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1. Identification and Quantification of 3D Fiber Clusters in Fiber-Reinforced Composite Materials

   https://doi.org/10.1007/s11837-021-04703-0  

   Schey, Mathew J. ; Beke, Tibor ; Appel, Lars ; Zabler, Simon ; Shah, Sagar ; Hu, Jie ; Liu, Fuqiang ; Maiaru, Marianna ; Stapleton, Scott ( July 2021 , JOM)

   null (Ed.)
2. More Stiffness with Less Fiber: End-to-End Fiber Path Optimization for 3D-Printed Composites

   Sun, Xingyuan ; Roeder, Geoffrey ; Xue, Tianju ; Adams, Ryan P. ; Rusinkiewicz, Szymon ( October 2023 , ACM Symposium on Computational Fabrication)
3. Enhancing the Interlaminar Shear Strength and Void Control of 3D-Printed Continuous Carbon-Fiber-Reinforced Polymer Composites Using a Robotic Magnetic Compaction Force-Assisted Additive Manufacturing (MCFA-AM) Process and Carbon-Nanofiber Z-Threads

   https://doi.org/10.3390/app13105914  

   Islam, Mohammad Rakibul ; Taylor, Wyatt ; Warren, Ryan ; Hsiao, Kuang-Ting ( May 2023 , Applied Sciences)

   Manoj Gupta (Ed.)

   Three-dimensional (3D) printing with continuous carbon-fiber-reinforced polymer (C-CFRP) composites is under increasing development, as it offers more versatility than traditional molding processes, such as the out-of-autoclave-vacuum bag only (OOA-VBO) process. However, due to the layer-by-layer deposition of materials, voids can form between the layers and weaken some of the parts’ properties, such as the interlaminar shear strength (ILSS). In this paper, a novel mold-less magnetic compaction force-assisted additive manufacturing (MCFA-AM) method was used to print carbon nanofiber (CNF) z-threaded CFRP (ZT-CFRP) laminates with significantly improved ILSS and reduced void content compared to traditional C-CFRP laminates, which are printed using a no-pressure 3D-printing process (similar to the fused-deposition-modeling process). The radial flow alignment (RFA) and resin-blending techniques were utilized to manufacture a printing-compatible fast-curing ZT-CFRP prepreg tape to act as the feedstock for a MCFA-AM printhead, which was mounted on a robotic arm. In terms of the ILSS, the MCFA-AM method coupled with ZT-CFRP nanomaterial technology significantly outperformed the C-CFRP made with both the traditional no-pressure 3D-printing process and the OOA-VBO molding process. Furthermore, the mold-less MCFA-AM process more than doubled the production speed of the OOA-VBO molding process. This demonstrates that through the integration of new nanomaterials and 3D-printing techniques, a paradigm shift in C-CFRP manufacturing with significantly better performance, versatility, agility, efficiency, and lower cost is achievable.

    

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4. PunchPrint: Creating Composite Fiber-Filament Craft Artifacts by Integrating Punch Needle Embroidery and 3D Printing

   https://doi.org/10.1145/3544548.3581298  

   Del Valle, Ashley ; Toka, Mert ; Aponte, Alejandro ; Jacobs, Jennifer ( April 2023 , 2023 CHI Conference on Human Factors in Computing Systems (CHI '23))

   New printing strategies have enabled 3D-printed materials that imitate traditional textiles. These filament-based textiles are easy to fabricate but lack the look and feel of fiber textiles. We seek to augment 3D-printed textiles with needlecraft to produce composite materials that integrate the programmability of additive fabrication with the richness of traditional textile craft. We present PunchPrint: a technique for integrating fiber and filament in a textile by combining punch needle embroidery and 3D printing. Using a toolpath that imitates textile weave structure, we print a flexible fabric that provides a substrate for punch needle production. We evaluate our material’s robustness through tensile strength and needle compatibility tests. We integrate our technique into a parametric design tool and produce functional artifacts that show how PunchPrint broadens punch needle craft by reducing labor in small, detailed artifacts, enabling the integration of openings and multiple yarn weights, and scaffolding soft 3D structures. 

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5. Connected-tube MPP Model for unsupervised 3D fiber detection

   https://doi.org/10.2352/ISSN.2470-1173.2020.14.COIMG-305  

   Li, Tianyu ; Aguilar, Camilo G. ; Agyei, Ronald F. ; Hanhan, Imad A. ; Sangid, Michael D. ; Comer, Mary L. ( January 2020 , Electronic Imaging)

   Fast track article for IS&T International Symposium on Electronic Imaging 2020: Computational Imaging proceedings. 

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