Fluid-Mediated Stochastic Self-Assembly at Centimetric and Sub-Millimetric Scales: Design, Modeling, and Control

厘米级和亚毫米级流体介导的随机自组装:设计、建模和控制

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Abstract

Stochastic self-assembly provides promising means for building micro-/nano-structures with a variety of properties and functionalities. Numerous studies have been conducted on the control and modeling of the process in engineered self-assembling systems constituted of modules with varied capabilities ranging from completely reactive nano-/micro-particles to intelligent miniaturized robots. Depending on the capabilities of the constituting modules, different approaches have been utilized for controlling and modeling these systems. In the quest of a unifying control and modeling framework and within the broader perspective of investigating how stochastic control strategies can be adapted from the centimeter-scale down to the (sub-)millimeter-scale, as well as from mechatronic to MEMS-based technology, this work presents the outcomes of our research on self-assembly during the past few years. As the first step, we leverage an experimental platform to study self-assembly of water-floating passive modules at the centimeter scale. A dedicated computational framework is developed for real-time tracking, modeling and control of the formation of specific structures. Using a similar approach, we then demonstrate controlled self-assembly of microparticles into clusters of a preset dimension in a microfluidic chamber, where the control loop is closed again through real-time tracking customized for a much faster system dynamics. Finally, with the aim of distributing the intelligence and realizing programmable self-assembly, we present a novel experimental system for fluid-mediated programmable stochastic self-assembly of active modules at the centimeter scale. The system is built around the water-floating 3-cm-sized Lily robots specifically designed to be operative in large swarms and allows for exploring the whole range of fully-centralized to fully-distributed control strategies. The outcomes of our research efforts extend the state-of-the-art methodologies for designing, modeling and controlling massively-distributed, stochastic self-assembling systems at different length scales, constituted of modules from centimetric down to sub-millimetric size. As a result, our work provides a solid milestone in structure formation through controlled self-assembly.

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