26404567, 2022, 11, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/aisy.202200192 by Readcube (Labtiva Inc.), Wiley Online Library on [28/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License RESEARCH ARTICLE www.advintellsyst.com Motion Analysis and Real-Time Trajectory Prediction of Magnetically Steerable Catalytic Janus Micromotors Jiaen Wu, David Folio,* Jiawei Zhu, Bumjin Jang,* Xiangzhong Chen, Junxiao Feng, Pietro Gambardella, Jordi Sort, Josep Puigmartí-Luis, Olgac Ergeneman, Antoine Ferreira, and Salvador Pané* 1. Introduction Chemically driven micromotors display unpredictable trajectories due to the rotational Brownian motion interacting with the surrounding fluid molecules. This hampers the “Chemically propelled motor” is a term practical applications of these tiny robots, particularly where precise control is a requisite. used for micro- and nanoscale motile structures that can swim through fluid To overcome the rotational Brownian motion and increase motion directionality, robots environments by means of chemical are often decorated with a magnetic composition and guided by an external magnetic processes.[1] These motile devices have field. However, despite the straightforward method, explicit analysis and modeling of their attracted a great deal of attention from both motion have been limited. Here, catalytic Janus micromotors are fabricated with distinct fundamental[2] and applied[3,4] perspec- magnetizations and a controlled self-propelled motion with magnetic steering is shown. tives. The past two decades have seen major endeavors devoted to understanding the To analyze their dynamic behavior, a dynamic model that can successfully predict the mechanisms underlying the motion of trajectory of micromotors in uniform viscous flows in real time by incorporating a form of chemically propelled devices. Key aspects state-dependent-coefficient with a robust two-stage Kalman filter is theoretically devel- that determine the propulsive forces of oped. A good agreement is observed between the theoretically predicted dynamics and such swimmers depend on several factors experimental observations over a wide range of model parameter variations. The including, but not limited to, the generated developed model can be universally adopted to various designs of catalytic micro-/ reaction byproducts, the reaction kinetics, the geometry, size, and the surface of the nanomotors with different sizes, geometries, and materials, even in diverse fuel solutions. swimmers.[1,2] A recurrent design that Finally, the proposed model can be used as a platform for biosensing, detecting fuel has been commonly used to investigate concentration, or determining small-scale motors’ propulsion mechanisms in an the motion mechanisms and dynamics of unknown environment. these swimmers is the spherical Janus particle (JP)[5–7] because of its simple geom- etry, processability, functionalization, and analytical modeling[6–8] These particles consist of a spherical bead semi-coated with one or more materi- als that range from continuous films to particles or molecules. J. Wu, J. Zhu, X. Chen, O. Ergeneman, S. Pané B. Jang Multi-Scale Robotics Lab Department of Robotics Institute of Robotics and Intelligent Systems Hanyang University ETH Zurich ERICA Campus, Ansan-si 15588, Republic of Korea Tannenstrasse 3, CH 8092 Zurich, Switzerland E-mail: bjang@hanyang.ac.kr E-mail: vidalp@ethz.ch J. Feng, P. Gambardella D. Folio, A. Ferreira Department of Materials PRISME Laboratory ETH Zurich INSA Centre Val de Loire Honggerbergring 64, CH 8093 Zurich, Switzerland University of Orleans EA 4229 Bourges, France J. Sort E-mail: david.folio@insa-cvl.fr Departament de Física Universitat Autònoma de Barcelona The ORCID identification number(s) for the author(s) of this article 08193 Bellaterra, Spain can be found under https://doi.org/10.1002/aisy.202200192. J. Sort, J. Puigmartí-Luis © 2022 The Authors. Advanced Intelligent Systems published by Wiley- Institució Catalana de Recerca i Estudis Avançats (ICREA) VCH GmbH. This is an open access article under the terms of the Pg. Lluís Companys 23, 08010 Barcelona, Spain Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is J. Puigmartí-Luis properly cited. Departament de Ciència dels Materials i Química Física Institut de Química Teòrica i Computacional DOI: 10.1002/aisy.202200192 08028 Barcelona, Spain Adv. Intell. Syst. 2022, 4, 2200192 2200192 (1 of 11) © 2022 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH 26404567, 2022, 11, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/aisy.202200192 by Readcube (Labtiva Inc.), Wiley Online Library on [28/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License www.advancedsciencenews.com www.advintellsyst.com A typical chemically propelled JP motor design comprises a poly- and nucleate on the C side and their propulsive direction is mer bead, which is semi-coated with a metal,[9] ceramic,[10] or toward the N side, the mechanism is called bubble recoil.[8] In enzyme layer[11] that serves as a catalyst (C), while the uncoated this case, the bubbles are large enough to provide a thrusting side is not catalytically active (N). Figure 1A illustrates this par- force to the JPs. In other situations, a few gas molecules are ticular design, where the chemical reaction responsible for the formed on the C side, but are quickly dissolved in the surround- motion occurs in the C region. The mechanism that explains ing liquid, and therefore, provide insufficient time for the bubble the motion of these types of swimmers is still under debate. nucleation. A concentration gradient of the reacted products Generally, it is widely accepted that the propulsion is the result between the C and the N regions creates a diffusive flow around of an asymmetric field gradient ∇f , for example, from the chemi- the JP, resulting in the diffusiophoretic motion of the JP towards cal products around the N and C sides of the JP. However, the the N side. Recent studies have shown that the dominance of one detailed mechanism can vary depending on the generated mechanism over the other can simply depend on small byproducts. For example, when visible gas bubbles are formed changes in the geometries and/or composition of the motors. A B C D E Figure 1. A) A schematic illustration of self-propelled Janus micromotors moving along the magnetic controlled direction. B) A schematic illustration of the fabrication steps and corresponding layer structure for magnetic Janus micromotors: i) assembling a monolayer of silica colloids; ii) sputtering of thin Pt adhesion layer; iii) DC magnetron sputtering of Co/Pt stack bilayer; iv) sputtering of thick Pt protection layer; v) sonication. C) Characteristic scanning electron microscope (SEM) images of Janus micromotors morphology: i) side view; ii) top view. D) Characteristic images of Janus micromotors compo- sition: i) SEM image of a spherical Janus micromotor; ii–iii) The corresponding energy-dispersive X-ray (EDX) image for Pt and Co, respectively. Adv. Intell. Syst. 2022, 4, 2200192 2200192 (2 of 11) © 2022 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH 26404567, 2022, 11, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/aisy.202200192 by Readcube (Labtiva Inc.), Wiley Online Library on [28/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License www.advancedsciencenews.com www.advintellsyst.com For example, by changing the size of a JP, the propulsion phoretic or bubble recoil propulsion mechanism. Known inputs mechanism changes from diffusiophoresis (radius r < 5 μm) (namely the applied magnetic field) are used as a ground truth to to bubble recoil mechanism (radius r > 5 μm).