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Emergence of reconfigurable wires and spinners via dynamic self-assembly.

Kokot G, Piet D, Whitesides GM, Aranson IS, Snezhko A - Sci Rep (2015)

Bottom Line: The energy injection rate, and properties of the environment are important control parameters that influence the outcome of dynamic self-assembly.The spinners emerge via spontaneous breaking of the uniaxial symmetry of the energizing magnetic field.Demonstration of the formation and disaggregation of particle assemblies suggests strategies to form new meso-scale structures with the potential to perform functions such as mixing and sensing.

View Article: PubMed Central - PubMed

Affiliation: Complex Matter Department, Jozef Stefan Institute, Jamova 39, 1000 Ljubliana, Slovenia.

ABSTRACT
Dissipative colloidal materials use energy to generate and maintain structural complexity. The energy injection rate, and properties of the environment are important control parameters that influence the outcome of dynamic self-assembly. Here we demonstrate that dispersions of magnetic microparticles confined at the air-liquid interface, and energized by a uniaxial in-plane alternating magnetic field, self-assemble into a variety of structures that range from pulsating clusters and single-particle-thick wires to dynamic arrays of spinners (self-assembled short chains) rotating in either direction. The spinners emerge via spontaneous breaking of the uniaxial symmetry of the energizing magnetic field. Demonstration of the formation and disaggregation of particle assemblies suggests strategies to form new meso-scale structures with the potential to perform functions such as mixing and sensing.

No MeSH data available.


Related in: MedlinePlus

Spontaneous rotational symmetry breaking in spinners phase.(a),(b) Imbalance of positive/negative vorticity generated by clockwise versus counterclockwise spinners at the air-liquid interface. The spinners phase was dynamically self-assembled at 29 Oe, 50 Hz in-plane alternating magnetic field. Vorticity imbalance was calculated as an integral of the vorticity field over the experimental surface window. Each instance of the data contained information about 102 spinners within the experimental image. While the ensemble of spinners constantly develops spontaneous fluctuations in the number of spinners with different sense of rotation demonstrated in (a), the overall long time trend shows no synchronization as illustrated in the histogram of the imbalance events (b). Solid line is a fit to a Gaussian function. (c) Imbalance in number of spinners with different sense of rotation as a function of time obtained from simulations (see Methods). Each time step corresponds to 1/6 of the excitation period of the powering field. The simulation data has been collected over much longer time frame compared to the experiment (two orders of magnitude difference). The inset shows the behavior of the order parameter in the time window comparable to the experimental one shown in (a). The results are in good qualitative agreement. (d) Histogram of the order parameter values as obtained from the simulation data shown in (c). Solid curve is a fit to a Gaussian function. The results indicate an absence of synchronization between spinners. (e), (f) Fourier spectra of the spinners order parameter obtained for the experimental data (e) and simulations (f). The same data as in (a) and (c) are used for analysis. Frequency is in units of inverse field periods. Solid curve in (e) is a running average over neighboring 5 data points to reduce the noise. The clear evidence of peaks in the spectra suggests a deterministic nature of the order parameter fluctuations.
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f5: Spontaneous rotational symmetry breaking in spinners phase.(a),(b) Imbalance of positive/negative vorticity generated by clockwise versus counterclockwise spinners at the air-liquid interface. The spinners phase was dynamically self-assembled at 29 Oe, 50 Hz in-plane alternating magnetic field. Vorticity imbalance was calculated as an integral of the vorticity field over the experimental surface window. Each instance of the data contained information about 102 spinners within the experimental image. While the ensemble of spinners constantly develops spontaneous fluctuations in the number of spinners with different sense of rotation demonstrated in (a), the overall long time trend shows no synchronization as illustrated in the histogram of the imbalance events (b). Solid line is a fit to a Gaussian function. (c) Imbalance in number of spinners with different sense of rotation as a function of time obtained from simulations (see Methods). Each time step corresponds to 1/6 of the excitation period of the powering field. The simulation data has been collected over much longer time frame compared to the experiment (two orders of magnitude difference). The inset shows the behavior of the order parameter in the time window comparable to the experimental one shown in (a). The results are in good qualitative agreement. (d) Histogram of the order parameter values as obtained from the simulation data shown in (c). Solid curve is a fit to a Gaussian function. The results indicate an absence of synchronization between spinners. (e), (f) Fourier spectra of the spinners order parameter obtained for the experimental data (e) and simulations (f). The same data as in (a) and (c) are used for analysis. Frequency is in units of inverse field periods. Solid curve in (e) is a running average over neighboring 5 data points to reduce the noise. The clear evidence of peaks in the spectra suggests a deterministic nature of the order parameter fluctuations.

Mentions: To quantify this effect we introduce an order parameter I related to the imbalance of spinners with different sense of rotation: I = (N+ − N−)/(N+ + N−). Here N+ and N- are the number of clockwise and counterclockwise spinners respectively. The emergence of complete global synchronization of the sense of rotation of spinners rotation would correspond to the order parameter values I = ±1; the completely random non-synchronized state would correspond to I = 0. The results of experimental and computational studies are illustrated in Fig. 5. Smaller number of particles in a simulation window (see Methods) than those used in experiments expectedly produce smaller amount of spinners per simulation frame (~10). Consequently, asymmetry in the number of spinners with different rotational direction results in a high magnitude of imbalance compared to the larger experimental system (~102 spinners).


