Mechanochemical topological defects in an active nematic.

IF 2.4 3区 物理与天体物理 Q1 Mathematics
Michael M Norton, Piyush Grover
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引用次数: 0

Abstract

We propose a reaction-diffusion system that converts topological information of an active nematic into chemical signals. We show that a curvature-activated reaction dipole is sufficient for creating a system that dynamically senses topology by producing a concentration field possessing local extrema coinciding with ±1/2 defects. The enabling term is analogous to polarization charge density seen in dielectric materials. We demonstrate the ability of this system to identify defects in both passive and active nematics. Our results illustrate that a relatively simple feedback scheme, expressed as a system of partial differential equations, is capable of producing chemical signals in response to inherently nonlocal structures in anisotropic media. We posit that such coarse-grained systems can help generate testable hypotheses for regulated processes in biological systems, such as morphogenesis, and motivate the creation of bio-inspired materials that utilize dynamic coupling between nematic structure and biochemistry.

我们提出了一种反应扩散系统,可将活性向列的拓扑信息转化为化学信号。我们的研究表明,曲率激活的反应偶极子足以创建一个系统,通过产生具有与 ±1/2 缺陷重合的局部极值的浓度场来动态感知拓扑结构。该使能项类似于电介质材料中的极化电荷密度。我们展示了该系统识别被动和主动线粒体缺陷的能力。我们的结果表明,用偏微分方程系统表示的相对简单的反馈方案能够产生化学信号,以响应各向异性介质中固有的非局部结构。我们认为,这种粗粒度系统有助于为形态发生等生物系统中的调节过程提出可检验的假设,并激励人们利用向列结构与生物化学之间的动态耦合创造生物启发材料。
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来源期刊
Physical review. E
Physical review. E 物理-物理:流体与等离子体
CiteScore
4.60
自引率
16.70%
发文量
0
审稿时长
3.3 months
期刊介绍: Physical Review E (PRE), broad and interdisciplinary in scope, focuses on collective phenomena of many-body systems, with statistical physics and nonlinear dynamics as the central themes of the journal. Physical Review E publishes recent developments in biological and soft matter physics including granular materials, colloids, complex fluids, liquid crystals, and polymers. The journal covers fluid dynamics and plasma physics and includes sections on computational and interdisciplinary physics, for example, complex networks.
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