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复杂介质中化学驱动微游泳者集体动力学的影响，特别是具有粘弹性响应的流体。最终目标是更好地理解游泳者的接触、（弹性）流体动力学和电泳（化学）相互作用之间的相互作用，这些相互作用是在各种现实世界系统中观察到的合作行为的基础。例如，对于化学模型系统，最近在活性物质群落中得到了实验的关注，对推进机制的更好理解可能会让我们深入了解细菌入侵我们重要器官内壁的保护性粘弹性粘液的方式。我们的项目旨在通过从更基本的角度研究当前可用的模型系统来促进这一努力。我们最近考虑了各种自电泳系统，例如，过氧化氢溶液中的Janus胶体，在理论上我们已经证明了它们的自我推进可以通过诱导反应性筛选的体离子反应来强烈调节。我们将在SPP资助期间扩展这些单粒子结果，以涵盖这些系统的集体动力学。为此，我们将使用之前SPP资助期间开发的晶格-电动力学（lattice-EK）算法对活性颗粒进行建模。Lattice-EK利用了流体动力学的lattice-Boltzman （LB）算法的计算效率，并将其与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，并探索集体运动产生的方式，同时使我们能够完全控制建模中包含的所有元素。我们的格子- ek是最先进的，因为它能够模拟带电系统的移动边界条件，这是此类算法中的第一个。我们在SPP资助期间的策略是对lattice-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。这些改进包括自适应网格优化和润滑校正，以及将网格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一些由我们的SPP合作者实验实现的游泳系统，并系统地表征其中的集体。通过采用这种方法，我们的项目将有助于更好地理解导致主动驱动粒子复杂的不平衡行为的关键参数。

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.