High-stability polyimides exhibit tremendous potential for applications in flexible electronics, fibers, and membrane materials. However, screening polyimide structures with superior performance remains a significant challenge. In this study, we combined literature data, machine learning, and molecular dynamics simulations to identify key factors influencing the stability of polyimide structures and screen for high-stability polyimide candidates. Specifically, we utilized interpretable machine learning methods to analyze polyimide systems documented in the literature, aiming to identify crucial substructures that impact polyimide stability. This approach offers valuable insights for the development of high-stability polymers. By integrating diamine and dianhydride structures from both the PubChem database and the literature, we generated a data set containing over 15 million hypothetical polyimides. Using appropriate machine learning models, we conducted high-throughput screening to discover polyimides that simultaneously exhibit high thermal stability and excellent mechanical properties. The selected machine learning models demonstrated strong predictive capability in forecasting four key properties: glass transition temperature (T_g), Young’s modulus (Y_m), tensile strength (T_s), and elongation at break (E_g). Based on the predictions from the optimal models and synthetic accessibility scores, we ultimately identified eight polyimide copolymer structures with outstanding stability, with some of their properties validated through all-atom molecular dynamics simulations.

中文翻译：

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基于机器学习的高稳定性聚酰亚胺高通量筛选


高稳定性聚酰亚胺在柔性电子、纤维和膜材料中表现出巨大的应用潜力。然而，筛选具有卓越性能的聚酰亚胺结构仍然是一项重大挑战。在这项研究中，我们结合了文献数据、机器学习和分子动力学模拟，以确定影响聚酰亚胺结构稳定性的关键因素，并筛选高稳定性的聚酰亚胺候选物。具体来说，我们利用可解释的机器学习方法来分析文献中记录的聚酰亚胺系统，旨在确定影响聚酰亚胺稳定性的关键子结构。这种方法为高稳定性聚合物的开发提供了有价值的见解。通过整合来自 PubChem 数据库和文献的二胺和二酐结构，我们生成了一个包含超过 1500 万个假设聚酰亚胺的数据集。使用适当的机器学习模型，我们进行了高通量筛选，以发现同时表现出高热稳定性和优异机械性能的聚酰亚胺。选定的机器学习模型在预测玻璃化转变温度 （T_g）、杨氏模量 （Y_m）、拉伸强度 （TS_{） 和}断裂伸长率 （E_g） 四个关键特性方面表现出很强的预测能力。根据最优模型的预测和合成可及性分数，我们最终确定了八种具有出色稳定性的聚酰亚胺共聚物结构，它们的一些特性通过全原子分子动力学模拟得到了验证。