[5,12,13] This is assess the validity of the estimates. Our results demonstrate the because the surface area increases with the diameter. consistency of the proposed model between experimental and Therefore, the increased number of gas molecules cannot fully estimated results. Such real-time trajectory predictions will dissolve in the surrounding liquid quickly, and thus, nucleates enable an abundance of applications where predicting the trajec- visible bubbles. tory is critical, such as target delivery or biosensing.[22] We One of the ultimate goals of chemical micro- and nanomotor emphasize the robustness of our modeling, which can be univer- technology is to use these devices in micro- and nanomanipula- sally adopted to a wide range of catalytic micro-/nanomotors with tion,[6] targeted therapy,[3] or environmental remediation.[14] diverse shapes, materials, and sizes in various fuel solutions. However, to enable the full realization of these devices in bio- Moreover, by analyzing the consistency of the modeling to the medicine, it is essential not only to understand the propulsive experimental data, the propulsion mechanism of the motor mechanism, but also the control over their motion by predicting can be identified, particularly in experimental conditions where the trajectory in real time. While the dynamics of externally pow- bubbles are invisible. ered motors, such as magnetic or acoustically driven micro- and nanorobots, can be deterministically established by the energy input, chemically propelled small-scale swimmers suffer from 2. Results and Discussion a lack of control over their trajectory because their motion relies on a complex interplay of chemical reactions at the motor’s 2.1. Fabrication and Characterization of MJM surface–fluid interface. In other words, their motion dynamics must be analyzed by accounting for Brownian diffusion as their Magnetic Janus micromotors were fabricated by depositing thin directionality is significantly dependent on rotational diffusiv- film layers on a self-assembled monolayer of silica (SiO2) micro- ity.[15] The simplest method for minimizing the rotational diffu- spheres, as illustrated in Figure 1B. First, a dispersion of silica sivity consists of integrating magnetic components, which microspheres in water was deposited using a pipette on a clean enables the control of the swimmers’ directionality by applying silicon substrate. Upon evaporation, a self-assembled monolayer an external magnetic field.[6,16–18] Despite this being a straight- was formed in dried ambient air. Then, a thin Pt adhesion layer forward approach, research on the explicit models that can enable with a thickness of tPt1 was sputtered on top of the silica micro- predictable navigation strategies of magnetically guided chemi- sphere monolayer. n Co/Pt magnetic bilayers with a thickness of cally propelled motors is limited.[7,17–19] In addition, unknown tCo and tPt2, respectively, were deposited onto the adhesion layer environmental inputs, including the magnetic properties, by DC magnetron sputtering. Finally, a thick Pt layer with a thick- competition between propulsion mechanisms, and Brownian ness of 15 nm was sputtered on top of the Co/Pt bilayer stacks. motion, have hampered the establishment of a motion theory This final Pt layer served both as a catalyst for the decomposition for magnetically driven catalytic swimmers. of H2O2, and as a protective coating to prevent the inner This article explicitly analyzes the motion control of magnetic magnetic Co/Pt bilayers from corroding. The configuration of steerable catalytic Janus micromotors (MJM) with different mag- our Janus micromotor is denoted as M(d)Pt(tPt1)[Co(tCo)/ netizations. Our results show that by adding the surfactant into Pt(tPt2)]nPt15 nm, where d is the diameter of the Janus micromo- the swimming environment, the MJM switches the motion tor, t is the thickness of each layer, and n is the number of Co/Pt behavior from self-diffusiophoresis to bubble recoil propulsion. magnetic bilayers. In this study, we evaluated two different sizes To analyze the dynamic behavior of MJMs, a dynamic model of (d = 5 and 10 μm) and several layer configurations (tPt1 = 2 and an MJM is exploited to predict the MJM’s behavior more accu- 5 nm; tCo = 0.4 nm; tPt2 = 0.6, 1.5, and 3 nm; n = 5, 10, 20) of rately, despite having only a limited knowledge of the system Janus micromotors. state and the uncontrollable inputs. To this aim, the state- Scanning electron microscope (SEM) images (side view and dependent coefficient (SDC) form of the MJM is expressed, a top view) show a monolayer of the fabricated Janus micromotors robust two-stage Kalman filter[20] (RTSKF) is extended for state with compositions of M10 μmPt2 nm(Co0.4 nm/Pt0.6 nm)20Pt15 nm, as and unknown or uncontrollable inputs estimation, and a trajec- shown in Figure 1D. We can see a visible boundary between tory prediction in real time is also demonstrated. Our previous metal layers and silica particles, demonstrating the successful model,[21] which was based on a basic Kalman filter with SDC formation of a metal cap. Energy-dispersive X-Ray (EDX) spec- parametrization, was able to describe the dynamic behavior of troscopy images in Figure 1E present the elementary distribution MJMs only with magnetic moments perpendicular to their easy of Pt and Co on the silica particle. The layered structure of the axis and propelled only by the self-phoretic mechanism. This was magnetic Janus micromotors is schematically shown in achieved by estimating inputs from our experimental data that Figure 1B. was collected by analyzing the motion of MJMs comprising The fabricated Co/Pt bilayer displays a ferromagnetic behavior different layers. However, they failed to account for the MJMs and a strong spin–orbit coupling effect between Co and Pt with different magnetic moments or the MJMs propelled with elements. As a result of the electronic hybridization localized bubble recoil propulsion mechanisms. Moreover, the poor at the Co–Pt interfaces, the Co/Pt multilayers display a large per- knowledge of the parametrization and the inputs does not ensure pendicular magnetic anisotropy (PMA).