Cooperative Motion of Microswimmers: The Influence of Ionic and Reactive Screening on Hydrodynamic Interactions in Complex Fluids

在这个项目中，我们将使用计算方法研究静电和反应性筛选对化学驱动的微泳者在复杂介质中--具体地说，具有粘弹性响应的流体--集体动力学的影响。最终目标是更好地了解游泳者之间的接触、(弹性)水动力和磷(化学)相互作用的相互作用，这些相互作用是在大量现实世界系统中观察到的合作行为的基础。例如，对于最近在活性物质群落中获得实验关注的化学模型系统，对推进机制的更好理解可能会使我们深入了解细菌如何入侵我们重要器官内的保护性粘弹性粘液。我们的项目旨在通过从更基本的角度研究目前可用的模型体系来为这一努力做出贡献。我们最近研究了各种自电泳体系，例如在过氧化氢溶液中的Janus胶体，我们从理论上证明了它们的自推进可以被诱导反应性筛选的整体离子反应强烈地调制。我们将在本SPP资助期内扩展这些单粒子结果，以涵盖这些系统的集体动态。为此，我们将使用我们在上一次SPP资助期开发的晶格电动力学(Latge-EK)算法对活性粒子进行建模。格子-EK算法利用了格子-玻尔兹曼算法在流体力学中的计算效率，并将其与计算溶质浓度和静电场的强大数值求解器相结合。这种效率使我们能够模拟许多化学游泳者之间的相互作用，并探索集体运动的产生方式，同时让我们完全控制建模中包括的所有元素。我们的格子-EK是最先进的，因为它能够模拟带电系统的运动边界条件，这是此类算法的第一次。我们在本SPP资助期的策略是对格子-EK进行进一步的算法改进，以促进集体运动的研究，并更好地恢复相关物理。这些修改包括自适应网格细化和润滑修正，以及将格子-EK和粘弹性LB方法结合在一起。同时，我们将使用我们的软件来研究由我们的SPP合作者实验实现的一些游泳系统，并系统地描述其中的集体特征。通过遵循这一方法，我们的项目将导致对导致主动驱动粒子复杂的不平衡行为的关键参数的更好理解。

In this project, we will study the effect of electrostatic and reactive screening on the collective dynamics of chemically driven microswimmers in complex media -- specifically, fluids with viscoelastic response -- using computational methods. The ultimate goal is to achieve a better understanding of the interplay of swimmers' contact, (elasto)hydrodynamic, and phoretic (chemical) interactions that underlie the cooperative behavior observed in a large variety of real-world systems. For example, for chemical model systems, which have recently gained experimental attention within the active matter community, an improved understanding of the propulsion mechanisms may give insights into the way bacteria invade the protective viscoelastic mucus lining our vital organs. Our project aims to contribute to this effort by studying currently available model systems from a more fundamental perspective.We have recently considered a variety of self-electrophoretic systems, e.g., Janus colloids in a hydrogen peroxide solution, where we have theoretically demonstrated that their self-propulsion can be strongly modulated by bulk ionic reactions that induce reactive screening. We will extend these single particle results in this SPP funding period to encompass the collective dynamics of these systems. To this end, we will model the active particles using our lattice-electrokinetics (lattice-EK) algorithm, developed during the previous SPP funding period. Lattice-EK exploits the computational efficiency of the lattice-Boltzman (LB) algorithm for hydrodynamics and combines this with powerful numerical solvers for solute concentration and electrostatic fields. This efficiency enables us to simulate the interaction between many chemical swimmers and explore the way collective motion comes about, while giving us full control over all elements included in the modelling. Our lattice-EK is state of the art, as it is capable of simulating moving boundary conditions for charged systems, a first of its kind for this type of algorithm.Our strategy for this SPP funding period is to make further algorithmic improvements to the lattice-EK in order to facilitate the study of collective motion and to better recover the relevant physics. These modifications include adaptive grid refinement and lubrication corrections, as well as bringing together lattice-EK and viscoelastic LB methods. Simultaneously, we will use our software to investigate a number of swimmer systems that are experimentally realized by our SPP collaborators, and systematically characterize the collectivity therein. By following this approach, our project will lead to an improved understanding of the key parameters that bring about the complex out-of-equilibrium behavior of actively driven particles.