Collaborative Research: FET: Small: Algorithmic Self-Assembly with Crisscross Slats

该项目利用所有生物体的基本遗传物质DNA作为纳米级结构的建筑材料。这项研究的潜在影响涵盖多个领域，包括医疗保健，它可能导致疾病检测和治疗的突破，以及纳米工程，为纳米级制造提供新方法。利用DNA固有的碱基配对特性，该项目采用了一种称为板条组装的新策略，其中DNA序列被设计成折叠成细长的板条，然后拼凑在一起形成复杂的几何形状。这种方法的目的是规避以前的DNA组装方法的局限性，特别是与构建更大结构相关的高成本和错误率。板条组装可以大大降低这些障碍，从而能够创建更复杂和更大的纳米结构。 此外，通过将这些进步融入学术课程，该项目还旨在为新一代科学家提供必要的跨学科技能，以推动科学可能性的界限。该项目的重点是完善和推进基于板条的DNA组装，作为DNA纳米技术目前面临的挑战的解决方案，特别是与算法自组装相关的错误和硬编码方法的可扩展性问题。研究小组将对缝翼组装进行系统的探索，从计算机模拟开始，设计基于DNA的缝翼系统，以减轻生长误差。这些理论设计将通过一系列增量实验进行实证检验。初始阶段将复制并简化现有的基于slat的图案，然后发展能够任意大小扩展的图案。这为在这些可扩展平台中实现算法增长模式奠定了基础，这是该领域的一项新奋进。该项目包括设计可变长度和形状的板条，这是一种需要精确控制和超越现有方法的创新技术。这些策略的成功实施将证明使用板条的算法增长的可行性，例如构建一个离散版本的谢尔宾斯基三角形。该项目代表了实现可扩展的，错误最小化的DNA纳米结构组装的关键一步，该项目由计算和通信基础部的新兴技术基础计划和刺激竞争研究的既定计划（EPSCoR）联合资助。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project utilizes DNA, the fundamental genetic material of all living organisms, as a construction material for nano-scale structures. The potential impact of this research spans multiple fields, including healthcare, where it could lead to breakthroughs in disease detection and treatment, and nano-engineering, offering new methods for manufacturing at the nanoscale. Leveraging the inherent base-pairing properties of DNA, the project employs a novel strategy known as slat assembly, where DNA sequences are designed to fold into elongated slats that then piece together to form complex geometries. This approach aims to circumvent the limitations of previous DNA assembly methods—specifically, the high costs and error rates associated with constructing larger structures. Slat assembly stands to substantially lower these barriers, enabling the creation of more intricate and vast nanostructures. Furthermore, by integrating these advancements into academic curricula, the project also seeks to equip a new generation of scientists with the interdisciplinary skills necessary to push the boundaries of what is scientifically possible.The focus of this project is to refine and advance slat-based DNA assembly as a solution to the challenges currently faced in DNA nanotechnology, specifically the errors associated with algorithmic self-assembly and the scalability issues of hard-coded approaches. The research team will engage in a systematic exploration of slat assembly, starting with computer simulations to design DNA-based slat systems that promise to mitigate growth errors. These theoretical designs will be brought to empirical testing through a series of incremental experiments. Initial phases will replicate and then simplify existing slat-based motifs, progressing to the development of motifs capable of arbitrary size expansion. This sets the groundwork for implementing algorithmic growth patterns within these scalable platforms, a novel endeavor within the field. The project includes designing slats of variable lengths and shapes, a technique that requires precise control and innovation beyond current methodologies. Successful implementation of these strategies will demonstrate the feasibility of algorithmic growth using slats, exemplified by constructing a discrete version of the Sierpinski triangle. This project represents a pivotal step towards achieving scalable, error-minimized assembly of DNA nanostructures, with significant implications for the future of nanotechnology and its applications across various disciplines.This project is jointly funded by the Foundations of Emerging Technologies program in the Division of Computing and Communication Foundations and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.