[23] The magnetic proper- the good quality of the estimates. Here, we have specifically ties of the MJM were systematically studied at room temperature developed a dynamic model that properly describes the behavior by vibrating sample magnetometry (VSM) as a function of the of MJMs with different magnetic anisotropies, as well as the self- thickness of Pt (tPt2 = 0.6, 1.5, and 3.0 nm) and the number of Adv. Intell. Syst. 2022, 4, 2200192 2200192 (3 of 11) © 2022 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH 26404567, 2022, 11, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/aisy.202200192 by Readcube (Labtiva Inc.), Wiley Online Library on [28/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License www.advancedsciencenews.com www.advintellsyst.com A B exhibit a spin reorientation (from in-plane to perpendicular-to- 1 In-plane Out-of-plane plane directions) below a critical crossover Co thickness in the 0.5 range 0.3–1.7 nm, depending on the substrate, Pt thickness, and interface quality.[25–27] This transition occurs provided that M/M s In-plane 0 micromotor 1 0.5 the Pt thickness is sufficiently large; otherwise, an in-plane mag- -0.5 -0.5 0 netic easy axis is always energetically more favorable.[28] Also of -1 -1 -50 0 50 note, the saturation field of the in-plane hysteresis loops for -1000 -500 0 500 1000 tPt2 = 1.5 nm increases with the number of Co/Pt repeats. A tail b (mT) at high fields is observed for n = 10 or 20. This tail is related to C D 1 In-plane Out-of-plane high-field magnetic irreversibility[29] and can be ascribed to the 0.5 formation and difficulty in annihilating magnetic stripe domains Out-of-plane with magnetization oriented perpendicular to the Co/Pt interfa- M/M s micromotor 0 1 0.5 ces (either upwards or downwards). Finally, it is worth mention- -0.5 -0.5 0 ing that, due to the curvature of the silica particles, the Co/Pt -1 -1 -50 0 50 interfaces in the investigated structures are not horizontal and -1000 -500 0 500 1000 flat. As a consequence, for tPt2 = 1.5 and 3 nm, the preferential b (mT) orientation of the magnetization, governed by the interface Figure 2. Schematic illustration of the magnetic moment of: A) IP and anisotropy, is not strictly perpendicular to the substrate plane, C) OP magnetic Janus micromotors. The magnetic moment of the IP as it deviates at an angle with respect to the particles’ upper micromotor is aligned with the plane of the Co/Pt stack bilayers. The surface normal, which increases near the particles’ equator magnetic moment of the OP micromotor shows an offset angle α to (as depicted in Figure 2C). the plane of the Co/Pt bilayers. Normalized hysteresis loops measured with the magnetic field applied in-plane and out-of-plane to the plane of the Janus micromotors (MJM diameter 5 μm). Depending on the thick- 2.2. Locomotion Analysis ness of the Co/Pt bilayers, the Janus micromotors show: B) in-plane or D) out-of-plane magnetic anisotropy. Insets: low magnetic field hysteresis To experimentally analyze the motion dynamics, the fabricated loops. arrays of Janus micromotors were suspended in deionized water and detached from the silicon substrate through ultrasonication (Figure 1B (v)). After dispersing the individual Janus micromotor deposited Co/Pt repeats (n = 5, 10, 20). Figure 2 and S1, S2, into the deionized water, this colloidal suspension, together with Supporting Information, show the normalized in-plane (IP) an aqueous solution of H2O2, was dripped onto a pre-cleaned and out-of-plane (OP) magnetic hysteresis loops of the MJM with glass substrate. To inhibit the coalescence of oxygen bubbles, sur- different diameters (5 and 10 μm) and compositions. One can factant (sodium dodecyl sulfate, SDS) was pre-mixed with H2O2; observe that the magnetic anisotropy of the MJM can be adjusted note that in the following section, we demonstrate that by adding by varying the tPt2. surfactants into the H2O2 fuel solutions, the directional control- For tPt2 = 0.6 nm, the Janus micromotors with diameters 5 and lability, as well as the propulsion speed of the micromotors, can 10 μm both exhibit in-plane magnetic anisotropy, as shown in be significantly improved. Due to gravity, the particles sink Figure 2A,B (see also Figure S1A,B and S2A–C, Supporting quickly to a distance close to the surface of the substrate, where Innformation). This is evidenced by the rectangular shape of the equilibrium of the gravity and electrostatic repulsion between the in-plane hysteresis loops and the large saturation field of the particle and the substrate are balanced. With no movement the tilted out-of-plane loops (which is around 400 mT), which in the vertical direction, the degrees of freedom for Janus suggests that the magnetization preferentially aligns parallel to micromotors are reduced, and their motion can be considered the Co layers (due to the shape of anisotropy). The rectangular as a quasi-two-dimensional movement in the horizontal xy-plane shape of the in-plane hysteresis loops is in contrast with the con- (Figure 1C).[30] The locomotion experiments were conducted stricted hysteresis loops (i.e., with a narrowing in their central with a Magnebotix Nanomag setup, which consists of eight coils section) observed in-plane in thin, soft magnetic layers in a hemispherical order. The micromotor dynamics were moni- (e.g., Ni or permalloy) grown onto silica spherical particles[24,25] tored and recorded, using an inverted optical microscope coupled whose magnetization reversal was governed by vortex state with a 30 frame rate camera. formation. Here, no clear evidence for vortex states was obtained. For larger tPt2 values, a spin reorientation transition was 2.3. Directionality of Janus Micromotors observed. Namely, the out-of-plane hysteresis loops tend to display a rectangular shape with the remanence ratio close to The controllability of the directional motion was investigated at 1 (see Figure 2C,D), whereas the in-plane hysteresis loops are different concentrations of H2O2 under an applied external mag- hard to saturate, with magnetic saturation fields in excess of netic field (b). This static magnetic field was applied to orient the 500 mT. In this case, the Janus micromotors display an obvious micromotors, but it did not generate any magnetic field gra- PMA characteristic, where the interface anisotropy is large dients. When the H2O2 and the external magnetic field are absent enough to overcome the shape anisotropy. These results are (c(H2O2) = 0 wt%, b = 0 mT), the micromotors exhibit a typical in agreement with previous works from the literature, which random “walking” due to Brownian diffusion, resulting in a have shown that [Pt/Co] multilayers grown on flat substrates zero-net motion, regardless of Co/Pt thicknesses and number Adv. Intell. Syst. 2022, 4, 2200192 2200192 (4 of 11) © 2022 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH 26404567, 2022, 11, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/aisy.202200192 by Readcube (Labtiva Inc.), Wiley Online Library on [28/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License www.advancedsciencenews.com www.advintellsyst.com of layers. The activity of micromotors increases with an increase respond to the direction change of the static magnetic field, in H2O2 concentration, and therefore displays a net motion (or but they show a different motion behavior. propulsion) (Figure 3A, Video S1, Supporting Information). In detail, when the external magnetic field direction changes, With the absence of an external magnetic field, this net propul- we observed that IP micromotors did not align their propulsion sion exhibits a random trajectory. This is because the rotational direction with the direction of the external magnetic field and diffusion around the micromotor randomizes the reorientation maintained an offset angle of around 45°, which is approximated of the catalytic surface.