Yousefi Mohammad Amin, Rahmatabadi Davood, Baniassadi Majid, Bodaghi Mahdi, Baghani Mostafa
School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, 1417614411, Iran.
Department of Engineering, School of Science and Technology, Nottingham Trent University, Nottingham, NG11 8NS, UK.
Macromol Rapid Commun. 2025 Jan;46(2):e2400661. doi: 10.1002/marc.202400661. Epub 2024 Oct 14.
4D printing magneto-responsive shape memory polymers (SMPs) using biodegradable nanocomposites can overcome their low toughness and thermal resistance, and produce smart materials that can be controlled remotely without contact. This study presented the development of 3D/4D printable nanocomposites based on poly (lactic acid) (PLA)-poly (butylene adipate-co-terephthalate) (PBAT) blends and magnetite (FeO) nanoparticles. The nanocomposites are prepared by melt mixing PLA-PBAT blends with different FeO contents (10, 15, and 20 wt%) and extruded into granules for material extrusion 3D printing. The morphology, dynamic mechanical thermal analysis (DMTA), mechanical properties, and shape memory behavior of the nanocomposites are investigated. The results indicated that the FeO nanoparticles are preferentially distributed in the PBAT phases, enhancing the storage modulus, thermal stability, strength, elongation, toughness, shape fixity, and recovery of the nanocomposites. The optimal FeO loading is found to be 10 wt%, as higher loadings led to nanoparticle agglomeration and reduced performance. The nanocomposites also exhibited fast shape memory response under thermal and magnetic activation due to the presence of FeO nanoparticles. The 3D/4D printable nanocomposites demonstrated multifunctional multi-trigger shape-memory capabilities and potential applications in contactless and safe actuation.
使用可生物降解的纳米复合材料打印4D磁响应形状记忆聚合物(SMP)可以克服其低韧性和耐热性,并生产出可远程无接触控制的智能材料。本研究展示了基于聚乳酸(PLA)-聚己二酸丁二醇酯-对苯二甲酸丁二醇酯(PBAT)共混物和磁铁矿(FeO)纳米颗粒的3D/4D可打印纳米复合材料的开发。通过将不同FeO含量(10%、15%和20%重量)的PLA-PBAT共混物熔融混合来制备纳米复合材料,并将其挤出成颗粒用于材料挤出3D打印。研究了纳米复合材料的形态、动态机械热分析(DMTA)、力学性能和形状记忆行为。结果表明,FeO纳米颗粒优先分布在PBAT相中,提高了纳米复合材料的储能模量、热稳定性、强度、伸长率、韧性、形状固定率和回复率。发现最佳FeO负载量为10%重量,因为更高的负载量会导致纳米颗粒团聚并降低性能。由于存在FeO纳米颗粒,纳米复合材料在热和磁激活下也表现出快速的形状记忆响应。这种3D/4D可打印纳米复合材料展示了多功能多触发形状记忆能力以及在非接触式和安全驱动方面的潜在应用。