Physical Chemistry and Soft Matter, Wageningen University & Research, Wageningen 6708 WE, Netherlands.
BioNano Technology, Wageningen University & Research, Wageningen 6700 EK, Netherlands.
Biointerphases. 2021 Jan 19;16(1):011002. doi: 10.1116/6.0000634.
Probabilistic fasteners are known to provide strong attachment onto their respective surfaces. Examples are Velcro® and the "3M dual lock" system. However, these systems typically only function using specific counter surfaces and are often destructive to other surfaces such as fabrics. Moreover, the design parameters to optimize their functionality are not obvious. Here, we present a surface patterned with soft micrometric features inspired by the mushroom shape showing a nondestructive mechanical interlocking and thus attachment to fabrics. We provide a scalable experimental approach to prepare these surfaces and quantify the attachment strength with rheometric and video-based analysis. In these "probabilistic fasteners," we find that higher feature densities result in higher attachment force; however, the individual feature strength is higher on a low feature density surface. We interpret our results via a load-sharing principle common in fiber bundle models. Our work provides new handles for tuning the mechanical attachment properties of soft patterned surfaces that can be used in various applications including soft robotics.
概率紧固件以其在各自表面的强附着性而闻名。例如 Velcro®和“3M 双锁”系统。然而，这些系统通常仅使用特定的反面来发挥功能，并且经常对其他表面（如织物）具有破坏性。此外，优化其功能的设计参数并不明显。在这里，我们展示了一种受蘑菇形状启发的带有软微观特征的表面图案，它具有非破坏性的机械互锁，从而可以附着在织物上。我们提供了一种可扩展的实验方法来制备这些表面，并通过流变和基于视频的分析来量化附着强度。在这些“概率紧固件”中，我们发现较高的特征密度会导致较高的附着力；但是，在特征密度较低的表面上，单个特征的强度更高。我们通过纤维束模型中常见的负载共享原理来解释我们的结果。我们的工作为软图案化表面的机械附着性能提供了新的调节手段，可用于包括软机器人在内的各种应用。
