CAREER: Bio-inspired Nonequilibrium Design Principles of Molecular Information Machines

职业：分子信息机的仿生非平衡设计原理

• 批准号: 2145256
• 负责人: Zhiyue Lu
• 金额: $ 65万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2027-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2145256&HistoricalAwards=false
• 关键词: CAREER; Bio; inspired; Nonequilibrium; Design

NONTECHNICAL SUMMARY This CAREER Award supports the research and integrated educational efforts toward developing a new theoretical framework to guide the design of intelligent, responsive materials that mimic living organisms. Intelligent responses allow an entity to smartly discern and respond to the complex spatial and temporal changes of surroundings. For example, a bacterium can actively gather information from the environment and swim toward foods or flee from toxins. Such intelligent responses, ubiquitously observed in living organisms, must operate far from the steady state of thermal equilibrium. So, they cannot be described by the equilibrium theory of classical thermodynamics. Instead, a novel non-equilibrium theory is required to explain and predict the intelligent responsiveness in the fundamental building blocks of materials – molecules. The main aim of this project is to develop a non-equilibrium theory to quantitatively predict the intelligence of a molecule’s response to external stimuli. The theory will capture the relationship between the intelligence of the molecule’s response, its robustness to environmental noise, and how far it needs to be driven away from thermal equilibrium. To accomplish this aim, the research team will combine numerical simulation techniques with the modern theory of non-equilibrium physics. In addition, the team will construct generic toy models that distill the essential dynamics of molecules’ non-equilibrium responses. This project will lead to a set of fundamental and generic statements and predictions as design principles for intelligent materials. These activities will provide students with a cross-disciplinary training program combining mathematics, statistical physics, chemistry, and biophysics and mentorship and professional development skills.The PI and the research team will partner with the Morehead Planetarium and Science Center at the University of North Carolina-Chapel Hill to engage the public. This collaboration involves outreach activities such as Family Science Day and Launch Lab events to make the scientific principles behind the research available to the students and teachers in middle schools, kids and families, and the public.TECHNICAL SUMMARYThis CAREER Award supports the research and integrated education to elucidate the design of microscopic information machines that autonomously sense, memorize, and respond to spatiotemporal patterns of external stimuli, such as pH, temperature, and chemical environments. These microscopic machines will serve as fundamental building blocks of next-generation novel materials and smart nano-robots. Attaining this goal will transform the field of novel functional and active materials by imparting life-like attributes to otherwise inert molecular complexes and deepen our understanding of thermodynamics, information, and intelligence in the chemistry, biology, and material science communities.Living organisms, maintained far from equilibrium by constantly dissipating energy and producing entropy, can actively sense, memorize, and respond to complex information hidden in environmental conditions. Biological systems have evolved to utilize diverse ingenious nonequilibrium mechanisms to maintain robust and accurate performance, typically at the cost of energy dissipation or the speed of response. The strategic goal of the research is to elucidate nonequilibrium mechanisms of energy extraction, information sensing and storage, noise resistance, and robustness in connection to entropy production and to develop a universal theory to predict and optimize the performance of generic microscopic information machines. Specifically, this research will address the following questions: What are the general nonequilibrium thermodynamic principles behind these mechanisms? What are the possible mechanisms to better extract and dissipate energy for the optimal performance of smart materials and intelligent molecular complexes? What can one learn from the physical understanding of biological systems to help the design of artificial molecular complexes to achieve similar or better information processing?The specific aims of the research are to (1) use a hybrid energy landscape approach to describe the nonequilibrium flows of energy caused by a time-varying environment, and (2) find the thermodynamic limit of memory capacity in macromolecular complexes and general relation between the ability of pattern recognition and system’s energy-landscape complexity as reflected in its topology and geometry, and (3) lift the ideal-environment assumption to include the backaction from the system and the thermal fluctuations, and understand the counter-intuitive stochasticity induced comprehensive sensing mechanism.The research activities are closely integrated with education and outreach efforts: both graduate and undergraduate students will be exposed to cutting-edge tools and concepts via direct involvement participation in a novel course module of “thermodynamics of information processing” that is to be included in the re-designed course “Thermodynamics and Introduction to Thermal Statistics”. The PI will collaborate with the Center for Faculty Excellence at UNC to acquire knowledge and guidance regarding the up-to-date educational tools and methodologies and obtain frequent quantifiable evaluations to guarantee the success of the re-designed course. The PI and the research team will work with visitors and high school teachers and students in North Carolina by collaborating with the Morehead Planetarium and Science Center on Family Science Day and during the Launch Lab events. Morehead will provide evaluation data to the PI that examines the extent to which the event’s main communications goals are met and provide further guidance on improving the public's engagement.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.

