiments. The dispensing nozzle and the collection platform were not heated during the experimental procedure. A geometry for tensile tests (Figure 4A) was used to manufacture the part samples. A commercially available computer-aided design software (Solidworks, Waltham, MA, USA) was employed to produce the code for controlling the movement of the dispensing tip. After additive manufacturing, the mechanical properties of the manufactured dumbbell-shaped parts were evaluated using a tensile tester (Lloyd, Ameteck, Berwyn, PA, USA) with a 2500 N load cell by following the ASTM D638 standard. The tensile pulling speed was set as 60 mm/min. The tensile strength was computed as follows:  
\[\text{Tensile strength (MPa) = Breaking force (N)/Cross-sectional area of sample (mm\({}^{2}\)) } \tag{1}\] \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Factor**} & **A: PCL/DCM Ratio** & **B: Fill Density** & **C: Print Speed** & **D: Print Orientation** \\  & **(_w/v_)** & **(\%)** & **(mm/s)** & **of Infill** \\ \hline Level 1 & 5 g/6.8 mL & 65 & 40 & 30\({}^{\circ}\) \\ Level 2 & **5 g/7 mL** & **70** & **50** & **45\({}^{\circ}\)** \\ Level 3 & 5 g/7.1 mL & 75 & 60 & 75\({}^{\circ}\) \\ Level 4 & 5 g/7.2 mL & 80 & 70 & 90\({}^{\circ}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Parameters used for the 3D printing experiments. Figure 3: **(A)** Polycaprolactone (PCL) pellets were first mixed in dichloromethane (DCM), **(B)** the solution was poured into the syringe for additive manufacturing, **(C)** manufacturing of parts layer-by-layer with designated print orientation of infill. A full factorial experiment allows the investigator to investigate the effect of each factor on the response variable, as well as the effects of interactions between factors on the response variable. However, it requires a large number of samples and experimental trials, which is time-consuming. A single-factor experimental design utilizes experimental methodology to focus on only one subject. This design is distinct from case study methodology, which also focuses on one individual, because single-factor experimental designs use the same systematic processes as other experimental designs. The investigator establishes the study to manipulate an independent variable (or variables) and to measure how a dependent variable responds to changes in the independent variable. This design has the experimental benefit of a controlled comparison, because the individual subject serves as the control by engaging in all of the conditions [14]. In this study, the single-factor experimental design was employed, where a set of arbitrarily selected processing condition (Level 2 in Table 1) was selected as a reference.