This comprehensive review discusses the recent progress in synthesis, properties, applications, 3D printing and machine learning of graphene quantum dots (GQDs) in polymer composites. It explores various synthesis methods, highlighting the size control and surface functionalization of GQDs. The unique electronic structure, tunable bandgap, and optical properties of GQDs are examined. Strategies for incorporating GQDs into polymer matrices and their effects on mechanical, electrical, thermal, and optical properties are discussed. Applications of GQD-based polymer composites in optoelectronics, energy storage, sensors, and biomedical devices are also reviewed. The challenges and future prospects of GQD-based composites are also explored, aiming to provide researchers with a comprehensive understanding of further advancements that should be possible in related fields. Moreover, this article explores new developments in 3D printing technology that can benefit from the promise of composite materials loaded with graphene quantum dots, a promising class of materials with a wide range of potential applications. In addition to discussing the synthesis and properties of GQDs, this review delves into the emerging role of machine learning techniques in optimising GQD-polymer composite materials. Furthermore, it explores how artificial intelligence and data-driven approaches are revolutionising the design and characterisation of these nanocomposites, enabling researchers to navigate the vast parameter space efficiently to achieve the desired properties. The overall aim of this review is to build up a common platform connecting individual subsections of synthesis, properties, applications, 3D printing and machine learning of GQD in polymer nanocomposites together to generate a comprehensive review for the readers.

中文翻译：

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聚合物纳米复合材料中石墨烯量子点的合成、性能、应用、3D打印和机器学习

这篇综合综述讨论了聚合物复合材料中石墨烯量子点 (GQD) 的合成、性能、应用、3D 打印和机器学习方面的最新进展。它探索了各种合成方法，重点介绍了 GQD 的尺寸控制和表面功能化。研究了 GQD 独特的电子结构、可调带隙和光学特性。讨论了将 GQD 纳入聚合物基体的策略及其对机械、电学、热学和光学性能的影响。还回顾了基于 GQD 的聚合物复合材料在光电子、储能、传感器和生物医学设备中的应用。还探讨了基于 GQD 的复合材料的挑战和未来前景，旨在让研究人员全面了解相关领域可能取得的进一步进展。此外，本文探讨了 3D 打印技术的新发展，该技术可以受益于装载石墨烯量子点的复合材料的前景，石墨烯量子点是一类具有广泛潜在应用前景的材料。除了讨论 GQD 的合成和性能之外，本综述还深入探讨了机器学习技术在优化 GQD-聚合物复合材料中的新兴作用。此外，它还探讨了人工智能和数据驱动的方法如何彻底改变这些纳米复合材料的设计和表征，使研究人员能够有效地导航巨大的参数空间以实现所需的性能。本综述的总体目标是建立一个通用平台，将聚合物纳米复合材料中 GQD 的合成、性能、应用、3D 打印和机器学习的各个部分连接在一起，为读者提供全面的综述。