The emerging field of self-propelling micro/nanorobots is teeming with a wide variety of novel micro/nanostructures, which are tested here for self-propulsion in a liquid environment. As the size of these microscopic movers diminishes into the fully nanosized region, the ballistic paths of an active micromotor become a random walk of colloidal particles. To test such colloidal samples for self-propulsion, the commonly adopted "golden rule" is to refer to the mean squared displacement (MSD) function of the measured particle tracks. The practical significance of the result strongly depends on the amount of collected particle data and the sampling rate of the particle track. Because micro/nanomotor preparation methods are mostly low-yield, the amount of used experimental data in published results is often on the edge of reproducibility. To address the situation, we perform MSD analysis on an experimental as well as simulated dataset. These data are used to explore the effects of MSD analysis on limited data and several situations where the lack of data can lead to insignificant results.

Center for Advanced Functional Nanorobots Dept of Inorganic Chemistry Faculty of Chemical Technology University of Chemistry and Technology Prague Technická 5 Prague CZ 166 28 Czech Republic

Department of Chemical and Biomolecular Engineering Yonsei University 50 Yonsei ro Seodaemun gu Seoul 03722 Korea

Future Energy and Innovation Laboratory Central European Institute of Technology Brno University of Technology Purkyňova 656 123 Brno CZ 616 00 Czech Republic

Zobrazit více v PubMed

Li J, Rozen I, Wang J. Rocket Science at the Nanoscale. ACS Nano. 2016;10:5619–5634. doi: 10.1021/acsnano.6b02518. PubMed DOI

Gao W, Wang J. The Environmental Impact of Micro/Nanomachines: A Review. ACS Nano. 2014;8:3170–3180. doi: 10.1021/nn500077a. PubMed DOI

Li J, Esteban-Fernández de Ávila B, Gao W, Zhang L, Wang J. Micro/nanorobots for biomedicine: Delivery, surgery, sensing, and detoxification. Sci. Robot. 2017;2:eaam6431. doi: 10.1126/scirobotics.aam6431. PubMed DOI PMC

Orozco J, et al. Bubble-Propelled Micromotors for Enhanced Transport of Passive Tracers. Langmuir. 2014;30:5082–5087. doi: 10.1021/la500819r. PubMed DOI

Ezhilan B, et al. Motion-based threat detection using microrods: experiments and numerical simulations. Nanoscale. 2015;7:7833–7840. doi: 10.1039/C4NR06208F. PubMed DOI

Lee T-C, et al. Self-Propelling Nanomotors in the Presence of Strong Brownian Forces. Nano Lett. 2014;14:2407–2412. doi: 10.1021/nl500068n. PubMed DOI PMC

Kong, L., Mayorga-Martinez, C. C., Guan, J. & Pumera, M. Fuel-Free Light-Powered TiO2/Pt Janus Micromotors for Enhanced Nitroaromatic Explosives Degradation. ACS Appl. Mater. Interfaces (2018). PubMed

Li Jinxing, Liu Wenjuan, Wang Jiyuan, Rozen Isaac, He Sha, Chen Chuanrui, Kim Hyun Gu, Lee Ha-Jin, Lee Han-Bo-Ram, Kwon Se-Hun, Li Tianlong, Li Longqiu, Wang Joseph, Mei Yongfeng. Nanoconfined Atomic Layer Deposition of TiO2 /Pt Nanotubes: Toward Ultrasmall Highly Efficient Catalytic Nanorockets. Advanced Functional Materials. 2017;27(24):1700598. doi: 10.1002/adfm.201700598. DOI

Gao W, Wang J. Synthetic micro/nanomotors in drug delivery. Nanoscale. 2014;6:10486. doi: 10.1039/C4NR03124E. PubMed DOI

Nel A, Xia T, Madler L, Li N. Toxic potential of materials at the nanolevel. Science. 2006;311:622–7. doi: 10.1126/science.1114397. PubMed DOI

Tu Y, et al. Biodegradable Hybrid Stomatocyte Nanomotors for Drug Delivery. ACS Nano. 2017;11:1957–1963. doi: 10.1021/acsnano.6b08079. PubMed DOI PMC

