Theoretical Studies of Tunable Networks

可调谐网络的理论研究

• 批准号: 2005749
• 负责人: Andrea Liu
• 金额: $ 67万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2005749&HistoricalAwards=false
• 关键词: Theoretical; Studies; Tunable; Networks

NONTECHNICAL SUMMARYThis award supports theoretical, computational, and data-driven research, and education to study how living systems self-regulate by investigating mechanical networks that are tunable through their links at edges. The central goal is to uncover an organizing principle which can be further applied to materials design. On the face of it, the mechanism by which many enzymes are turned on and off (allostery), the ability of the brain vascular system to adjust blood flow to different parts of the brain on demand, the ability of the cellular cytoskeleton to control robustly cell shape and mechanics even as they are changing, and morphological processes in embryonic development have little in common. This project suggests and explores the possibility that there is an underlying organizing principle that unifies these phenomena. In each of these systems, the network connectivity can be modified at the level of individual links in the network, by evolution, by dilating or contracting blood vessels, by specific proteins or by adjustable levels of protein expression, respectively. This enables each link to have different and mutable properties that can be tuned in order to give rise to the aforementioned phenomena. The lessons that the PI and her research team will learn by studying this new possible organizing principle and its consequences will be applicable to synthetic systems and materials, and may provide insight into how to design materials capable of performing tasks that approach the diversity and complexity of those routinely accomplished by living systems.The PI will continue vigorous outreach, advocacy, mentoring and service, particularly for women; a few of her recent activities include (1) Lecturer to Philadelphia area high school science teachers; (2) Panelist for discussions for women in academic science; (3) Speaker and co-host of panels addressing issues affecting Asian-American scientists and engineers; (4) Deliverer of public lectures in Philadelphia and elsewhere; (5) Holder of leadership positions in the American Physical Society, representing approximately 55,000 physicists in the US and worldwide, as well as the Physics Section of the American Association for the Advancement of Science. The PI also meets with groups of women students, postdocs and faculty during seminar/colloquium trips to academic institutions in fields ranging from physics and chemistry to materials science and mechanical engineering.TECHNICAL SUMMARYThis award supports theoretical, computational, and data-driven research, and education to study athermal mechanical networks with tunable edge properties to reveal organizing principles that unite different features of living matter systems and are applicable to materials design. Living matter systems are often composed of constituents that are non-identical (such as amino acids in a protein or cells in a tissue) and mutable (amino acid sequences can change during evolution and cells differentiate during development). The ability of scientists to connect microscopic properties to collective behavior in many-body systems, in which every constituent can be different and can alter its properties, is currently limited. This project is focused on a class of such systems, athermal mechanical networks with tunable edge properties. The PI and collaborators have previously shown that such networks are highly malleable in their properties upon alteration of a very small fraction of edges. This project pursues three main directions of research on tunable mechanical networks. (1) Topological data analysis and machine learning methods will be used to connect microscopic properties to collective behavior. (2) Potentially abstract questions involving adaptability, evolvability and robustness of these systems will be addressed in a concrete, quantitative way. (3) Edge tuning will be explored as a new organizing principle for understanding and potentially designing functions and processes in mechanical networks ranging from molecular to cellular and tissue scales in living matter.The proposed research will use data mining methods to go beyond statistical mechanics to understand microscopic origins of many-body behavior. Such methods have been used in physics for fast approximation (e.g. in calculating electronic structure) or classification (e.g. in developing triggers for high energy experiments or distinguishing astronomical objects in images), but there has been little focus on applying them towards the central goal of condensed matter theory. The research also brings a unifying viewpoint to biological processes ranging from the molecular to the cellular and tissue scales. It will also provide a new perspective to semiflexible networks, a focus of considerable excellent soft and living matter research, as well as epithelial tissues, systems of increasing interest in the soft/living matter community. The topological data analysis developed previously by the PI and collaborators will be generalized and applied to real proteins, potentially leading to new understanding of the link between conserved amino acid sequences and allostery. An eventual goal is to develop a new strategy for designing synthetic allosteric proteins, which would have potential medical and other applications. The concept of tuning as a new organizing principle in mechanical networks across scales in living systems could allow useful insights to be exchanged across the fields of physics, materials science, mechanical engineering, bioengineering, structural biology, cell biology and developmental biology, to mutual benefit.The PI will continue vigorous outreach, advocacy, mentoring and service, particularly for women; a few of her recent activities include (1) Lecturer to Philadelphia area high school science teachers; (2) Panelist for discussions for women in academic science; (3) Speaker and co-host of panels addressing issues affecting Asian-American scientists and engineers; (4) Deliverer of public lectures in Philadelphia and elsewhere; (5) Holder of leadership positions in the American Physical Society, representing approximately 55,000 physicists in the US and worldwide, as well as the Physics Section of the American Association for the Advancement of Science. The PI also meets with groups of women students, postdocs and faculty during seminar/colloquium trips to academic institutions in fields ranging from physics and chemistry to materials science and mechanical engineering.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.

