The dynamic loading behavior of materials plays a vital role in various engineering applications, such as aerospace protective components, armor, marine infrastructures, and automotive crash safety. The advent of additive manufacturing technologies has enabled the design of metamaterials that exhibit exceptional mechanical performance and artificially engineered properties not found in nature. However, fabricating ideal materials that resist dynamic loading is challenging because of the complexity of dynamic mechanical processes and varying requirements across different applications. In this study, a novel hierarchical design is proposed that combines natural fiber-inspired frameworks with graphene-inspired parent structures. This design aims to produce metamaterials, with characteristics such as reduced dynamic compressive strength, high energy absorption, and programmable dynamic loading, via advanced manufacturing technologies. An additive-manufacturing-oriented digital design approach and machine learning techniques were employed to engineer the dynamic loading performance of graphene-inspired metamaterials using the bonding principles inspired by natural fibers, to facilitate the design of next-generation metamaterial for advanced manufacturing. Experimental results illustrate the significant improvements achieved with our metamaterials compared to their existing counterparts. These improvements include a decrease in dynamic compressive strength of up to 86 %, while maintaining a remarkable 682 % enhancement in energy absorption during dynamic compressions, with a 42 % reduction in the energy decay rate. A compositional design strategy and programmable dynamic compression curve methodology is proposed that enable the tailored optimization of dynamic loading behaviors without modifying the base topology of metamaterials. This research offers a promising pathway for the development of next-generation materials, engineered to withstand dynamic loadings with intelligent and programmable performances suitable for aerospace, defense, and other high-value applications. By leveraging the advantages of natural fiber-inspired structures and graphene-inspired metamaterials, this work contributes to the advancement of materials with tailored resistance to dynamic loading and opens new possibilities for intelligent dynamic loading performance.

材料的动态加载行为在各种工程应用中发挥着至关重要的作用，例如航空航天防护部件、装甲、海洋基础设施和汽车碰撞安全。增材制造技术的出现使得超材料的设计成为可能，这些材料表现出自然界中不存在的卓越机械性能和人工工程特性。然而，由于动态机械过程的复杂性以及不同应用的不同要求，制造抵抗动态载荷的理想材料具有挑战性。在这项研究中，提出了一种新颖的分层设计，将天然纤维启发的框架与石墨烯启发的母体结构相结合。该设计旨在通过先进的制造技术生产具有降低动态压缩强度、高能量吸收和可编程动态加载等特性的超材料。采用面向增材制造的数​​字设计方法和机器学习技术，利用天然纤维启发的粘合原理来设计石墨烯超材料的动态加载性能，以促进用于先进制造的下一代超材料的设计。实验结果表明，与现有的同类材料相比，我们的超材料取得了显着的改进。这些改进包括动态压缩强度降低高达 86%，同时在动态压缩过程中能量吸收显着增强 682%，能量衰减率降低 42%。提出了组合设计策略和可编程动态压缩曲线方法，可以在不修改超材料基础拓扑的情况下实现动态加载行为的定制优化。这项研究为开发下一代材料提供了一条有前途的途径，这些材料旨在承受动态载荷，具有适合航空航天、国防和其他高价值应用的智能和可编程性能。通过利用天然纤维结构和石墨烯超材料的优势，这项工作有助于改进具有定制动态负载能力的材料，并为智能动态负载性能开辟新的可能性。