Ha JW. Recent advances in single particle rotational tracking of plasmonic anisotropic gold nanoparticles under far-field optical microscopy. Appl. Spectrosc. Rev. 2016;51:552–569. doi: 10.1080/05704928.2016.1165688. DOI

Dunderdale G, Ebbens S, Fairclough P, Howse J. Importance of Particle Tracking and Calculating the Mean-Squared Displacement in Distinguishing Nanopropulsion from Other Processes. Langmuir. 2012;28:10997–11006. doi: 10.1021/la301370y. PubMed DOI

Copeland CR, et al. Subnanometer localization accuracy in widefield optical microscopy. Light Sci. Appl. 2018;7:31. doi: 10.1038/s41377-018-0031-z. PubMed DOI PMC

Saveyn H, et al. Accurate particle size distribution determination by nanoparticle tracking analysis based on 2-D Brownian dynamics simulation. J. Colloid Interface Sci. 2010;352:593–600. doi: 10.1016/j.jcis.2010.09.006. PubMed DOI

Berglund AJ. Statistics of camera-based single-particle tracking. Phys. Rev. E. 2010;82:011917. doi: 10.1103/PhysRevE.82.011917. PubMed DOI

Haiden C, Wopelka T, Jech M, Keplinger F, Vellekoop MJ. Sizing of Metallic Nanoparticles Confined to a Microfluidic Film Applying Dark-Field Particle Tracking. Langmuir. 2014;30:9607–9615. doi: 10.1021/la5016675. PubMed DOI

Malloy A, Carr B. NanoParticle Tracking Analysis – The HaloTM System. Part. Part. Syst. Charact. 2006;23:197–204. doi: 10.1002/ppsc.200601031. DOI

Cheng C-Y, Hsieh C-L. Background Estimation and Correction for High-Precision Localization Microscopy. ACS Photonics. 2017;4:1730–1739. doi: 10.1021/acsphotonics.7b00238. DOI

Diezmann A, von, Lee MY, Lew MD, Moerner WE. Correcting field-dependent aberrations with nanoscale accuracy in three-dimensional single-molecule localization microscopy. Optica. 2015;2:985–993. doi: 10.1364/OPTICA.2.000985. PubMed DOI PMC

Howse, J. R. et al. Self-Motile Colloidal Particles: From Directed Propulsion to Random Walk. Phys. Rev. Lett. 99 (2007). PubMed

Savin T, Doyle PS. Static and Dynamic Errors in Particle Tracking Microrheology. Biophys. J. 2005;88:623–638. doi: 10.1529/biophysj.104.042457. PubMed DOI PMC

Qian H, Sheetz MP, Elson EL. Single particle tracking. Analysis of diffusion and flow in two-dimensional systems. Biophys. J. 1991;60:910–921. doi: 10.1016/S0006-3495(91)82125-7. PubMed DOI PMC

Saxton MJ. Single-particle tracking: models of directed transport. Biophys. J. 1994;67:2110–2119. doi: 10.1016/S0006-3495(94)80694-0. PubMed DOI PMC

Martin DS, Forstner MB, Käs JA. Apparent Subdiffusion Inherent to Single Particle Tracking. Biophys. J. 2002;83:2109–2117. doi: 10.1016/S0006-3495(02)73971-4. PubMed DOI PMC

Heyde, C. C. Central Limit Theorem. In Wiley StatsRef: Statistics Reference, 10.1002/9781118445112.stat04559 (American Cancer Society, 2014).

Lubelski A, Sokolov IM, Klafter J. Nonergodicity Mimics Inhomogeneity in Single Particle Tracking. Phys. Rev. Lett. 2008;100:250602. doi: 10.1103/PhysRevLett.100.250602. PubMed DOI

Majka, M. et al. The effects of subdiffusion on the NTA size measurements of extracellular vesicles in biological samples. ArXiv Prepr. ArXiv170109001 (2017).

Saxton MJ. Single-particle tracking: the distribution of diffusion coefficients. Biophys. J. 1997;72:1744–1753. doi: 10.1016/S0006-3495(97)78820-9. PubMed DOI PMC

Nanorobot-Cell Communication via In Situ Generation of Biochemical Signals: Toward Regenerative Therapies

Trapping and detecting nanoplastics by MXene-derived oxide microrobots