[8,12] When a weak static magnetic field from the open-loop controlled motion trajectories, to the was applied in-plane (parallel to the x- or y-axis), we observed that field direction (Figure 3C, c(H2O2) = 7.5 wt%, b = 2 mT, both micromotors with IP or OP magnetic anisotropy aligned M5 μmPt2 nm(Co0.4 nm/Pt0.6 nm)20Pt15 nm). Due to an offset angle their magnetic moment to the external magnetic field, suppress- between the effective magnetization direction and the horizontal ing the random reorientation of the body caused by rotational plane of Co/Pt bilayers, the OP micromotor could not always diffusion effects, and therefore presenting a directional move- align its swimming direction with the direction of the external ment. Indeed, as shown in Figure 3B, a trajectory of the micro- magnetic field, but showed an offset that varied at motor showed a straight line in response to an applied magnetic around 135° (Figure 3D, c(H2O2) = 7.5 wt%, b = 2 mT, field, compared to the random motion without an applied mag- M5 μmPt5 nm(Co0.4 nm/Pt1.5 nm)5Pt15 nm). From our study, we netic field (Figure 3A). Note that the experimental conditions observed that this type of magnetic property can be easily used are c(H2O2) = 7.5 wt%, b = 2 mT, and a motor with changed during the deposition process of Co/Pt multi-layers. M10 μmPt2 nm(Co0.4 nm/Pt0.6 nm)5Pt15 nm. However, once the offset angle of the magnetic property of To demonstrate the directional controllability of these self- the motor has been measured, the propulsion trajectory can propelled Janus micromotors, the direction of the applied static be precisely controlled under any static magnetic field applied. magnetic field was sequentially changed, and the micromotors’ locomotion behavior was recorded, as shown in Figure 3C,D (Video S2, S3, Supporting Information). A much richer motion 2.4. Motion Characterization of Janus Micromotors behavior is observed in our system compared to the previously reported magnetic Janus micromotor’s motion.[6,31] Micromotors To thoroughly explore the motion dynamics of our micromotors, with both IP and OP magnetic properties can immediately we further evaluated their motion with different parameters A B OFF ON b 50 µm 50 µm C i b ii b iii b iv b v b 50 µm D i ii iii iv v b b b b b 50 µm Figure 3. A) A random movement trajectory of a magnetic Janus micromotor in a 7.5 wt% H2O2 solution with surfactant but without static magnetic field. B) A microscope image of a magnetic Janus micromotor swimming in a 7.5 wt% H2O2 solution with surfactant under a weak static magnetic field of 2 mT. C,D) The time-lapse images of trajectories for the: (C) IP and (D) OP micromotors with the composition of M5 μmPt2 nm(Co0.4 nm/Pt0.6 nm)20Pt15 nm and M5 μmPt5 nm(Co0.4 nm/Pt1.5 nm)5Pt15 nm, in 7.5 wt% H2O2 solution under a weak static magnetic field of 2 mT. Adv. Intell. Syst. 2022, 4, 2200192 2200192 (5 of 11) © 2022 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH 26404567, 2022, 11, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/aisy.202200192 by Readcube (Labtiva Inc.), Wiley Online Library on [28/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License www.advancedsciencenews.com www.advintellsyst.com (different fluid solutions, size of the motor, and magnetic prop- bubbles and micromotors. The surfactant lowers the surface ten- erties) under a weak static magnetic field of 2 mT. First, the influ- sion by absorbing at the gas–liquid interface, breaking oxygen ence of the surfactant was investigated, Video S5, Supporting bubbles at lower pressure between the inside and the outside Information, shows the motion behavior of our micromotors of the bubbles. This results in a smaller bubble size at a very close in H2O2 solution without surfactant under a static magnetic field vertical distance between the bubble and the micromotor. The of 2 mT. We observed that a very low rate of bubble bursting collapse frequency of the oxygen bubble increases as the bubble occurred at a distance far from the surface of the motor. size decreases, as the total oxygen production remains the same Without the additive, the surface tension around the bubble con- under the same concentration of H2O2. In addition, the proba- tinuously increased as the size of the bubble grew over time, until bility of the micromotors being trapped in smaller bubbles also the bubbles and the micromotors could no longer align in the reduces. As a proof, the overall speed of the motor with surfac- same horizontal plane because of their different densities. At tant showed a much higher speed, compared to that of the a relatively large distance in the vertical direction between the “without” case (Figure 4A). We also discovered that in a relatively bubble and the micromotors, the bubble bursts in the negative low concentration in the H2O2 region (0–7.5 wt%), the speed of normal direction to the in-plane of the motor. This implies that the micromotor shows a linear behavior with the H2O2 concen- the bubble generation and bursting process do not contribute tration due to the enhanced evolution and ejection rates of the much to the in-plane motion of the micromotors. With this oxygen bubbles. With a further increase in the concentration knowledge, we concluded that, in this case, the propulsion of the H2O2, the speed of the micromotors velocity was finally mechanism of the micromotors is dominated by the self- saturated, reaching the maximum speed of 145  25.07 μm s1 diffusiophoresis mechanism as a result of the diffusion of the due to the limited catalytic surface area and progressively dissolved oxygen molecules. saturated H2O2 decomposition rate. However, with the surfactant, we observed that the movement These variations in the propulsion mechanism were also of the micromotors occurred as a result of the bubble recoil observed by Zhang et al.[32] For Janus micromotors with a diam- mechanism, as the bubble formation and collapse frequently eter smaller than 5 μm, the motion is generated by self-diffusio- occurred at a high rate in the same horizontal plane of the phoresis.