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利用形状记忆聚合物克服粗糙表面的粘附悖论和切换冲突。

Overcoming the adhesion paradox and switchability conflict on rough surfaces with shape-memory polymers.

机构信息

School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore.

School of Materials Science and Engineering, Xiangtan University, Xiangtan, Hunan 411105, China.

出版信息

Proc Natl Acad Sci U S A. 2023 Mar 28;120(13):e2221049120. doi: 10.1073/pnas.2221049120. Epub 2023 Mar 20.

Abstract

Smart adhesives that can be applied and removed on demand play an important role in modern life and manufacturing. However, current smart adhesives made of elastomers suffer from the long-standing challenges of the adhesion paradox (rapid decrease in adhesion strength on rough surfaces despite adhesive molecular interactions) and the switchability conflict (trade-off between adhesion strength and easy detachment). Here, we report the use of shape-memory polymers (SMPs) to overcome the adhesion paradox and switchability conflict on rough surfaces. Utilizing the rubbery-glassy phase transition in SMPs, we demonstrate, through mechanical testing and mechanics modeling, that the conformal contact in the rubbery state followed by the shape-locking effect in the glassy state results in the so-called rubber-to-glass (R2G) adhesion (defined as making contact in the rubbery state to a certain indentation depth followed by detachment in the glassy state), with extraordinary adhesion strength (>1 MPa) proportional to the true surface area of a rough surface, overcoming the classic adhesion paradox. Furthermore, upon transitioning back to the rubbery state, the SMP adhesives can detach easily due to the shape-memory effect, leading to a simultaneous improvement in adhesion switchability (up to 10, defined as the ratio of the SMP R2G adhesion to its rubbery-state adhesion) as the surface roughness increases. The working principle and the mechanics model of R2G adhesion provide guidelines for developing stronger and more switchable adhesives adaptable to rough surfaces, thereby enhancing the capabilities of smart adhesives, and impacting various fields such as adhesive grippers and climbing robots.

摘要

能够按需施加和去除的智能粘合剂在现代生活和制造业中发挥着重要作用。然而,目前由弹性体制成的智能粘合剂存在长期存在的挑战,即粘合力悖论(尽管存在粘性分子相互作用,但在粗糙表面上的粘合力迅速下降)和可切换性冲突(粘合力和易于分离之间的权衡)。在这里,我们报告了使用形状记忆聚合物(SMP)来克服粗糙表面上的粘合力悖论和可切换性冲突。利用 SMP 中的橡胶-玻璃相转变,我们通过机械测试和力学建模证明,在橡胶状态下的一致接触随后在玻璃状态下的形状锁定效应导致所谓的橡胶-玻璃(R2G)粘附(定义为在橡胶状态下接触到一定的压痕深度,然后在玻璃状态下分离),具有非凡的粘附强度(>1 MPa)与粗糙表面的真实表面积成正比,克服了经典的粘附悖论。此外,在回到橡胶状态时,由于形状记忆效应,SMP 粘合剂可以很容易地分离,从而导致粘附可切换性的同时提高(高达 10,定义为 SMP R2G 粘附与其橡胶状态粘附的比值),随着表面粗糙度的增加。R2G 粘附的工作原理和力学模型为开发更强和更可切换的适应粗糙表面的粘合剂提供了指导,从而提高了智能粘合剂的能力,并影响了粘性夹具和攀爬机器人等各个领域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e640/10068835/e1d1940f2875/pnas.2221049120fig01.jpg

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