Molecular Dynamics Simulation of the Stress–Strain Behavior of Polyamide Crystals

Artificial Neural Networks for Predicting Mechanical Properties of Crystalline Polyamide12 via Molecular Dynamics Simulations

Predicting material properties of 3D printed polymer products is a challenge in additive manufacturing due to the highly localized and complex manufacturing process. The microstructure of such products is fundamentally different from the ones obtained by using conventional manufacturing methods, which makes the task even more difficult. As the first step of a systematic multiscale approach, in this work, we have developed an artificial neural network (ANN) to predict the mechanical properties of the crystalline form of Polyamide12 (PA12) based on data collected from molecular dynamics (MD) simulations. Using the machine learning approach, we are able to predict the stress-strain relations of PA12 once the macroscale deformation gradient is provided as an input to the ANN. We have shown that this is an efficient and accurate approach, which can provide a three-dimensional molecular-level anisotropic stress-strain relation of PA12 for any macroscale mechanics model, such as finite element modeling at arbitrary quadrature points. This work lays the foundation for a multiscale finite element method for simulating semicrystalline polymers, which will be published as a separate study.

Probabilistic Approach to Low Strain Rate Atomistic Simulations of Ultimate Tensile Strength of Polymer Crystals

Molecular dynamics simulations of the tensile ultimate properties of polymer crystals require the use of empirical potentials that model bond dissociation. However, fully reactive potentials are computationally expensive such that reactive simulations cannot reach the low strain rates of typical experiments. Here, we present a hybrid approach that uses the simplicity of a classical, nonreactive potential, information from bond dissociation energy calculations, and a probabilistic expression that mimics bond breaking. The approach is demonstrated for poly(p-phenylene terephthalamide) and, with one tunable parameter, the calculated tensile ultimate stress matches that obtained using a fully reactive simulation at high strain rates. Then, the hybrid simulations are run at much lower strain rates where the ultimate tensile stress is strain rate-independent and consistent with the expected experimental range.

Accelerated Design of Ultra-High-Performance Aramid Copolymers via a High-Throughput Screening Approach

Developing advanced materials, such as functional polymers, poses a significant challenge as a result of the vastness of the material space that needs to be explored, which could potentially be infinite in principle. We propose a data-driven high-throughput screening approach coupled with molecular dynamics (MD) simulations to address this issue in the design of high-performance co-polymerized aramid fibers. We aimed to identify diamine monomers that could replace 3,4'-oxydianiline in Technora from a large-scale set (1 920 304) of possible monomers that were prepared from the PubChem database. We initially screened these monomers using a cheminformatics-based approach, considering four criteria: complexity, neutrality, linearity, and gyration radius of the molecule. Then, we performed subsequent screening based on MD simulations to estimate interchain interaction energies under both stretched and melted conditions and tensile strength simulations. Our screening approach successfully identified 31 promising and novel diamine monomers for aramid copolymers. This demonstrates the potential and effectiveness of our approach as a promising protocol for exploring targeted chemical spaces in designing novel monomers for high-performance aramid fibers and possibly other advanced polymers.

Methanol-Assisted ADMET Polymerization of Semiaromatic Amides

A method for the acyclic diene metathesis polymerization of semiaromatic amides is described. The procedure uses second-generation Grubbs' catalyst and N-cyclohexyl-2-pyrrolidone (CHP), a high boiling, polar solvent capable of solubilizing both monomer and polymer. The addition of methanol to the reaction was found to significantly increase polymer molar mass although the role of the alcohol is currently not understood. Hydrogenation with hydrogen gas and Wilkinson's catalyst resulted in near-quantitative saturation. All polymers synthesized here exhibit a hierarchical semicrystalline morphology driven by ordering of aromatic amide groups via strong nonbonded interactions. Furthermore, the melting points can be tuned over a >100 °C range by precise substitution at just one of the backbone positions on each mer (<5% of the total).

Anisotropic atomistic shock response mechanisms of aramid crystals

Aramid fibers composed of poly(p-phenylene terephthalamide) (PPTA) polymers are attractive materials due to their high strength, low weight, and high shock resilience. Even though they have widely been utilized as a basic ingredient in Kevlar, Twaron, and other fabrics and applications, their intrinsic behavior under intense shock loading is still to be understood. In this work, we characterize the anisotropic shock response of PPTA crystals by performing reactive molecular dynamics simulations. Results from shock loading along the two perpendicular directions to the polymer backbones, [100] and [010], indicate distinct shock release mechanisms that preserve and destroy the hydrogen bond network. Shocks along the [100] direction for particle velocity U_p < 2.46 km/s indicate the formation of a plastic regime composed of shear bands, where the PPTA structure is planarized. Shocks along the [010] direction for particle velocity U_p < 2.18 km/s indicate a complex response regime, where elastic compression shifts to amorphization as the shock is intensified. While hydrogen bonds are mostly preserved for shocks along the [100] direction, hydrogen bonds are continuously destroyed with the amorphization of the crystal for shocks along the [010] direction. Decomposition of the polymer chains by cross-linking is triggered at the threshold particle velocity U_p = 2.18 km/s for the [010] direction and U_p = 2.46 km/s for the [100] direction. These atomistic insights based on large-scale simulations highlight the intricate and anisotropic mechanisms underpinning the shock response of PPTA polymers and are expected to support the enhancement of their applications.