[32] During the chemical catalytic reaction, hydrogen A 180 B 250 Exp With Surfactant Sim Exp Diameter 10 m Sim 160 Exp Diameter 5 m Sim Exp Without Surfactant Sim 140 200 Speed ( m/s) Speed ( m/s) 120 150 100 80 100 60 40 50 20 0 0 0 5 10 15 20 25 0 5 10 15 20 25 c(H 2O2) (%) c(H 2O2) (wt%) C 200 D 250 Exp In-plane Sim Exp 5 Co/Pt Bilayers Sim Exp Out-of-plane Sim Exp 10 Co/Pt Bilayers Sim 200 150 Exp 20 Co/Pt Bilayers Sim Speed ( m/s) Speed ( m/s) 150 100 100 50 50 0 0 0 5 10 15 20 25 0 5 10 15 20 25 c(H O ) (wt%) c(H O ) (wt%) 2 2 2 2 Figure 4. A) The average speed of Janus micromotors propulsion with surfactant (black line) and without surfactant (red line). B) The average speed profiles of Janus micromotors with diameters of 10 μm (black line) and 5 μm (red line). C) The average speed profiles of IP (black line) and OP (red line) Janus micromotors. D) The average speed profiles of Janus micromotors with 5 (black line), 10 (red line), and 20 (yellow line) numbers of Co/Pt bilayers. Solid lines: experiment results. Dotted lines: simulation results. All bar plots represent a mean value SD (n = 5). Adv. Intell. Syst. 2022, 4, 2200192 2200192 (6 of 11) © 2022 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH 26404567, 2022, 11, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/aisy.202200192 by Readcube (Labtiva Inc.), Wiley Online Library on [28/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License www.advancedsciencenews.com www.advintellsyst.com peroxide is consumed, and new oxygen molecules are generated catalytic surface area and catalytic composition, the driving force at the catalytic side of the Janus micromotor. This asymmetric (which is dependent on the production rate of oxygen bubbles) reaction induces concentration gradients produced by oxygen and the drag force remain the same. The magnetization direction molecules, resulting in a directional fluid flow near the particle of micromotors does not contribute to the propulsion of micro- surface.[5,33] Consequently, the Janus micromotors move in the motors but only affects their orientation. The negligible velocity opposite direction of the flow with the reactive side facing back- difference could be attributed to the subtle distinctive roughness ward. As the size of Janus micromotors increases to 10 μm or of the exposed Pt surface, resulting in a slight difference in the more, the generated oxygen molecules can nucleate bubbles surface area. on the particles’ surface and the bubbles collapse. This series Finally, the influence of the magnetic composition of of reactions causes Janus micromotors to be self-propelled, multilayer thickness, i.e., the number of Co/Pt bilayers, was which is known as a bubble recoil mechanism. In addition, they investigated. Figure 4D presents a motion comparison of micro- argued that a Janus micromotor shows a time-variant propulsion motors with periodical numbers of 5, 10, and 20. We observed mechanism, which can be explained in three stages. In the first that the micromotors with a thicker Co/Pt bilayer moved slightly stage (or at the very beginning of the propulsion), invisible oxy- faster than the micromotors with thinner Co/Pt bilayers. gen bubbles form on the surface of the micromotors. The motion Although the reaction only occurred at the surface of the micro- is dominated by a diffusiophoretic force, caused by the concen- motors, the magnetic remanence is enhanced with a higher con- tration gradient of invisible dissolved oxygen molecules sur- tent of Co, and a significantly more stable-oriented locomotion rounding the motor’s body by H2O2 decomposition. At this was observed during the experiments. With a more directed tra- stage, the speed of the motor is around 5 μm s1 due to the weak jectory, the average speed will be slightly higher, while the instan- force exerted by the molecular diffusion. In the second stage, the taneous speed will remain the same. In addition, as the number dissolution of the oxygen molecules becomes locally saturated, of the Co/Pt bilayers increases, the diameter of the micromotor and as a consequence, visible oxygen bubbles start to nucleate and the surface area also increases. A larger surface area can lead on the surface of the Janus micromotor. The motion speed to a higher catalytic reaction rate, which may also contribute to increases linearly with the bubble growth, displaying a speed the increased propulsion velocity of Janus micromotors. of 500 μm s1. In the third stage, the bubble reaches its maxi- mum size and finally collapses. The horizontal component of 2.5. Theoretical Analysis bubble cavitation induces a jet stream on the motor, providing a substantial force on the Janus micromotor. This allows an To assess the consistency of the experimental observations, we instantaneous maximum speed of up to 0.1 m s1.[32,34,35] investigated the dynamic model of the MJM in detail. To do Before presenting such an instantaneous forward movement, so, the MJM was assumed to be a spherical particle with two the micromotors are sometimes pulled back by the bubble after distinguishable hemispheres (Figure 1C). With no movement the bubble collapses, which is known as quasi-oscillatory in the vertical direction, and for the sake of simplicity, we motion.[36] reduced the system to a two-dimensional (2D) problem in the To study the influence of a motor size on the motion of Janus xy-plane. This problem reduction is compatible with the obser- micromotors, micromotors with two different diameters (5 and vation of the MJM under an optical microscope. 10 μm) were used and investigated at different concentrations of The magnetic material within the MJM revealed a magnetic H2O2 solution with surfactant under an applied magnetic field. anisotropy that can be either in-plane or out-of-plane. The applied Note that we only changed the diameter of MJM, while the Co/Pt magnetic field b ¼ ðb, φÞ, with b the magnitude and φ its direc- layers remain unchanged (Co0.4 nm/Pt0.6 nm)5Pt15 nm. Figure 4B tion, is used only for directional control, and the MJM’s magnetic presents the speed of the motors, obtained from the regions moment m tends to be aligned with b∶m ¼ m jjbjj b . where the trajectories were linear. We can see that the average velocity almost doubled with the change in the diameter of the Typically, the self-phoretic swimming velocity is expressed as: micromotors in the overall concentration range of H2O2. The vp ¼ v0 ex , where ex is the easy axis of the MJM and v0 is the sta- larger catalytic surface of the larger diameter of the micromotors tionary swimming velocity (Figure 1C). As previously mentioned, permits a higher rate of oxygen bubble generation that propels the self-propulsion of the MJM can be either self-diffusiophoresis the micromotors at a higher speed. However, when the speeds or bubble recoil propulsion mechanisms. In ref., [21] we only convert to the scale in the body per length, both fall to a similar addressed the dynamic modeling for the self-diffusiophoresis level. While the driving and drag forces increase with the case, and it is our aim to further extend the model to consider dimension of the micromotors, the relative velocity of displace- both cases. Under diffusiophoresis conditions, the stationary μ a ment per body length remains the same. velocity can be roughly approximated by v0 ∝ Dp . The surface Furthermore, we analyzed the effect of the magnetization activity a describes the catalytic activity on the MJM, which is direction of the Janus micromotors on their propulsion behavior the production or consumption of solute by catalytic reaction. by comparing micromotors with two different magnetic proper- μp is known as the local “phoretic mobility.” The transport coeffi- ties (IP and OP). Figure 4C shows that the speed profile of micro- cient D describes the efficiency with which a gradient ∇f is motors in the IP and OP cases shows a similar trend and velocity smoothed out in the fluid and is then related to the diffusion magnitude from a low concentration of H2O2 to a saturated con- coefficient. centration of H2O2. This result indicates that the magnetization The bubble recoil propulsion mechanism is governed by the direction does not have a significant influence on the average Rayleigh–Plesset equation,[37] where the bubble growth and speed of the micromotors along the directed path. With the same release are the main steps.