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AF:Small:Collaborative Research:Kinetics and Thermodynamics of Chemical Computation

AF：小：协作研究：化学计算的动力学和热力学

基本信息

批准号：
1618895
负责人：
David Soloveichik
金额：
$ 24.99万
依托单位：
University of Texas at Austin
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2016
资助国家：
美国
起止时间：
2016-06-01 至 2020-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1618895&HistoricalAwards=false
关键词：
AF Small Collaborative Research Kinetics

项目摘要

Biology is replete with smart molecular systems that perform nanoscale assembly, sense environmental stimuli, create chemical signals, and produce physical motion - each of these tasks coordinated by information processing circuits implemented with chemical reactions. Learning how to build artificial chemicals that compute autonomously in complex environments would bring about groundbreaking advances in manufacturing, chemical sensing, and medicine. The theory of computation has proven invaluable in enabling information processing in electronic man-made systems, and much-studied algorithms underlie the behavior of everything from communication networks to video games. However, a thorough understanding of the principles of chemical computation is still lacking. The goal of this proposal is to use rigorous mathematical models to investigate the capabilities and limitations of chemical information processing.The proposed research will bring the fields of physics, chemistry, biology, and computer science closer intellectually and mutually enrich them. For example, conceptual frameworks and mathematical tools capturing the manipulation of information at the molecular level may yield critical insights into the design principles of evolved biological regulatory networks. Further, understanding how information processing is possible in the disordered world of chemistry could result in error-robust electronic computing. The project will also contribute to the development of undergraduate and graduate courses, which will train students to apply the principles of computer science and electrical engineering in traditionally incompatible domains. This will encourage the next generation of scientists to break through traditional disciplinary barriers and create the scientific and engineering fields of tomorrow. This proposal will answer foundational questions about the computational power of chemical kinetics (chemical reaction networks). How can chemicals be programmed to have desired behaviors? How much molecular energy does such computation consume? How much "more computation" does every additional chemical reaction enable? Recent advances in DNA nanotechnology (strand displacement cascades) demonstrate that molecular systems of complex functionality can be designed and constructed from the ground up. This proposal will help precisely delineate the capabilities and limitations of this technology, resulting in smaller, simpler DNA-based circuits. This proposal also introduces a new paradigm, based on the laws of thermodynamics, for programming DNA-DNA interactions. As chemical and biological systems are comprised of molecules that are inherently information-rich and programmable, principles of computer science will help design smart molecules.

生物学充满了智能分子系统，它们可以进行纳米级组装，感知环境刺激，产生化学信号，并产生物理运动-这些任务中的每一项都由化学反应实现的信息处理电路协调。学习如何构建在复杂环境中自主计算的人工化学品将为制造业、化学传感和医学带来突破性的进步。计算理论已经证明在电子人造系统中实现信息处理方面是非常宝贵的，并且从通信网络到视频游戏的所有行为都是基于大量研究的算法。然而，对化学计算原理的透彻理解仍然缺乏。本项目的目标是利用严格的数学模型来研究化学信息处理的能力和局限性，该研究将使物理学、化学、生物学和计算机科学领域在智力上更加接近，并相互丰富。例如，概念框架和数学工具捕捉在分子水平上的信息操作可能会产生重要的见解进化的生物调控网络的设计原则。此外，理解信息处理在无序的化学世界中是如何可能的，可能会导致错误鲁棒的电子计算。该项目还将促进本科生和研究生课程的发展，这些课程将训练学生在传统上不相容的领域应用计算机科学和电气工程的原理。这将鼓励下一代科学家突破传统的学科障碍，创造明天的科学和工程领域。该提案将回答有关化学动力学（化学反应网络）计算能力的基本问题。化学物质如何被编程以具有期望的行为？这样的计算消耗了多少分子能量？每一个额外的化学反应能带来多少“更多的计算”？DNA纳米技术（链置换级联）的最新进展表明，复杂功能的分子系统可以从头开始设计和构建。这项提议将有助于精确地描述这项技术的能力和局限性，从而产生更小、更简单的基于DNA的电路。该提案还介绍了一种新的范例，基于热力学定律，用于编程DNA-DNA相互作用。由于化学和生物系统是由内在信息丰富和可编程的分子组成的，计算机科学的原理将有助于设计智能分子。