Acknowledgements
J.W. and D.F. contributed equally to this work. This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 764977, the Spanish (PID2020-116844RB-C2 and PID2020-116844RB-C21) and Catalan (2017-SGR-0292) research administrations, and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2022R1C1C1007338).
Supporting Information
Supplementary material is available on the editor website.
Reuse
Citation
@article{wu2022,
author = {Wu, Jiaen and Folio, David and Zhu, Jiawei and Jang, Bumjin
and Chen, Xiangzhong and Feng, Junxiao and Gambardella, Pietro and
Jordi , Sort and Puigmarti-Luis, Josep and Ergeneman, Olgac and
Ferreira, Antoine and Pané, Salvador},
publisher = {Wiley},
title = {Motion {Analysis} and {Real-Time} {Trajectory} {Prediction}
of {Magnetically} {Steerable} {Catalytic} {Janus} {Micromotors}},
journal = {Advanced Intelligent Systems},
volume = {4},
number = {11},
date = {2022-09-21},
url = {https://dfolio.fr/publications/articles/2022wuAIS.html},
doi = {10.1002/aisy.202200192},
issn = {2640-4567},
langid = {en-US},
abstract = {Chemically driven micromotors display unpredictable
trajectories due to the rotational Brownian motion interacting with
the surrounding fluid molecules. This hampers the practical
applications of these tiny robots, particularly where precise
control is a requisite. To overcome the rotational Brownian motion
and increase motion directionality, robots are often decorated with
a magnetic composition and guided by an external magnetic field.
However, despite the straightforward method, explicit analysis and
modeling of their motion have been limited. Here, catalytic Janus
micromotors are fabricated with distinct magnetizations and a
controlled self-propelled motion with magnetic steering is shown. To
analyze their dynamic behavior, a dynamic model that can
successfully predict the trajectory of micromotors in uniform
viscous flows in real time by incorporating a form of
state-dependent-coefficient with a robust two-stage Kalman filter is
theoretically developed. A good agreement is observed between the
theoretically predicted dynamics and experimental observations over
a wide range of model parameter variations. The developed model can
be universally adopted to various designs of catalytic
micro-/nanomotors with different sizes, geometries, and materials,
even in diverse fuel solutions. Finally, the proposed model can be
used as a platform for biosensing, detecting fuel concentration, or
determining small-scale motors’ propulsion mechanisms in an unknown
environment.}
}