[36] When the bubble reaches a Adv. Intell. Syst. 2022, 4, 2200192 2200192 (7 of 11) © 2022 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH 26404567, 2022, 11, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/aisy.202200192 by Readcube (Labtiva Inc.), Wiley Online Library on [28/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License www.advancedsciencenews.com www.advintellsyst.com maximum size, it imposes a strong impulse to push the MJM in falls to rank fCðxÞg ¼ 4, ∀θ ¼ n π2. Therefore, the SDC system the opposite direction. However, the bubble departure is difficult (4) is not fully controllable over the entire control domain. to predict as it is influenced by a variety of factors, such as the rate However, without input u ¼ 0 and Brownian disturbance, of bubble growth, interfacial tension, liquid pressure, and buoy- ξ ¼ 0, it can be shown that the MJM dynamic stabilizes at an ancy. Without the ability to observe bubble growth, the stationary equilibrium state x0 . Hence, if the Brownian disturbance is small velocity during the bubble growth/release can be approximated enough, the MJM could be assumed stabilizable. However, when from the average: v0 ¼ hV 0 ðtÞi, with V 0 ðtÞ the instantaneous self- the self-diffusiophoretic velocity v0 is not considered as a control phoretic velocity. The instantaneous self-phoretic velocity relies input and is then added to the state vector x, the corresponding on some empirical constants to be determined by high-speed SDC observability matrix remains full rank with rank recording.[36] fOðxÞg ¼ 7, ∀x ∈ ℝ7 ; whereas the corresponding SDC controlla- Any object moving in a viscous fluid can be described by bility matrix has a maximum rank fCðxÞg ¼ 2 < 7. Newton’s second law. For an MJM, this law classically includes the self-phoretic propulsion mechanism, the magnetic guidance, 2.6. Experimental Validation the drag force, and the Brownian motion,[21] as shown in Equation (S7), Supporting Information. This helps in expressing To assess the consistency of the modeling, different experiments the system dynamics as follows. have been conducted. Specifically, in this study, we mainly used : the dynamic model to estimate or predict the MJM behavior x ¼ vx ðSx Þ : (1) under different conditions. From the observation of the behavior vx ¼ αx vx þ αx cosðθÞu0 þ ξx of the MJM, the state-dependent coefficient robust two-stage : Kalman filter (SDC-RTSKF) algorithm was used to estimate both y ¼ vy ðSy Þ : (2) the state and the input of the pseudo-linear system (1–3). Indeed, vy ¼ αy vy þ αy sinðθÞu0 þ ξy some of the system parameters are not well known (e.g., mag- : netic properties, catalytic activities, exact shape, etc.) and θ¼ω ðSθ Þ : (3) they can vary significantly from one MJM to another. ω ¼ αω ω þ βðsinðφÞbx þ cosðφÞby Þ þ ξθ Consequently, the system inputs are not fully known and may where αx,y,θ are the ratios of drag coefficient over mass/inertia of even be uncontrollable. SDC-RTSKF gives optimal state estima- the MJM, β is the magnetization over inertia ratio, and ξx,y,θ tions that are independent of the values of unknown inputs. Figure 5A,B shows an example of the real-time estimated tra- denotes the stochastic force and torque due to random fluctua- jectories of three MJMs with a size of around 9 μm immersed in tions. ðx, y, θÞ are the position and orientation, and ðvx , vy , ωÞ are an aqueous solution of 20% H2O2 without surfactant and with an the linear and angular velocities of the MJM. By considering that applied magnetic field magnitude of jjbjj ¼ 2mT. As no bubble the position and orientation of the MJM can be measured, was observed, a self-diffusiophoresis mechanism was considered and the control input is u ¼ ðv0 , bx , by Þ, the previous representa- here. In this context, the self-diffusiophoretic velocity was esti- tion can be rewritten in a 2D state-space representation with a mated to be around u0  3 μms1 (Figure S4D, Supporting pseudo-linear form Information). This is comparable to previously reported speeds : for MJMs in literature.[6,7,16,18] The distributionof the tracking x ¼ Ax þ BðxÞu þ ξ error between the measured output y and its estimation ŷ using (4) y ¼ Cx þ v the SDC-RTSKF are shown within the box plots in Figure S4A,B, Supporting Information. The position tracking errors remain with ξ  N ð0, QÞ a white Gaussian distribution computed from more or less identical for the 3 estimated trajectories. For the Brownian motion and ν  N ð0, RÞ the observation noise instance, for the second trajectory (#2), the corresponding which is assumed to be zero mean Gaussian white noise with root mean square errors (RMSE) of the position of the MJM is covariance matrices Q and R. RMSEðp  b pÞ ¼ 0.168 μm. The SDC-RTSKF, together with the The system (4) exhibits a pseudo-linear structure having an proposed modeling, provides a reasonable estimation of the SDC form. An important issue is to analyze the properties of behavior of the MJM. Indeed, the SDC-RTSKF outperforms the the pseudo-linear system. As in the linear control theory, the previous SDC-DKF proposed in,[21] where RMSEðp  b pÞ ¼ 0.5 μm SDC observability and the SDC controllability matrices are was reported. The improvements are related to a better knowledge defined here as follows. of the system parameters and better modeling.   In this experiment, the applied magnetic field b is a known OðxÞ ≜ C CA CA2 : : : CA5 t (5) input and serves as the ground truth to assess the accuracy   CðxÞ ≜ BðxÞ ABðxÞ A2 BðxÞ : : : A5 BðxÞ (6) of the estimated magnetic field b̂. Figure S4C, Supporting Information, shows the magnetic field error distribution. With If the matrices OðxÞ, resp. CðxÞ, have full rank for the entire an average RMSE of 0.106 mT, the SDC-RTSKF provides a domain for which the system is to be observed (resp. controlled), fully satisfactory input estimation. In contrast, the real self- then the SDC parametrization is said to be observable and con- diffusiophoretic stationary velocity is not well known. A good trollable.