1.2 Dynamic and structural behavior
1.2.2 Diffusion and deterministic transport
Microscopic particles in a liquid exhibit random motion that can be ascribed to the thermal fluctuations of the solvent (Brownian motion). Quantitatively, this diffusive transport is captured by the mean-square displacement (MSD) of the particles in the experiment:
(∆r(t))2
= 2d·Dst (2.12)
dis the dimensionality of the system under consideration, andDs is the self-diffusion coefficient of a tracer particle. The diffusion coefficientDs can be expressed for a single, spherical particle far away from any solvent interface through the Stokes-Einstein relationD0 =kBT /(6πηa). Therefore, the diffusion coefficient quantifies, on average, how far the thermal energy of the systemkBT can transpose a particle against the friction of the solvent (η= solvent viscosity,a= particle radius). In the vicinity of a surface, the diffusion coefficient diminishes drastically, owed to the hydrodynamic interactions (see below) with the surface ( q.v. figure 4.14, chapter 4). In chapter 4, we will clarify why the linearity in time of the MSD, usually found in two or three dimensional systems, brakes down for single-file systems.
The transport of a particle through a solvent can be described phenomenological by the Langevin equation of motion by making assumptions about the character of the Brownian motion.
Another possibility is the Smoluchoski-equation, that is the equation of motion for overdamped systems in phase space. Both concepts will be explained in section 4.2.2, where we will apply the Smoluchoski-formalism in the inquiry about the diffusive properties of one-dimensional systems.
For the dynamic description of the driven systems in chapter 5, we employ both the Langevin-and Smoluchoski-formalism.
The Reynolds number (RE) is the most important dimensionless number in fluid dynamics and provides a criterion for determining dynamic similarity. Where two geometrically similar objects in perhaps different fluids with possibly different flow rates have similar fluid flow around them, they are said to be dynamically similar. The RE is defined as RE = ρSvSσ/η, where ρS is the fluid density,vS the mean fluid velocity,σa characteristic length scale (e.g. particle diameter) and η the fluid viscosity. All the measurements of colloidal science, this work included, are performed in the low Reynolds number regime (RE ≈ 10−4). For RE ≤ 10 the motion of the particles proceeds in a laminar flow field of the solvent without causing any turbulence. This is important for the validity of the description we will give for the hydrodynamic interactions in our colloidal systems.
1.2. DYNAMIC AND STRUCTURAL BEHAVIOR 17
In colloidal science one often reads of the Peclet number (PE). The PE is like RE, a dimension-less number. It is the product of system length σ and fluid velocity vS, divided by diffusivity D (P e=σ vS/D). The PE indicates if the particle transport in a colloidal system is mostly through external driving force (P E 1) or through diffusion (P E 1). For large PE, the Brownian motion can be neglected in the description of particle motion through a solvent. In chapter 5 we will study the transition of a driven system from a deterministic regime with P E 1 to a regime where we find a sequence of regimes with P E 1 andP E 1 respectively.
Chapter 2
Experimental setup
The aim of this study is to examine the behavior of one-dimensional systems. We will elaborate especially on two different cases: the equilibrium system, where the particles exhibit pure diffusive transport ( chapters 3, 4), and the out-of-equilibrium situation of strongly-driven particles (chapter 5).
To emulate one-dimensionality in our colloidal system we had to form narrow channels which confine the particle motion effectively to one-dimension by diminishing their transverse fluctuations in the channel to less than the particle diameter. For this purpose, we used an optical trap because it gives the necessary flexibility in the selection of channel width and structure without the inevitable slowing down of particles in topographic channels due to hydrodynamic interactions with the walls. For our experiments we worked with circular channels, i.e. periodic boundary conditions. Static circular light fields can be created through the use of holographic masks (see elsewhere [LRHT00]) or be imitated by a rapid motion of a focused laser beam along a circular line [FSL95]. We employed in our measurements the second option of the dynamic single optical trap, since it allows greater variations in laser intensities and, if necessary, an additional constant driving of the particles along the channel.
In the beginning of this chapter we will explain why the fast motion of a single optical trap mimics a static channel and supplies a variable driving force at the same time. Then we will discuss how this principle is transposed in the components of our experimental setup. Thereby, for the different chapters of this work we will take special account of the variations in the setup and their particular consequences.
2.1 Creating topography with scanned optical tweezer
A simplified setup in figure 1.1 explains the basic principle of a scanning optical tweezer. A laser beam with a gaussian-shaped intensity profile is focused by a microscope objective into a cuvette with suspended dielectric particles. Before the objective, the laser gets deflected by two galvanometric mirrors whose motion is controlled by computer software. For example, the deflections can be such that the laser focus moves along a circle of radius Rparallel to the bottom of the substrate. As described in the previous chapter, the particles are attracted by the intensity gradient of the focus.
Faucheux et al.[FSL95] studied the influence of an optical trap scanned along a circular line on a single particle. Chiefly, they analyzed the effect of the laser power and the scanning speed of laser focus on the particle motion. They observed that the particle stayed always on the line followed by the laser focus (see figure 1.2, left). On the other hand, they discovered three regimes of the particle mean angular frequency νP (or velocity vP = 2πRνP) depending on the angular scanning frequencyνT of the mirrors. The three regimes are pointed out through the vertical lines
20 CHAPTER 2. EXPERIMENTAL SETUP
Figure 1.1. Rotation of an optical trap along a circular line in the experimental setup.
and the numbering above the graph in figure 1.2 (right).
