Atomistic Simulations to Understand Molecular Mechanics

Vitrimers, a promising class of sustainable polymers, are composed of dynamic covalent networks that enable reprocessability and recyclability through bond-exchange reactions. However, current modeling approaches fail to fully capture the reaction pathways, limiting the understanding of vitrimers' viscoelastic properties. This work addresses this gap by extending and applying the Accelerated ReaxFF technique (also known as the "bond boost" method). We employ Bayesian optimization for force parameter selection and introduce an empirical function to model the temperature dependence of reaction probabilities. The extended framework is used to simulate the nonisothermal creep behavior of vitrimers under varied stress levels, heating rates, and numbers of reactions. The simulation results agree with experimental observations in the literature, validating the efficacy of the framework and providing molecular insights into vitrimer viscoelasticity. https://doi.org/10.1021/acs.macromol.5c00501

Vitrimer is a new class of sustainable polymers with the ability of self-healing through rearrangement of dynamic covalent adaptive networks. However, a limited choice of constituent molecules restricts their property space, prohibiting full realization of their potential applications. Through a combination of molecular dynamics (MD) simulations and machine learning (ML), particularly a novel graph variational autoencoder (VAE) model, we establish a method for generating novel vitrimers and guide their inverse design based on desired glass transition temperature (Tg). We build the first vitrimer dataset of one million and calculate Tg on 8,424 of them by high-throughput MD simulations calibrated by a Gaussian process model. The proposed VAE employs dual graph encoders and a latent dimension overlapping scheme which allows for individual representation of multi-component vitrimers. By constructing a continuous latent space containing necessary information of vitrimers, we demonstrate high accuracy and efficiency of our framework in discovering novel vitrimers with desirable Tg beyond the training regime. The proposed vitrimers with reasonable synthesizability cover a wide range of Tg and broaden the potential widespread usage of vitrimeric materials.  https://doi.org/10.1002/advs.202411385