[38] It can be shown that the pseudo-linear system (1–3) estimate of the magnetic field inputs suggests that the self- is fully observable ∀x ∈ ℝ6 . In contrast, the SDC controllability diffusiophoretic velocity estimation û is properly determined matrix CðxÞ of the MJM has a maximum rank fCðxÞg ¼ 6, and (Figure S4D, Supporting Information). These results validate Adv. Intell. Syst. 2022, 4, 2200192 2200192 (8 of 11) © 2022 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH 26404567, 2022, 11, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/aisy.202200192 by Readcube (Labtiva Inc.), Wiley Online Library on [28/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License www.advancedsciencenews.com www.advintellsyst.com A C E Measure Last Measure Estimation Last Estimation 100 µm 100 µm 100 µm B D F Measure 60 Measure -20 Near Estimation1 400 Estimation2 Estimation Estimation3 50 300 -10 y (µm) y (µm) y (µm) 40 200 0 30 100 10 Far 80 90 100 110 120 130 100 200 300 400 500 -10 0 10 20 30 40 x (µm) x (µm) x (µm) Figure 5. An example of the evolution of a magnetic Janus micromotor: A) A captured image of MJMs propelled by self-diffusiophoresis from a digital microscope. B) Measured and tracked paths using the state-dependent coefficient robust two-stage Kalman filter (SDC-RTSKF). C) A captured micro- scope image of a magnetic steerable catalytic Janus micromotor (MJM) propelled by bubble recoil mechanism in solution with surfactant. D) The mea- sured and tracked path using the SDC-RTSKF. E) A microscope image of an MJM propelled by bubble recoil with its last positions estimated from different timestamps prior, and F) Last MJM positions estimated from different prediction horizons ahead (from the beginning to the end of the experiment) using the SDC-RTSKF. the consistency of the proposed dynamic model describing the observations and simulations provide similar propulsion behavior of MJM, while allowing access to the unknown input. results as those reported in Figure 4. In particular, the improved SDC-RTSKF offers better perfor- The MJM dynamic model can also be used to predict the mance on the estimation with a simplified implementation. behavior of the swimmer in an early stage of the experiment. Figure 5C,D (Video S6, Supporting Information) shows Figure 6A shows the real-time predicted MJM trajectories that the real-time estimated trajectory results when the bubble were estimated with 0, 1, 2, 5, and 10 timestamps prediction hori- recoil mechanism is observed. However, here the RMSE zon using the SDC-RTSKF. We can see that as the prediction on the position of the MJM is increased to horizon decreases, the prediction accuracy increases. RMSEðp  b pÞ ¼ 4.185 μm. This increase is notably due to Figure 5E,F (Video S7, Supporting Information) reports the the use of only the average velocity of the bubble recoil real-time last position estimate from the first step (far) to the last mechanism. Despite this, the model is sufficiently relevant step (near) of the experiment. At a distance from the last position, to describe the behavior of MJMs in so far as the experimental the position error is 14.11 μm and decreases to 4.43 μm just A B 25 20 c(H O ) (%) 15 2 2 10 5 Exp With Surfactant Sim Exp Without Surfactant Sim 0 0 20 40 60 80 100 120 140 160 180 Speed ( m/s) Figure 6. A) The measured and tracked paths of an MJM propelled by the bubble recoil mechanism in H2O2 solution with surfactant. The predicted trajectories were estimated with 0, 1, 2, 5, and 10 timestamps prediction horizons using the SDC-RTSKF. When the prediction horizon decreases, the prediction accuracy increases. B) Estimated H2O2 concentration from MJM propulsion speed. Adv. Intell. Syst. 2022, 4, 2200192 2200192 (9 of 11) © 2022 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH 26404567, 2022, 11, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/aisy.202200192 by Readcube (Labtiva Inc.), Wiley Online Library on [28/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License www.advancedsciencenews.com www.advintellsyst.com before the last step (at the end of the experiment). Even though of MJM were characterized at room temperature using a vibrating sample each position prediction provides a rough estimate of the last true magnetometer (VSM EZ9, Microsense). The magnetic hysteresis curves of position, the last few steps are enough to properly predict the last the MJM were recorded along the 0° (in-plane) and 90° (perpendicular-to- plane) directions of the Si substrates before the spheres were detached MJM position, which helps in an early control of MJM from the substrate using sonication methods. During the VSM analysis, propulsion. However, the coarse predictions are mainly due to to eliminate the diamagnetic contribution of the substrate, a linear func- the bubble recoil model, where the departure of the bubble tion was fitted with the raw VSM data at high magnetic fields. The fitted cannot be accurately predicted as it is influenced by many factors. linear slope was then subtracted from the raw VSM data at the whole range Another interesting point we address here is that once the of the magnetic field. Since the mass of a single MJM metal film cannot be propulsion mechanism of the MJM motion is known, the directly measured, each magnetic hysteresis curve was normalized by its SDC-RTSKF can be exploited as a concentration sensor with saturation magnetization, Ms. Aqueous Solution Preparation: Hydrogen peroxide solutions with its ability to estimate the H2O2 concentration by measuring concentrations of 0–25 wt% were prepared by dilutions of 30% hydrogen the propulsion speed of particles (Figure 6B). This demonstrates peroxide solution (Sigma Aldrich) with deionized water. Droplets of the potential application of SDC-RTSKF as a biosensing tool. In sodium dodecyl sulfate (Sigma Aldrich) solution were added to the hydro- addition, when the propulsion mechanism of the MJM motion gen peroxide solutions as a surfactant to inhibit the coalescence of oxygen cannot be determined, for example, at low H2O2 concentrations, bubbles. The final concentrations of hydrogen peroxide in the solution the SDC-RTSKF can be used to determine the motion mecha- were 0, 2.5, 5, 7.5, 10, 15, 20, and 25 wt%, and the final concentration of sodium dodecyl sulfate in the mixed solution was 5 wt%. nism of the MJM as well as predict the motion properties that Magnetic Motion Control and Characterization: A prepared colloidal have not been discovered in the experiments. This method solution of Janus particles and an aqueous solution of H2O2 were dripped has strong generality and can therefore be universally applied onto a clean glass substrate. The substrate with the mixed colloidal H2O2 to any catalytic micro-/nanomotors, regardless of their shapes, solution was then transferred to the center of the Magnebotix Nanomag. A sizes, material compositions, and catalytic reactions. uniform magnetic field of 2 mT was generated by Nanomag to guide the directional propulsion of the micromotors. The motion of micromotors was then observed with an inverted microscopy (Olympus IX 81, Olympus Optical Co. Ltd., Japan) and recorded by a high-speed camera. 