In all three regimes the particles are radially trapped. The frequency of the focus is always high enough to prevent the particle to diffuse perpendicular to the circle, more than a small fraction of its diameter, before the laser trap returns and pulls the particle back into the focus.
In the first regime I, the motion of the particle is locked to the motion of the trap (νP =νT).
Once the particle is tweezed, it does not escape from the focus anymore. The second regime II reveals a reciprocal proportionality betweenνP andνT. The trap is not strong enough to withstand the viscous resistance of the fluid more than the time needed to pull the particle out of the potential well of the laser beam. The laser still drags the particle along the circle for a short distance every time it passes. The mean distance the particle follows the beam depends on the focus speed and the statistical fluctuations of the solvent. Although the resistence times of the particle in the trap are statistically distributed, the mean particle velocityvP is still deterministic. This is not surprising since the potential depth of the single trap ( by Faucheux et al. 250kBT) is adjusted to be much deeper than the thermal activation through the solvent. Faucheux demonstrates that the thermal fluctuations can even be neglected in the theory and one still gets a quantitative description of the experimental results. As the focus speed still increases, the mean angular velocityvP becomes zero in the third regime III. The particle remains confined on the circle, since it is always pulled back to the centerline radially by one or the other side of the passing gaussian intensity profile.
But the focus is now to fast to push or pull the particle away from the position it has reached by diffusion along the circular line. The particle behaves as if it would diffuse freely inside a ring channel.
In chapter 3 we will employ regime III to study the structure of many-particle systems. We will also employ regime III in chapter 4 to inquire into the diffusive behavior of single-file sys-tems. In chapter 5 we will investigate the steady-state properties of constantly driven particles in unstructured and structured channels. For the driving, we will make use of the constant mean particle angular velocityvP of the regime II.
Faucheux et al. solved the equation of motion of a single particle along the circle circumference x in regime II. They obtained the following mathematical relation between the mean particle
2.1. CREATING TOPOGRAPHY WITH SCANNED OPTICAL TWEEZER 21
Figure 1.2. Left: Trajectory of a single particle center of mass. Recording time 60s. Trap rotation frequency 14 Hz. Right: The particle mean angular frequency νp as a function of the trap angular frequency νT for three different laser powers P(P0 (crosses), 2·P0 (triangles), 4.7·P0 (circles)). From reference [FSL95].
velocity vP and the angular frequency of the laser focus νT in the referential frame of the trap:
vP = 1 νT
1 (2πR)2
Z Xb
Xa
F(x) mγ
2
dx (1.1)
with mγvT > maxF(x) (large velocity case) m := mass of the particle
γ = 6πηa/m (damping rate) R := radius of the light circle
a := particle radius
η := viscosity of the solvent
F(x) = (−∂/∂x)U(x) (force connected with the trapping potential of the focus) Xb−Xa = width of single trap potential
This equation clearly indicates an inverse proportionality between the mirror motion and the particle drift along the circular line, i. e. vp ∝νT−1.
The result 1.1, together with calculations of Tlusty et al. [TMBZ98], is also an elegant way to determine the potential depth of the single trap and the laser intensity in the focus from the mean angular velocity vP of a single, driven particle. Faucheux et al. showed that the potential of a single trap can be approximated by a triangular potential (see figure 1.3) of width 2X0 and depth VF ocus, leading to the same result for the mean particle velocity vP. For a triangular potential,
22 CHAPTER 2. EXPERIMENTAL SETUP
Figure 1.3. Representation of a single optical trap with a harmonic or triangular potential respectively.
equation 1.1 simplifies to:
vP ≈ 1 νT
1
(2πR)22· 1 X0
VF ocus 6πηa
2
2·X0 := width of single laser trap potential VF ocus:= single laser trap potential depth
(1.2)
From this equation we obtain immediately the potential depth VF ocus of the laser trap, if we measure the mean particle velocity vP. 2X0 corresponds to the beam waist ω0 for the Gaussian distributed laser light intensity. As an example, we arrive at a potential depth for our single laser trap of VF ocus = 4500kBT for the experimental parameters of chapter 5 (vP = 7µm/sec, νT = 76Hz, X0 = 0.3µm, R = 9.87µm, a = 1.5µm, η = 1.2·103 N·secm2 ). The value for VF ocus can be used in a next step to calculate the intensity of the laser beam in the focus. With equation 1.3 (Tlusty et al. [TMBZ98]), we can derive the energy density of the beam 4πε0I.
VFocus
4πε0 ≈(2π)3/2αIω03 aω0 (1.3)
4πε0I := Energy density of the laser beam ω0 := beam waist
α := εP εS −1
εP := dielectric constant of the particle εS := dielectric constant solvent
Finally, the laser power of the focused beamP is equal to 4πε0I·c·π·ω02, wherecis the speed of light and π·ω02 the focus size. In our experiment, the beam waist ω0 = 0.6µm, the dielectric constants of the particle εP = 1.39, and of the solvent εS = 1.37, lead to a laser power of about 210mW in the single trap. This is consistent with Faucheux’s intensity estimation in the focus of 10mW for his laser trap potential with a depth of 250kBT and a width of about 2µm.