Emergence of reconfigurable wires and spinners via dynamic self-assembly.

Kokot G, Piet D, Whitesides GM, Aranson IS, Snezhko A - Sci Rep (2015)

Spontaneous rotational symmetry breaking in spinners phase.(a),(b) Imbalance of positive/negative vorticity generated by clockwise versus counterclockwise spinners at the air-liquid interface. The spinners phase was dynamically self-assembled at 29 Oe, 50 Hz in-plane alternating magnetic field. Vorticity imbalance was calculated as an integral of the vorticity field over the experimental surface window. Each instance of the data contained information about 102 spinners within the experimental image. While the ensemble of spinners constantly develops spontaneous fluctuations in the number of spinners with different sense of rotation demonstrated in (a), the overall long time trend shows no synchronization as illustrated in the histogram of the imbalance events (b). Solid line is a fit to a Gaussian function. (c) Imbalance in number of spinners with different sense of rotation as a function of time obtained from simulations (see Methods). Each time step corresponds to 1/6 of the excitation period of the powering field. The simulation data has been collected over much longer time frame compared to the experiment (two orders of magnitude difference). The inset shows the behavior of the order parameter in the time window comparable to the experimental one shown in (a). The results are in good qualitative agreement. (d) Histogram of the order parameter values as obtained from the simulation data shown in (c). Solid curve is a fit to a Gaussian function. The results indicate an absence of synchronization between spinners. (e), (f) Fourier spectra of the spinners order parameter obtained for the experimental data (e) and simulations (f). The same data as in (a) and (c) are used for analysis. Frequency is in units of inverse field periods. Solid curve in (e) is a running average over neighboring 5 data points to reduce the noise. The clear evidence of peaks in the spectra suggests a deterministic nature of the order parameter fluctuations.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4374141&req=5

f5: Spontaneous rotational symmetry breaking in spinners phase.(a),(b) Imbalance of positive/negative vorticity generated by clockwise versus counterclockwise spinners at the air-liquid interface. The spinners phase was dynamically self-assembled at 29 Oe, 50 Hz in-plane alternating magnetic field. Vorticity imbalance was calculated as an integral of the vorticity field over the experimental surface window. Each instance of the data contained information about 102 spinners within the experimental image. While the ensemble of spinners constantly develops spontaneous fluctuations in the number of spinners with different sense of rotation demonstrated in (a), the overall long time trend shows no synchronization as illustrated in the histogram of the imbalance events (b). Solid line is a fit to a Gaussian function. (c) Imbalance in number of spinners with different sense of rotation as a function of time obtained from simulations (see Methods). Each time step corresponds to 1/6 of the excitation period of the powering field. The simulation data has been collected over much longer time frame compared to the experiment (two orders of magnitude difference). The inset shows the behavior of the order parameter in the time window comparable to the experimental one shown in (a). The results are in good qualitative agreement. (d) Histogram of the order parameter values as obtained from the simulation data shown in (c). Solid curve is a fit to a Gaussian function. The results indicate an absence of synchronization between spinners. (e), (f) Fourier spectra of the spinners order parameter obtained for the experimental data (e) and simulations (f). The same data as in (a) and (c) are used for analysis. Frequency is in units of inverse field periods. Solid curve in (e) is a running average over neighboring 5 data points to reduce the noise. The clear evidence of peaks in the spectra suggests a deterministic nature of the order parameter fluctuations.
Mentions: To quantify this effect we introduce an order parameter I related to the imbalance of spinners with different sense of rotation: I = (N+ − N−)/(N+ + N−). Here N+ and N- are the number of clockwise and counterclockwise spinners respectively. The emergence of complete global synchronization of the sense of rotation of spinners rotation would correspond to the order parameter values I = ±1; the completely random non-synchronized state would correspond to I = 0. The results of experimental and computational studies are illustrated in Fig. 5. Smaller number of particles in a simulation window (see Methods) than those used in experiments expectedly produce smaller amount of spinners per simulation frame (~10). Consequently, asymmetry in the number of spinners with different rotational direction results in a high magnitude of imbalance compared to the larger experimental system (~102 spinners).

Bottom Line: The energy injection rate, and properties of the environment are important control parameters that influence the outcome of dynamic self-assembly.The spinners emerge via spontaneous breaking of the uniaxial symmetry of the energizing magnetic field.Demonstration of the formation and disaggregation of particle assemblies suggests strategies to form new meso-scale structures with the potential to perform functions such as mixing and sensing.

View Article: PubMed Central - PubMed

Affiliation: Complex Matter Department, Jozef Stefan Institute, Jamova 39, 1000 Ljubliana, Slovenia.

ABSTRACT
Dissipative colloidal materials use energy to generate and maintain structural complexity. The energy injection rate, and properties of the environment are important control parameters that influence the outcome of dynamic self-assembly. Here we demonstrate that dispersions of magnetic microparticles confined at the air-liquid interface, and energized by a uniaxial in-plane alternating magnetic field, self-assemble into a variety of structures that range from pulsating clusters and single-particle-thick wires to dynamic arrays of spinners (self-assembled short chains) rotating in either direction. The spinners emerge via spontaneous breaking of the uniaxial symmetry of the energizing magnetic field. Demonstration of the formation and disaggregation of particle assemblies suggests strategies to form new meso-scale structures with the potential to perform functions such as mixing and sensing.

No MeSH data available.


Related in: MedlinePlus