# Injection Molding Simulation of Polycaprolactone-Based Carbon Nanotube Nanocomposites for Biomedical Implant Manufacturing

## TL;DR

This study simulates and validates the injection molding of PCL-based nanocomposites with carbon nanotubes for biomedical implants, finding that low CNT content yields the best results.

## Contribution

The study introduces a validated simulation approach for optimizing PCL/MWCNT nanocomposites in injection molding for 3D-printed biomedical implants.

## Key findings

- Low CNT content (0.5 wt.%) enabled stable filling times and complete mold cavity filling.
- Higher CNT loadings (10 wt.%) caused longer fill times and incomplete cavity filling due to increased viscosity.
- Experimental trials confirmed simulation results for 0.5 wt.% CNT composites.

## Abstract

This study consisted of the injection molding simulation of polycaprolactone (PCL)-based nanocomposites reinforced with multi-walled carbon nanotubes (MWCNTs) for biomedical implant manufacturing. The simulation was additionally supported by experimental validation. The influence of varying MWCNT concentrations (0.5%, 5%, and 10% by weight) on key injection molding parameters, i.e., melt flow behavior, pressure distribution, temperature profiles, and fiber orientation, was analyzed with SolidWorks Plastics software. The results proved the low CNT content (0.5 wt.%) to be endowed with stable filling times, complete mold cavity filling, and minimal frozen regions. Thus, this formulation produced defect-free modular filament sticks suitable for subsequent 3D printing. In contrast, higher CNT loadings (particularly 10 wt.%) led to longer fill times, incomplete cavity filling, and early solidification due to increased melt viscosity and thermal conductivity. Experimental molding trials with the 0.5 wt.% CNT composites confirmed the simulation findings. Following minor adjustments to processing parameters, high-quality, defect-free sticks were produced. Overall, the PCL/MWCNT composites with 0.5 wt.% nanotube content exhibited optimal injection molding performance and functional properties, supporting their application in modular, patient-specific biomedical 3D printing.