该奖项支持理论、计算和数据驱动的研究和教育，以研究生命系统如何通过边缘链接进行自我调节的机械网络。中心目标是揭示一个可以进一步应用于材料设计的组织原则。从表面上看，许多酶的开启和关闭机制（变构），脑血管系统根据需要调节血液流向大脑不同部位的能力，细胞骨架在细胞形状和力学变化时强有力地控制细胞形状和力学的能力，以及胚胎发育中的形态过程几乎没有共同之处。该项目提出并探索了统一这些现象的潜在组织原则的可能性。在这些系统中，网络连通性可以在网络中的单个链接水平上进行修改，分别通过进化，通过扩张或收缩血管，通过特定蛋白质或可调节的蛋白质表达水平。这使得每个链接具有不同的可变属性，可以对这些属性进行调优，从而产生上述现象。PI和她的研究团队将通过研究这种新的可能的组织原理及其结果而获得的经验教训将适用于合成系统和材料，并可能为如何设计能够执行接近生命系统常规完成的任务的多样性和复杂性的材料提供见解。PI将继续大力推广、宣传、指导和服务，特别是对妇女；她最近的一些活动包括：(1)费城地区高中科学教师的讲师；(2)学术科学领域女性讨论小组成员；(3)就影响亚裔美国科学家和工程师的问题发表演讲并共同主持小组讨论；(4)在费城和其他地方进行公开演讲；(5)在美国物理学会担任领导职务，代表美国和全世界约55,000名物理学家，以及美国科学促进会物理分会。在参加从物理和化学到材料科学和机械工程等领域的学术机构的研讨会/座谈会期间，PI还会见了女学生、博士后和教师团体。该奖项支持理论、计算和数据驱动的研究和教育，以研究具有可调边缘特性的非热机械网络，以揭示将生命物质系统的不同特征结合起来的组织原则，并适用于材料设计。生命物质系统通常由不相同的成分（如蛋白质中的氨基酸或组织中的细胞）和可变的成分（氨基酸序列可以在进化过程中改变，细胞在发育过程中分化）组成。科学家们将微观特性与多体系统中的集体行为联系起来的能力目前是有限的，在多体系统中，每一个组成部分都可能是不同的，并且可以改变其特性。这个项目的重点是一类这样的系统，具有可调边缘特性的非热机械网络。PI和合作者先前已经表明，这种网络在改变极小部分的边缘时，其性质具有高度的延展性。本项目主要从三个方向研究可调谐机械网络。(1)将使用拓扑数据分析和机器学习方法将微观属性与集体行为联系起来。(2)涉及这些系统的适应性、可进化性和鲁棒性的潜在抽象问题将以具体的、定量的方式解决。(3)边缘调谐将作为一种新的组织原理，用于理解和潜在地设计生物物质中从分子到细胞和组织尺度的机械网络中的功能和过程。拟议的研究将使用数据挖掘方法超越统计力学，以了解多体行为的微观起源。这些方法已经在物理学中用于快速逼近（例如计算电子结构）或分类（例如开发高能实验触发器或在图像中区分天文物体），但很少关注将它们应用于凝聚态理论的中心目标。该研究还为从分子到细胞和组织尺度的生物过程带来了统一的观点。它还将为半柔性网络提供一个新的视角，半柔性网络是相当优秀的软物质和生物物质研究的焦点，以及上皮组织，软/生物物质社区越来越感兴趣的系统。PI和合作者先前开发的拓扑数据分析将被推广并应用于实际蛋白质，可能导致对保守氨基酸序列和变构之间联系的新理解。最终目标是开发一种设计合成变构蛋白的新策略，这将有潜在的医疗和其他应用。调谐的概念作为生命系统中跨尺度机械网络的一种新的组织原则，可以使物理学、材料科学、机械工程、生物工程、结构生物学、细胞生物学和发育生物学等领域的有用见解得到交流，从而实现互利共赢。PI将继续大力推广、宣传、指导和服务，特别是对妇女；她最近的一些活动包括：(1)费城地区高中科学教师的讲师；(2)学术科学领域女性讨论小组成员；(3)就影响亚裔美国科学家和工程师的问题发表演讲并共同主持小组讨论；(4)在费城和其他地方进行公开演讲；(5)在美国物理学会担任领导职务，代表美国和全世界约55,000名物理学家，以及美国科学促进会物理分会。在参加从物理和化学到材料科学和机械工程等领域的学术机构的研讨会/座谈会期间，PI还会见了女学生、博士后和教师团体。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

Demonstration of Decentralized Physics-Driven Learning

• DOI: 10.1103/physrevapplied.18.014040
• 发表时间: 2022-07-18
• 期刊: PHYSICAL REVIEW APPLIED
• 影响因子: 4.6
• 作者: Dillavou, Sam;Stern, Menachem;Durian, Douglas J.
• 通讯作者: Durian, Douglas J.

Physical learning beyond the quasistatic limit

超越准静态极限的物理学习

• DOI: 10.1103/physrevresearch.4.l022037
• 发表时间: 2022
• 期刊: Physical Review Research
• 影响因子: 4.2
• 作者: Stern, Menachem;Dillavou, Sam;Miskin, Marc Z.;Durian, Douglas J.;Liu, Andrea J.
• 通讯作者: Liu, Andrea J.

Desynchronous learning in a physics-driven learning network

物理驱动学习网络中的异步学习

• DOI: 10.1063/5.0084631
• 发表时间: 2022
• 期刊: The Journal of Chemical Physics
• 作者: Wycoff, J. F.;Dillavou, S.;Stern, M.;Liu, A. J.;Durian, D. J.
• 通讯作者: Durian, D. J.

Learning Without Neurons in Physical Systems

• DOI: 10.1146/annurev-conmatphys-040821-113439
• 发表时间: 2022-06
• 期刊: Annual Review of Condensed Matter Physics
• 影响因子: 22.6
• 作者: M. Stern;A. Murugan