# Thermoplastic Materials for the Metal Replacement of Non-Structural Components in Marine Engines
## 2 Materials and Methods  
### Materials  
#### 2.1.1 Material Design  
The adopted CAMDD-based workflow is based on the adaptation and implementation of a series of computational recipes we previously developed and validated for a range of different (nano)composite polymeric materials [21; 22]. Briefly, using the Rotational Isomeric State (RIS) approach [23] at room temperature, 3 independent chain configurations were constructed beginning from the optimum monomer unit for each polymer. Then, for each chain, a three-dimensional (3D) simulation cell was constructed and optimized under periodic boundary conditions (PBCs), either using just polymer chains or 1 filler surrounded by the required amount of polymer molecules to attain a specific weight fraction (see below). As a result, 3 distinct 3D systems were created for each macromolecule generated via RIS, and each of these boxes was subjected to the computational procedure for determining the specified attribute. Accordingly, the reported value of each material property is averaged across three such simulations. All molecular in silico experiments were performed on our own CPU/GPU cluster exploiting the highly parallel features of the open-source platform LAMMPS ([[http://lammps.sandia.gov/](http://lammps.sandia.gov/)]([http://lammps.sandia.gov/](http://lammps.sandia.gov/))). The COMPASS force field was adopted in all simulations [24]. All theory and simulation details/procedures are given in full in Appendix A. For the current application, the following systems were considered: System 1) Nylon 6 (PA6) loaded either with glass fibres (GFs) or carbon fibres (CFs); system 2) Nylon 6,6 (PA6,6) loaded either with glass fibres (GFs) or carbon fibres (CFs); system 3) poly(ether ether ketone) (PEEK) loaded with multi-wall carbon nanotubes (MWCNTs), and system 4) PEEK loaded with hydroxyapatite (HA). Systems 1 and 2 were selected as the best compromise between the potential cost and performance; PEEK was selected as the best compromise between performance and eco-compatibility; finally, system 4 was selected on the basis of the best eco-compatibility characteristics of both the polymeric matrix and filler. Furthermore, the choice of thermoplastic polymers mentioned above was based on several considerations, including good thermal and mechanical properties, market and price motivations, easy processability, and material recycling potential. The selected fillers are all endowed with excellent mechanical characteristics and can, at least in principle, impart elevated performance to the corresponding (nano)composite even when added in small amounts. In polymer (nano)composite systems, nanofillers are not regularly aligned in a determined direction but are randomly three-dimensionally distributed in the polymer matrix, then ensuring a macroscopically isotropic behaviour in the system. As a result, the isotropic behaviour assumption for the investigated materials is acceptable. The results obtained from the application of the CAMMD-based workflow for the prediction of mechanical properties--expressed via the value of the Young modulus E--for the different polymer (nano)composite systems considered are gathered in Figure 1 and Tables A1-A3. Figure 1A,B show that in the case of PA6 as the thermoplastic polymeric matrix (system 1) the predicted value of the Young modulus E significantly increases with filler content, reaching the values of 4.6 \(\pm\) 0.3 GPa (E\({}_{\text{f}}\) = 4.2) and 9.1 \(\pm\) 0.2 GPa (E\({}_{\text{f}}\) = 8.3) in the presence of 30% wt of GFs and CFs, respectively (Table A1). Simulations of the PA6,6-based systems (system 2) yielded analogous results, although, with respect to the corresponding PA6-based (nano) composites, higher values of E (and E\({}_{\text{f}}\)) are predicted at all filler concentrations considered, as shown in Figure 1C,D.