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A Framework for Designing Novel Magnetic Tiles Capable of Complex Self-assemblies

机译:设计能够复杂的自组装的新型磁力砖的框架

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Self-assembly has been immensely successful in creating complex patterns at the molecular scale. However, the use of self-assembly techniques at the macroscopic level has so far been limited to the formation of simple patterns. For example, in a number of prior works, self-assembling units or tiles formed aggregates based on the polarity of magnetic pads on their sides. The complexity of the resulting assemblies was limited, however, due to the small variety of magnetic pads that were used: namely just positive or negative polarity. This paper addresses the key challenge of increasing the variety of magnetic pads for tiles, which would allow the tiles to self-assemble into more complex patterns. We introduce a barcode scheme which potentially allows for the generation of arbitrarily complex structures using magnetic self-assembly at the macro-scale. Development of a framework for designing such barcode schemes is the main contribution of the paper. We also present a physical model based On Newtonian mechanics and Maxwellian magnetics. Additionally, we present a preliminary software simulation system that models the binding of these tiles using magnetic interactions as well as external forces (e.g. wind) which provide energy to the system. Although we have not performed any physical experiments, nevertheless, we show that it is possible to use the simulation results to extract a higher level kinetic model that can be used to predict assembly yield on a larger scale and provide better insight into the dynamics of the real system.
机译:自我组装在分子尺度创造复杂的模式方面已经完全成功。然而,到目前为止,在宏观层面上使用自组装技术仅限于形成简单模式的形成。例如,在许多现有的作品中,自组装单元或瓷砖基于它们侧面上的磁焊盘的极性形成的聚集体。然而,由于所用的磁焊盘各种磁焊盘,所得组件的复杂性受到限制:即阳性或负极性。本文解决了增加瓷砖各种磁焊盘的关键挑战,这将允许瓷砖自动组装成更复杂的图案。我们介绍了一个条形码方案,该条形码方案可能允许在宏观规模处使用磁性自组装生成任意复杂的结构。开发设计这些条形码方案的框架是纸张的主要贡献。我们还介绍了基于牛顿力学和Maxwellian Magnicics的物理模型。此外,我们提供了一种初步的软件仿真系统,其使用磁相互作用和为系统提供能量的外力(例如风)来模拟这些瓷砖的绑定。尽管我们没有进行任何物理实验,但是,我们表明可以使用模拟结果来提取更高级别的动力学模型,该模型可用于预测大规模的装配产量,并提供更好地深入了解动态真实的系统。

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