Hydrodynamics can determine the optimal route for microswimmer navigation

Daddi-Moussa-Ider, Abdallah; Löwen, Hartmut; Liebchen, Benno

doi:10.1038/s42005-021-00522-6

Cited by 47 publications

(32 citation statements)

References 72 publications

(91 reference statements)

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“…Contrasting classical navigation problems of vehicles like ships or airplanes [21,22], mesoscopic active particles can face a variety of new challenges including fluctuations, hydrodynamic interactions with obstacles and boundaries [23,24], and highly complex environments [25][26][27][28]. Following these complex ingredients, the optimal (fastest) path generically differs from the shortest one and is highly challenging to determine.…”

Section: Introductionmentioning

confidence: 99%

Reinforcement learning of optimal active particle navigation

Nasiri¹,

Liebchen²

2022

Preprint

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The development of self-propelled particles at the micro-and the nanoscale has sparked a huge potential for future applications in active matter physics, microsurgery, and targeted drug delivery. However, while the latter applications provoke the quest on how to optimally navigate towards a target, such as e.g. a cancer cell, there is still no simple way known to determine the optimal route in sufficiently complex environments. Here we develop a machine learning-based approach that allows us, for the first time, to determine the asymptotically optimal path of a selfpropelled agent which can freely steer in complex environments. Our method hinges on policy gradient-based deep reinforcement learning techniques and, crucially, does not require any reward shaping or heuristics. The presented method provides a powerful alternative to current analytical methods to calculate optimal trajectories and opens a route towards a universal path planner for future intelligent active particles.

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Section: Introductionmentioning

confidence: 99%

Reinforcement learning of optimal active particle navigation

Nasiri¹,

Liebchen²

2022

Preprint

Self Cite

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“…These organisms live in the aqueous environment near the boundaries and often encounter various kinds of external perturbations via fluid flows [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. The accumulation at the boundaries, propensity to swim upstream, tumbling motion, depletion in bulk are quite often observed in natural microswimmers such as bacteria, sperms, pathogens [17,19,[24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]. In particular under pressure-driven flow, these microswimmers display fascinating dynamics following periodic trajectories in the from of helical, circular or chaotic trajectories in few specific scenarios [40][41][42][43].…”

Section: Introductionmentioning

confidence: 99%

Migration of active filaments under Poiseuille flow in a microcapillary tube

Anand

Singh

2021

Eur. Phys. J. E

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We present a comprehensive study of active filaments confined in a cylindrical channel under Poiseuille flow. The activity drives the filament towards the channel boundary, whereas external fluid flow migrates the filament away from the boundary. This migration further shifts towards the centre for higher flow strength. The migration behaviour of the filaments is presented in terms of the alignment order parameter that shows the alignment grows with shear and activity. Further, we have also addressed the role of length of filament on the migration behaviour, which suggests higher migration for larger filaments. Moreover, we discuss the polar ordering of filaments as a function of distance from the centre of channel that displays upstream motion near the boundary and downstream motion at the centre of the tube.

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“…Self-propelling microswimmers often experience dynamic fluid environments and confinements, for example, pathogens in lung mucus [1], microorganisms in laminar flow a through porous matrix [2], and sperm cells in the Fallopian tubes [3]. Often these swimmers interact with micro-scale flows and boundaries [4] to enhance survival probability [5] and biofilm formation [6] or cause intriguing collective patterns [7]. Their envisioned artificial counterparts-designed to execute in vitro drug delivery-also would have to interact with the dynamic conditions of such biological flows [8,9].…”

Section: Introductionmentioning

confidence: 99%

How inertial lift affects the dynamics of a microswimmer in Poiseuille flow

Choudhary¹,

Paul²,

Rühle³

et al. 2021

Preprint

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We analyze the dynamics of a microswimmer in pressure-driven Poiseuille flow, where fluid inertia is small but non-negligible. Using perturbation theory and the reciprocal theorem, we show that in addition to the classical inertial lift of passive particles, the active nature generates a 'swimming lift', which we evaluate for neutral and pusher/puller-type swimmers. Accounting for fluid inertia engenders a rich spectrum of novel complex dynamics including bistable states, where tumbling coexists with stable centerline swimming or swinging. The dynamics is sensitive to the swimmer's hydrodynamic signature and goes well beyond the findings at vanishing fluid inertia. Our work will have non-trivial implications on the transport and dispersion of active suspensions in microchannels.

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Hydrodynamics can determine the optimal route for microswimmer navigation

Cited by 47 publications

References 72 publications

Reinforcement learning of optimal active particle navigation

Reinforcement learning of optimal active particle navigation

Migration of active filaments under Poiseuille flow in a microcapillary tube

How inertial lift affects the dynamics of a microswimmer in Poiseuille flow

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