Emery Brett, Snapp Kelsey L, Revier Daniel, Sarkar Vivek, Nakura Masa, Brown Keith A, Lipton Jeffrey Ian
Department of Mechanical and Industrial Engineering, Northeastern University, 815 Columbus Ave, Boston, MA, 02120, USA.
Department of Mechanical Engineering, Boston University, 110 Cummington Mall College of Engineering, Boston, MA, 02215, USA.
Adv Sci (Weinh). 2024 Nov;11(44):e2408062. doi: 10.1002/advs.202408062. Epub 2024 Sep 27.
Foams are versatile by nature and ubiquitous in a wide range of applications, including padding, insulation, and acoustic dampening. Previous work established that foams 3D printed via Viscous Thread Printing (VTP) can in principle combine the flexibility of 3D printing with the mechanical properties of conventional foams. However, the generality of prior work is limited due to the lack of predictable process-property relationships. In this work, a self-driving lab is utilized that combines automated experimentation with machine learning to identify a processing subspace in which dimensionally consistent materials are produced using VTP with spatially programmable mechanical properties. In carrying out this process, an underlying self-stabilizing characteristic of VTP layer thickness is discovered as an important feature for its extension to new materials and systems. Several complex exemplars are constructed to illustrate the newly enabled capabilities of foams produced via VTP, including 1D gradient rectangular slabs, 2D localized stiffness zones on an insole orthotic and living hinges, and programmed 3D deformation via a cable-driven humanoid hand. Predictive mapping models are developed and validated for both thermoplastic polyurethane (TPU) and polylactic acid (PLA) filaments, suggesting the ability to train a model for any material suitable for material extrusion (ME) 3D printing.
泡沫本质上具有多种用途，在广泛的应用中无处不在，包括衬垫、隔热和隔音。先前的研究表明，通过粘性丝印刷（VTP）3D打印的泡沫原则上可以将3D打印的灵活性与传统泡沫的机械性能结合起来。然而，由于缺乏可预测的工艺-性能关系，先前研究的普遍性受到限制。在这项工作中，利用了一个自动驾驶实验室，该实验室将自动化实验与机器学习相结合，以识别一个加工子空间，在该子空间中，使用具有空间可编程机械性能的VTP生产尺寸一致的材料。在进行这个过程中，发现VTP层厚度的潜在自稳定特性是将其扩展到新材料和系统的一个重要特征。构建了几个复杂的示例来说明通过VTP生产的泡沫新具备的能力，包括一维梯度矩形板、鞋垫矫形器和活动铰链上的二维局部刚度区域，以及通过电缆驱动的人形手进行的编程3D变形。针对热塑性聚氨酯（TPU）和聚乳酸（PLA）长丝开发并验证了预测映射模型，这表明有能力为任何适合材料挤出（ME）3D打印的材料训练模型。