3. Conclusions The mean speed of each set of micromotors swimming in a certain concentration of H2O2 was analyzed from at least three distinct Janus In this study, we have demonstrated that the system dynamics of samples, and each sample velocity was averaged over five velocity a magnetic Janus catalytic micromotor can be estimated through measurements with a motion period longer than one second. an SDC-RTSKF even if the control inputs for the MJM guidance are not sufficiently identified. We found that there is good agreement between the dynamics computed from our theoretical Supporting Information predictions and the experimental observations. The proposed MJM modeling offers an analytic description that opens the Supporting Information is available from the Wiley Online Library or from way to explicit and advanced control strategies. Similarly, the the author. SDC-RTSKF is the first attempt to combine the SDC filter with a common RTSKF methodology. The use of the proposed MJM’s model can be extended to different micro/nanomotors such as a Acknowledgements nanorod or conical microjet by adapting the swimming velocity J.W. and D.F. contributed equally to this work. This project has received and the hydrodynamics analytical expressions. funding from the European Union’s Horizon 2020 research and innova- tion programme under the Marie Sklodowska-Curie grant agreement No. 764977, the Spanish (PID2020-116844RB-C2 and PID2020-116844RB- 4. Experimental Section C21) and Catalan (2017-SGR-0292) research administrations, and the National Research Foundation of Korea (NRF) grant funded by the Fabrication of Janus Micromotors: The fabrication of Janus micromotors Korea government (MSIT) (No. 2022R1C1C1007338). mainly involves two procedures: the self-assembly of a SiO2 microsphere monolayer[39] and bottom-up deposition of metal films. First, a droplet of silica microsphere (Whitehouse Scientific) water solution was released onto a clean silicon wafer. After the solvent slowly evaporated, a monolayer Conflict of Interest of SiO2 microspheres was formed by self-assembly. The diameters of the The authors declare no conflict of interest. SiO2 microspheres used in this study were 5 and 10 μm, respectively. Subsequently, a thin layer of Pt with a thickness of 2 nm/5 nm was sputtered on top of the silica microsphere monolayer to improve the adhesion condition. Next, n number of Co(tCo)/Pt(tPt2) magnetic bilayers Data Availability Statement were deposited on top of the Pt addition layer by DC magnetron sputtering under a base pressure of 1  107 mbar and Ar pressure of 8  103 mbar. The data that support the findings of this study are available in the Afterward, a Pt layer with a thickness of 15 nm was deposited on top of the supplementary material of this article. [Co(tCo)/Pt(tPt2)]n multilayer stacks to protect the surface from oxidization as well as preserve the catalytic properties. No annealing procedure was followed afterward. Finally, arrays of Janus micromotors were detached from the silicon wafer by ultrasonication in deionized water. Keywords Characterization of Janus Micromotors: SEM (Quanta 200F FEI) and EDX microscopy images were taken to characterize the morphology and the bubble recoil propulsion, catalytic swimmers, directionality control, composition of the magnetic Janus micromotors. The magnetic properties magnetic Janus particles, real-time trajectory prediction Adv. Intell. Syst. 2022, 4, 2200192 2200192 (10 of 11) © 2022 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH 26404567, 2022, 11, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/aisy.202200192 by Readcube (Labtiva Inc.), Wiley Online Library on [28/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License www.advancedsciencenews.com www.advintellsyst.com Received: July 6, 2022 [19] J. Li, O. E. Shklyaev, T. Li, W. Liu, H. Shum, I. Rozen, A. C. Balazs, Revised: August 18, 2022 J. Wang, Nano Lett. 2015, 15, 7077. Published online: September 21, 2022 [20] C.-S. Hsieh, IEEE Trans. Autom. Control 2000, 45, 2374. [21] D. Folio, A. Ferreira, IEEE Trans. Control Syst. Technol. 2022, 1, https://doi.org/10.1109/TCST.2021.3139192. [1] K. K. Dey, A. Sen, J. Am. Chem. Soc. 2017, 139, 7666. [22] P. Yánez-Sedeño, S. Campuzano, J. Pingarrón, Appl. Mater. Today [2] M. Fernández-Medina, M. A. Ramos-Docampo, O. Hovorka, 2017, 9, 276. V. Salgueiriño, B. Städler, Adv. Funct. Mater. 2020, 30, 1908283. [23] N. Nakajima, T. Koide, T. Shidara, H. Miyauchi, H. Fukutani, [3] B. E.-F. de Ávila, P. Angsantikul, J. Li, M. Angel Lopez-Ramirez, A. Fujimori, K. Iio, T. Katayama, M. Nývlt, Y. Suzuki, Phys. Rev. D. E. Ramírez-Herrera, S. Thamphiwatana, C. Chen, J. Delezuk, Lett. 1998, 81, 5229. R. Samakapiruk, V. Ramez, M. Obonyo, L. Zhang, J. Wang, [24] J. Yan, S. C. Bae, S. Granick, Adv. Mater. 2015, 27, 874. Nat. Commun. 2017, 8, 272. [25] R. Streubel, P. Fischer, F. Kronast, V. P. Kravchuk, D. D. Sheka, [4] M. Guix, C. C. Mayorga-Martinez, A. Merkoçi, Chem. Rev. 2014, 114, Y. Gaididei, O. G. Schmidt, D. Makarov, J. Phys. D: Appl. Phys. 6285. 2016, 49, 363001. [5] R. Golestanian, T. Liverpool, A. Ajdari, New J. Phys. 2007, 9, 126. [26] F. Den Broeder, W. Hoving, P. Bloemen, J. Magn. Magn. Mater. 1991, [6] L. Baraban, D. Makarov, R. Streubel, I. Monch, D. Grimm, S. Sanchez, 93, 562. O. G. Schmidt, ACS Nano 2012, 6, 3383. [27] J. Sort, V. Baltz, F. Garcia, B. Rodmacq, B. Dieny, Phys. Rev. B 2005, [7] I. S. Khalil, V. Magdanz, S. Sanchez, O. G. Schmidt, S. Misra, Int. J. 71, 054411. Adv. Rob. Syst. 2015, 12, 2. [28] R. D. Shull, Y. Iunin, Y. Kabanov, V. I. Nikitenko, O. Skryabina, [8] J. R. Howse, R. A. Jones, A. J. Ryan, T. Gough, R. Vafabakhsh, C. Chien, J. Appl. Phys. 2013, 113, 17C101. R. Golestanian, Phys. Rev. Lett. 2007, 99, 048102. [29] J. E. Davies, O. Hellwig, E. E. Fullerton, G. Denbeaux, J. Kortright, [9] R. F. Dong, Q. L. Zhang, W. Gao, A. Pei, B. Y. Ren, ACS Nano 2016, K. Liu, Phys. Rev. B 2004, 70, 224434. 10, 839. [30] M. Köppl, P. Henseler, A. Erbe, P. Nielaba, P. Leiderer, Phys. Rev. Lett. [10] H. Wang, G. Zhao, M. Pumera, J. Am. Chem. Soc. 2014, 136, 2719. 2006, 97, 208302. [11] X. Ma, A. Jannasch, U.-R. Albrecht, K. Hahn, A. Miguel-López, [31] L. Baraban, D. Makarov, O. G. Schmidt, G. Cuniberti, P. Leiderer, E. Schaffer, S. Sánchez, Nano Lett. 2015, 15, 7043. A. Erbe, Nanoscale 2013, 5, 1332. [12] L. Baraban, M. Tasinkevych, M. N. Popescu, S. Sanchez, S. Dietrich, [32] J. Zhang, X. Zheng, H. Cui, Z. Silber-Li, Micromachines 2017, O. Schmidt, Soft Matter 2012, 8, 48. 8, 123. [13] S. Wang, N. Wu, Langmuir 2014, 30, 3477. [33] J. L. Anderson, Annu. Rev. Fluid Mech. 1989, 21, 61. [14] H. Eskandarloo, A. Kierulf, A. Abbaspourrad, Nanoscale 2017, 9, [34] C. E. Brennen, Cavitation and Bubble Dynamics, Cambridge University 13850. Press, New York, NY 2014. [15] B. Jang, W. Wang, S. Wiget, A. J. Petruska, X. Chen, C. Hu, A. Hong, [35] E. Zwaan, S. Le Gac, K. Tsuji, C.-D. Ohl, Phys. Rev. Lett. 2007, 98, D. Folio, A. Ferreira, S. Pané, ACS Nano 2016, 10, 9983. 254501. [16] X. Ma, X. Wang, K. Hahn, S. Sánchez, ACS Nano 2016, 10, [36] M. Manjare, B. Yang, Y.-P. Zhao, Phys. Rev. Lett. 2012, 109, 3597. 128305. [17] T. Li, X. Chang, Z. Wu, J. Li, G. Shao, X. Deng, J. Qiu, B. Guo, [37] J.-P. Franc, J.-M. Michel, Fundamentals of Cavitation, Vol. 76, Kluwer G. Zhang, Q. He, ACS Nano 2017, 11, 9268. Academic Publisher, Dordrecht 2006. [18] S. Das, E. B. Steager, M. A. Hsieh, K. J. Stebe, V. Kumar, Journal of [38] H. Banks, B. Lewis, H. T. Tran, Comput. Optim. Appl. 2007, 37, 177. Micro-Bio Rob. 2018, 14, 25. [39] R. Micheletto, H. Fukuda, M. Ohtsu, Langmuir 1995, 11, 3333. Adv. Intell. Syst. 2022, 4, 2200192 2200192 (11 of 11) © 2022 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH