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.

非技术摘要该奖项支持理论、计算和数据驱动的研究以及教育，以研究生命系统如何通过研究可通过边缘链接进行调节的机械网络来进行自我调节。中心目标是揭示一种可以进一步应用于材料设计的组织原则。从表面上看，许多酶开启和关闭的机制（变构）、脑血管系统根据需要调整流向大脑不同部位的血流的能力、细胞骨架稳健控制的能力即使细胞形状和力学正在发生变化，胚胎发育中的形态过程也几乎没有共同点。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。在这些系统中的每一个中，网络连接性可以分别通过进化、扩张或收缩血管、特定蛋白质或可调节的蛋白质表达水平在网络中的各个链路水平上进行修改。这使得每个链接具有不同且可变的属性，可以调整这些属性以引起上述现象。 PI 和她的研究团队通过研究这种新的可能的组织原理及其后果将学到的经验教训将适用于合成系统和材料，并可能提供有关如何设计能够执行接近多样性和复杂性任务的材料的见解。 PI 将继续大力开展宣传、宣传、指导和服务，特别是针对女性；她最近的一些活动包括 (1) 为费城地区高中科学教师担任讲师； (2) 学术科学领域女性讨论小组成员； (3) 讨论影响亚裔美国科学家和工程师的问题的小组发言人和联合主持人； (4) 在费城和其他地方进行公开讲座； (5) 在美国物理学会（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中担任领导职务。 PI 还在物理、化学、材料科学和机械工程等领域的学术机构举办研讨会/座谈会期间会见了女学生、博士后和教师群体。 技术摘要该奖项支持理论、计算和数据驱动的研究，教育研究具有可调边缘特性的非热机械网络，以揭示结合生命物质系统不同特征并适用于材料设计的组织原理。生命物质系统通常由不相同的成分（例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。目前，科学家将微观特性与多体系统中的集体行为联系起来的能力有限，在多体系统中，每个成分都可以不同，并且可以改变其特性。该项目专注于一类此类系统，即具有可调边缘特性的无热机械网络。 PI 和合作者之前已经表明，这种网络在改变极小部分边的情况下其属性具有高度可塑性。该项目致力于可调谐机械网络的三个主要研究方向。 （1）利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、进化性和鲁棒性的潜在抽象问题将以具体、定量的方式得到解决。 (3) 将探索边缘调整作为一种新的组织原则，用于理解和潜在地设计生物体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了解多体行为的微观起源。这些方法已在物理学中用于快速近似（例如计算电子结构）或分类（例如开发高能实验的触发器或区分图像中的天文物体），但很少有人关注将它们应用于凝聚态理论。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新的视角，半柔性网络是相当出色的软物质和活物质研究的焦点，以及上皮组织，软物质/活物质界越来越感兴趣的系统。 PI和合作者之前开发的拓扑数据分析将被推广并应用于真实的蛋白质，有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，这将具有潜在的医学和其他应用。调整的概念作为生命系统中跨尺度机械网络的新组织原则，可以允许在物理学、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领域之间交换有用的见解，从而实现互惠互利.PI 将继续大力开展外展、宣传、指导和服务，特别是针对女性；她最近的一些活动包括 (1) 为费城地区高中科学教师担任讲师； (2) 学术科学领域女性讨论小组成员； (3) 讨论影响亚裔美国科学家和工程师的问题的小组发言人和联合主持人； (4) 在费城和其他地方进行公开讲座； (5) 在美国物理学会（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中担任领导职务。 PI 还在物理、化学、材料科学和机械工程等领域的学术机构举办研讨会/座谈会期间会见了女学生、博士后和教师。该奖项反映了 NSF 的法定使命，并通过评估被认为值得支持利用基金会的智力优势和更广泛的影响审查标准。

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