Developing high-performance materials with tailored properties is a key challenge that requires innovative molecular design methods. This study presents a machine learning-based approach, integrating Monte Carlo tree search and a recurrent neural network for the molecular design of polyamide systems, and we evaluate their properties with molecular dynamics simulations. By benchmarking against the performance of polyimides, we guide our algorithm to design sustainable polyamides with superior properties. A key consideration in our design approach is the incorporation of biodegradability as a critical design factor, in line with the growing demand for sustainable materials. We use an objective function targeting an optimal profile of low octanol–water partition coefficient (log P), high thermal stability (TS_ef), and substantial thermal conductivity (k). With 20 independent runs, which resulted in an evaluation of 133,655 monomers for design compatibility and generation of 5255 polyamide systems, our approach successfully designed promising 157 polyamide monomers, satisfying the criteria of log P < 0, TS_ef ≥ 2, and k ≥ 0.5 W/m K. These selections were validated by additional molecular dynamics (MD) calculations, revealing our objective function leads to sustainable and high-performance materials. Furthermore, we performed a detailed analysis of the structure–property relationship. Our algorithm successfully demonstrates the effectiveness of this integrated computational approach in guiding the design of novel polyamides.

中文翻译：

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高性能和可持续聚酰胺设计的综合框架

开发具有定制特性的高性能材料是一个关键挑战，需要创新的分子设计方法。本研究提出了一种基于机器学习的方法，集成了蒙特卡罗树搜索和循环神经网络，用于聚酰胺系统的分子设计，并通过分子动力学模拟评估其性能。通过对聚酰亚胺的性能进行基准测试，我们指导我们的算法设计具有卓越性能的可持续聚酰胺。我们设计方法中的一个关键考虑因素是将生物降解性作为关键设计因素，以满足对可持续材料不断增长的需求。我们使用的目标函数旨在实现低辛醇-水分配系数 (log P )、高热稳定性 (TS _ef ) 和高导热率 ( k ) 的最佳配置。通过 20 次独立运行，评估了 133,655 种单体的设计兼容性并生成了 5255 种聚酰胺系统，我们的方法成功设计了有前景的 157 种聚酰胺单体，满足 log P < 0、TS _ef ≥ 2 和k ≥ 0.5的标准W/m K。这些选择通过额外的分子动力学 (MD) 计算进行了验证，揭示了我们的目标函数可带来可持续的高性能材料。此外，我们对结构-性能关系进行了详细分析。我们的算法成功证明了这种集成计算方法在指导新型聚酰胺设计方面的有效性。