Effect of Collective Molecular Reorientations on Brownian Motion of Colloids in Nematic Liquid Crystal

Turiv, Taras; Lazo, Israel; Brodin, A.; Lev, B. I.; Reiffenrath, Volker; Nazarenko, V. G.; Lavrentovich, Oleg D.

doi:10.1126/science.1240591

Cited by 111 publications

(131 citation statements)

References 40 publications

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“…19 In addition, it is known that the Brownian motion of colloids is related to the carrier liquid viscosity. 20 The relation has been revealed between relaxation of field-induced structure and ferrofluid viscosity from field-induced transmission of light in ferrofluids of tunable viscosity. 21 However, according to the present point, the difference in viscosity may and undoubtedly does affect the time of establishing the stationary magnetization 19 but by no means is able to affect it's value.…”

Section: Introductionmentioning

confidence: 99%

Investigation into loss in ferrofluid magnetization

Gong

Lin

et al. 2014

AIP Advances

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Ferrofluids containing γ-Fe2O3/Ni2O3 nanoparticles (not chemically treated) were synthesized using water and mixed water–glycerol as carrier liquid and the ferrofluid viscosity was modified by varying the glycerol content in the carrier liquid. The apparent magnetization of the ferrofluids decreased with increasing glycerol content. The loss in magnetization is described by the ratio of effective magnetic volume fraction to physical volume fraction of nanoparticles in the ferrofluids as a characteristic parameter. We ascribe the loss to the formation of “dead aggregates” having a ring-like structure of closed magnetic flux rather than to any chemical reaction. Such dead aggregates exist in zero magnetic field and do not contribute to the magnetization in the low or high field regime, so that the effective magnetic volume fraction in the ferrofluids decrease. An increase in carrier liquid viscosity is similar to a weakening of the thermal effect, so the number of dead aggregates increases and the magnetization decreases in inverse proportion to the viscosity. This relationship between the apparent magnetization and ferrofluid carrier liquid viscosity can be termed the “viscomagnetic effect”.

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Section: Introductionmentioning

confidence: 99%

Investigation into loss in ferrofluid magnetization

Gong

Lin

et al. 2014

AIP Advances

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“…Even at the single particle level, the thermally-driven motion of nonspherical particles (98) and of particles in anisotropic fluids (99) continues to reveal surprises, nearly 100 years after Perrin's experiments. The hydrodynamic interactions between these particles can not only select for certain phases (41), but can also result in different collective phenomena when the driving forces are intrinsic or extrinsic energy sources rather than thermal fluctuations (100).…”

Section: Looking Forwardmentioning

confidence: 99%

Colloidal matter: Packing, geometry, and entropy

Manoharan

2015

Science

484

390

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“…On the contrary, asymptotically superdiffusive walkers 2a,e). It is typically relevant to tracers moving in nematics 11 or solutions of non-adsorbing polymers 27 . (2) The choice ψ(t) = Kt 2H where 0 < H < 1 and K is a positive transport coefficient (Fig.…”

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confidence: 99%

Mean first-passage times of non-Markovian random walkers in confinement

Guérin¹,

Levernier²,

Bénichou³

et al. 2016

Nature

135

124

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The first-passage time (FPT), defined as the time a random walker takes to reach a target point in a confining domain, is a key quantity in the theory of stochastic processes 1 . Its importance comes from its crucial role to quantify the efficiency of processes as varied as diffusion-limited reactions 2,3 , target search processes 4 or spreading of diseases 5 . Most methods to determine the FPT properties in confined domains have been limited to Markovian (memoryless) processes 3,6,7 . However, as soon as the random walker interacts with its environment, memory effects can not be neglected. Examples of non Markovian dynamics include single-file diffusion in narrow channels8 or the motion of a tracer particle either attached to a polymeric chain 9 or diffusing in simple 10 or complex fluids such as nematics 11 , dense soft colloids 12 or viscoelastic solutions 13,14 . Here, we introduce an analytical approach to calculate, in the limit of a large confining volume, the mean FPT of a Gaussian non-Markovian random walker to a target point. The non-Markovian features of the dynamics are encompassed by determining the statistical properties of the trajectory of the random walker in the future of the first-passage event, which are shown to govern the FPT kinetics. This analysis is applicable to a broad range of stochastic processes, possibly correlated at long-times. Our theoretical predictions are confirmed by numerical simulations for several examples of non-Markovian processes including the emblematic case of the Fractional Brownian Motion in one or higher dimensions. These results show, on the basis of Gaussian processes, the importance of memory effects in first-passage statistics of non-Markovian random walkers in confinement.It has long been recognized that the kinetics of reactions is influenced by the properties of the transport process that brings reactants into contact 1,2 . Transport can even be the rate limiting step and in this diffusion controlled regime, More precisely, we consider a non-Markovian Gaussian stochastic process x(t), defined in unconfined space, which represents the position of a random walker at time t, starting from x 0 at t = 0. As the process is non-Markovian, the FPT statistics in fact depends also on x(t) for t < 0. For the sake of simplicity, we assume that at t = 0 the process of constant average x 0 is in stationary state (see SI for more general initial conditions), with incrementsThe process x(t) is then entirely characterized by its Mean Square DisplacementSuch a quantity is routinely measured in single particle tracking experiments and in fact includes all the memory effects in the case of Gaussian processes. At long times, the MSD is assumed to diverge and thus, typically, the particle does not remain close to its initial position. Last, the process is continuous and non smooth 25 ( ẋ(t) 2 = +∞), meaning that the trajectory is irregular and of fractal type, similarly to the standard Brownian motion. Note that the class of random walks that we consider here covers a broad spe...

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Effect of Collective Molecular Reorientations on Brownian Motion of Colloids in Nematic Liquid Crystal

Abstract: , with the exponent α either smaller than 1 (subdiffusion) or

Cited by 111 publications

References 40 publications

Investigation into loss in ferrofluid magnetization

Investigation into loss in ferrofluid magnetization

Colloidal matter: Packing, geometry, and entropy

Mean first-passage times of non-Markovian random walkers in confinement

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