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用于可编程粘合剂的多尺度裂纹捕获

Multiscale crack trapping for programmable adhesives.

作者信息

Park Seongjin, Kang Dong Kwan, Lee Donghyuk, Choi Geonjun, Kim Jaeil, Lee Chanhong, Seong Minho, Bartlett Michael D, Jeong Hoon Eui

机构信息

Department of Mechanical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.

Department of Mechanical Engineering, Soft Materials and Structures Lab, Virginia Tech, Blacksburg, VA, USA.

出版信息

Sci Adv. 2024 Sep 13;10(37):eadq3438. doi: 10.1126/sciadv.adq3438. Epub 2024 Sep 11.

Abstract

The precise control of crack propagation at bonded interfaces is crucial for smart adhesives with advanced performance. However, previous studies have primarily concentrated on either microscale or macroscale crack propagation. Here, we present a hybrid adhesive that integrates microarchitectures and macroscopic nonlinear cut architectures for unparalleled adhesion control. The integration of these architectural elements enables conformal attachment and simultaneous crack trapping across multiple scales for high capacity, enhancing adhesion by more than 70×, while facilitating crack propagation at the macroscale in specific directions for programmable release and reusability. As adhesion strength and directionality can be independently controlled at any location, skin adhesive patches are created that are breathable, nondamaging, and exceptionally strong and secure yet remove easily. These capabilities are demonstrated with a skin-mounted adhesive patch with integrated electronics that accurately detects human motion and wirelessly transmits signals, enabling real-time control of avatars in virtual reality applications.

摘要

对于具有先进性能的智能粘合剂而言,精确控制粘结界面处的裂纹扩展至关重要。然而,先前的研究主要集中在微观尺度或宏观尺度的裂纹扩展上。在此,我们展示了一种混合粘合剂,它集成了微结构和宏观非线性切割结构,以实现无与伦比的粘附控制。这些结构元素的整合实现了保形附着,并能在多个尺度上同时捕获裂纹,从而实现高承载能力,使粘附力提高70多倍,同时在宏观尺度上促进裂纹在特定方向上的扩展,以实现可编程释放和可重复使用。由于粘附强度和方向性可以在任何位置独立控制,因此可以制造出透气、无损伤、异常牢固且安全但易于移除的皮肤粘贴片。通过带有集成电子器件的皮肤粘贴片展示了这些功能,该粘贴片能够精确检测人体运动并无线传输信号,从而在虚拟现实应用中实现对虚拟化身的实时控制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7e20/11389778/f27e71f22e57/sciadv.adq3438-f1.jpg

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