Zheng Yiwen, Thakolkaran Prakash, Biswal Agni K, Smith Jake A, Lu Ziheng, Zheng Shuxin, Nguyen Bichlien H, Kumar Siddhant, Vashisth Aniruddh
Department of Mechanical Engineering, University of Washington, Seattle, WA, 98195, USA.
Department of Materials Science and Engineering, Delft University of Technology, Delft, CD, 2628, The Netherlands.
Adv Sci (Weinh). 2025 Feb;12(6):e2411385. doi: 10.1002/advs.202411385. Epub 2024 Dec 16.
Vitrimer is a new, exciting class of sustainable polymers with healing abilities due to their dynamic covalent adaptive networks. However, a limited choice of constituent molecules restricts their property space and potential applications. To overcome this challenge, an innovative approach coupling molecular dynamics (MD) simulations and a novel graph variational autoencoder (VAE) model for inverse design of vitrimer chemistries with desired glass transition temperature (T) is presented. The first diverse vitrimer dataset of one million chemistries is curated and T for 8,424 of them is calculated 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. High accuracy and efficiency of the framework are demonstrated by discovering novel vitrimers with desirable T beyond the training regime. To validate the effectiveness of the framework in experiments, vitrimer chemistries are generated with a target T = 323 K. By incorporating chemical intuition, a novel vitrimer with T of 311-317 K is synthesized, experimentally demonstrating healability and flowability. The proposed framework offers an exciting tool for polymer chemists to design and synthesize novel, sustainable polymers for various applications.
玻璃转化弹性体是一类新型的、令人兴奋的可持续聚合物，由于其动态共价自适应网络而具有自愈能力。然而，组成分子的选择有限限制了它们的性能空间和潜在应用。为了克服这一挑战，本文提出了一种创新方法，将分子动力学（MD）模拟与一种新颖的图变分自编码器（VAE）模型相结合，用于逆设计具有所需玻璃化转变温度（T）的玻璃转化弹性体化学结构。整理了第一个包含一百万个化学结构的多样化玻璃转化弹性体数据集，并通过由高斯过程模型校准的高通量MD模拟计算了其中8424个结构的T值。所提出的VAE采用双图编码器和潜在维度重叠方案，允许对多组分玻璃转化弹性体进行单独表示。通过发现训练范围之外具有所需T值的新型玻璃转化弹性体，证明了该框架的高精度和高效率。为了在实验中验证该框架的有效性，生成了目标T = 323 K的玻璃转化弹性体化学结构。通过结合化学直觉，合成了一种T值为311 - 317 K的新型玻璃转化弹性体，实验证明了其自愈性和流动性。所提出的框架为聚合物化学家设计和合成用于各种应用的新型可持续聚合物提供了一个令人兴奋的工具。