该职业奖支持研究和综合教育工作，旨在开发新的理论框架，指导设计模仿生物体的智能、反应性材料。智能响应允许实体巧妙地识别和响应周围复杂的空间和时间变化。例如，细菌可以积极地从环境中收集信息，然后游向食物或逃离毒素。这种智能反应，在生物体中随处可见，必须远离热平衡的稳定状态。所以，它们不能用经典热力学的平衡理论来描述。相反，需要一种新的非平衡理论来解释和预测材料的基本组成部分——分子的智能响应。该项目的主要目的是发展一种非平衡理论，以定量预测分子对外部刺激反应的智力。该理论将捕捉到分子反应的智能、它对环境噪声的稳健性以及它需要离开热平衡多远之间的关系。为了实现这一目标，研究小组将把数值模拟技术与现代非平衡物理理论结合起来。此外，该团队将构建通用玩具模型，提取分子非平衡反应的基本动力学。这个项目将导致一套基本的和通用的陈述和预测，作为智能材料的设计原则。这些活动将为学生提供跨学科的培训计划，结合数学，统计物理，化学和生物物理学以及指导和专业发展技能。PI和研究小组将与北卡罗来纳大学教堂山分校的莫尔黑德天文馆和科学中心合作，吸引公众参与。此次合作包括家庭科学日和启动实验室活动等外展活动，向中学的学生和教师、儿童和家庭以及公众提供研究背后的科学原理。该职业奖支持研究和综合教育，以阐明微观信息机器的设计，这些机器可以自主感知、记忆和响应外部刺激的时空模式，如pH值、温度和化学环境。这些微型机器将成为下一代新材料和智能纳米机器人的基本组成部分。实现这一目标将通过赋予惰性分子复合物类似生命的属性来改变新型功能和活性材料领域，并加深我们对化学、生物学和材料科学界热力学、信息和智能的理解。生物通过不断耗散能量和产生熵来保持远离平衡的状态，能够主动感知、记忆和响应隐藏在环境条件中的复杂信息。生物系统已经进化到利用各种巧妙的非平衡机制来保持稳健和准确的性能，通常以能量耗散或响应速度为代价。本研究的战略目标是阐明与熵产生相关的能量提取、信息感知和存储、抗噪声和鲁棒性的非平衡机制，并发展一种通用理论来预测和优化通用微观信息机器的性能。具体来说，本研究将解决以下问题：这些机制背后的一般非平衡热力学原理是什么？为了实现智能材料和智能分子复合物的最佳性能，有哪些可能的机制可以更好地提取和耗散能量？我们可以从对生物系统的物理理解中学到什么，以帮助设计人工分子复合物，以实现类似或更好的信息处理？本研究的具体目标是：(1)利用混合能量景观方法描述时变环境引起的能量不平衡流动；(2)找到大分子复合物中记忆容量的热力学极限，以及模式识别能力与系统拓扑和几何结构所反映的能量景观复杂性之间的一般关系。(3)提升理想环境假设，纳入系统反作用力和热波动，理解反直觉的随机性诱导的综合感知机制。研究活动与教育和推广工作紧密结合：研究生和本科生都将通过直接参与“信息处理热力学”的新课程模块来接触前沿工具和概念，该课程模块将包含在重新设计的课程“热力学和热统计入门”中。PI将与北卡罗来纳大学卓越教师中心合作，获取有关最新教育工具和方法的知识和指导，并获得频繁的量化评估，以确保重新设计的课程取得成功。PI和研究团队将在家庭科学日和发射实验室活动期间与莫尔黑德天文馆和科学中心合作，与北卡罗来纳州的游客和高中教师和学生合作。莫尔黑德将向项目负责人提供评估数据，以检查活动的主要传播目标达到的程度，并为提高公众参与度提供进一步的指导。该奖项反映了美国国家科学基金会的法定使命，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。

项目成果

Energy landscape design principle for optimal energy harnessing by catalytic molecular machines

催化分子机器优化能源利用的能源景观设计原理

• DOI: 10.1103/physreve.107.l012102
• 发表时间: 2023
• 期刊: Physical Review E
• 影响因子: 2.4
• 作者: Zhang, Zhongmin;Du, Vincent;Lu, Zhiyue
• 通讯作者: Lu, Zhiyue

Sloppy gear mechanism for coupled stochastic transportation: From antiequilibrium flow to kinetic selectivity

耦合随机传输的马虎齿轮机构：从反平衡流到动力学选择性

• DOI: 10.1103/physrevresearch.4.023234
• 发表时间: 2022
• 期刊: Physical Review Research
• 影响因子: 4.2
• 作者: Slowey, Chase;Lu, Zhiyue
• 通讯作者: Lu, Zhiyue

Theoretical upper bound of multiplexing in biological sensory receptors

生物感觉受体中多路复用的理论上限

• DOI: 10.1103/physrevresearch.5.023032
• 发表时间: 2023
• 期刊: Physical Review Research
• 影响因子: 4.2
• 作者: Pagare, Asawari;Min, Sa Hoon;Lu, Zhiyue
• 通讯作者: Lu, Zhiyue