Colloid Transport Project Project Advisors: Timothy R. Ginn, Professor, Department of Civil and Environmental Engineering, University of California Davis, Daniel M. Tartakovsky, Professor, Department of Mechanical and Aerospace Engineering University of Patricia J. Culligan, Professor, Department of Civil Engineering and Engineering Mechanics, Columbia

Filtration (sorption, deposition, or attachment) Basic Goal Examine the transport of a dilute suspension (of micron sized particles) in a saturated, rigid porous medium under uniform flow Advection Dispersion Filtration (sorption, deposition, or attachment)

Challenge ∂S/∂t…. Classic mathematical models used to describe ∂S/∂t are inadequate in many cases - even in very simple systems

Problems Involving Particle Transport through Porous Media Water treatment system Deep Bed Filtration (DBF) Membrane-based filtration Transport of contaminants in aquifers Colloidal particle transport Transport of microorganisms Pathogen transport in groundwater Bioremediation of aquifers Clinical settings Blood cell filtration Bacteria and viruses filtration Why is the discrete particle transport in porous media important in the environment and what are the applications? Water/wastewater purification system uses the particle filtration method. Colloidal particle transport in soil is an important topic in environmental engineering. Also, the principles of microbial transport in porous media are applied to pathogen transport, bioremediation, and bacterial filtration. In addition, some clinical settings use the filtration theory, too.

Particle Sizes 10-10 10-9 10-8 10-7 10-6 10-5 10-4 10-3 10-2 (diameter, m) 1 Å 1 nm 1 mm 1 mm 1 cm Soils Clay Silt Sand Gravel Microorganisms Viruses Bacteria Protozoa Red blood cell Blood cells White blood cell Atoms, molecules This figure illustrates the examples and sizes of discrete particles. The particles are in the sub-miron to micron range. Atoms Molecules Macromolecules Colloids Suspended particles Depth-filtration range Electron microscope Light microscope Human eye

Particle Filtration through a Porous Medium Particle suspension injection at C0 Porous Medium C/Co < 1 C/Co Fraction of particle mass is permanently removed by filtration L Particle filtration is basically how many particles become immobile and stay inside porous medium while they are transporting through a porous medium. For example, particle suspension of the particle concentration C0 is injected through a porous medium of length L, and the particle breakthrough concentration is monitored vs time like this figure. Then, it is the conventional way of measuring the filter efficiency of the medium that the filtration coefficient is calculated by comparing the inject concentration and the breakthrough concentration. Particle breakthrough

Idealized Description of Particle Filtration Clean-bed “Filtration Theory” Single collector efficiency Single “collector” represents a solid phase grain. A fraction h of the particles are brought to surface of the collector by the mechanisms of Brownian diffusion, Interception and/or Gravitational sedimentation. A fraction a of the particles that reach the collector surface attach to the surface The filtration theory, then, takes one cell and the flow field, separetely, and considering the three colliding mechanisms of moving particles onto the colletor grain, the approximate analytical solution has been obtained for the single collector efficiency. Then, the single collector efficiency is now related to the macroscopic parameter of the whole medium such as the filtration coefficient or first-order deposition rate. Filtration coefficient First-order deposition rate The single collector efficiency is then scaled up to a macroscopic filtration coefficient, which can be related to first-order attachment rate of the particles to the solid phase of the medium.

Particle Filtration through a Porous Medium Particle suspension injection at C0 Porous Medium C/Co < 1 C/Co L Particle filtration is basically how many particles become immobile and stay inside porous medium while they are transporting through a porous medium. For example, particle suspension of the particle concentration C0 is injected through a porous medium of length L, and the particle breakthrough concentration is monitored vs time like this figure. Then, it is the conventional way of measuring the filter efficiency of the medium that the filtration coefficient is calculated by comparing the inject concentration and the breakthrough concentration. Particle breakthrough katt (and ah) is assumed to be spatially constant and dependent upon particle-solid interaction energies (DLVO theory) and system physics

Motivation for Work Growing body of literature that indicates that katt decreases with transport distance - points to inadequacies in the filtration-theory Various solutions to fixing these inadequacies More complex macroscopic models? Modeling at the micro-scale? Examine solutions in context of a unique data set that has resolved particle concentrations in the interior of a porous medium in real time

Generation of Data Set Translucent porous medium – glass beads saturated with water Laser induced fluorescent particles Micro-size Fluorescent Particles: Excitation wavelength 511-532nm, Emission wavelength 570-595nm. Laser : 6W Argon-ion Laser Digital image processing Captured images in real-time with CCD camera Image processing software The new visualization technique was developed involving a translucent porous medium, laser induced fluorescent particles and digital image processing. The translucent porous medium was constructed with glass beads saturated with water. Micro-size fluorescent particles were used. The particles are excited by 511-532nm wavelength, which is blue-green range, and emit 570-595nm wavelength, green-yellow light. An 6W argon-ion laser was used to excite the particles. The emitted light from the particles was capture by a CCD camera with an optical filter which allows only the emission wavelength. And the capture images were enhanced and analyzed by an image processing software. This figure illustrates how the visualization technique works. This is the medium, and this is the captured image, and this is an enhanced image by the software.

Particles Acrylic particles with organic fluorescent dyes (fluorecein, rhodamine) embedded. Specific gravity = 1.1 Particle size Range: 1-25 mm, d50=7mm Surface potential zeta-potential = -109.97mV. Unlikely to attach to the glass bead surface due to the repulsive electrostatic force The fluorescent particles are acrylic particles with organic dyes embedded in them. The excitation and emission wavelengths are like this. This is an SEM picture of the particles. The specific gravity is 1.1, very close to water. The particle size is 1-25 micrometer and d50 is 7 micrometer, and this is the particle size distribution curve. I measured the zeta-potential for the surface potential of the particles. The zeta-potential was about -110mV. This showed us that the particles are very unlikely to attach to the glass bead surface, because the soda-lime glass bead surface is also negative, usually reported around -60mV. This is a very interesting point.

Experimental Set Up This is a picture of the whole experimental set up, located in building 48. The medium is placed here, and this is the laser outlet and this is the spinning mirror mounted on the traversing actuator. This is the camera with the optical filter. The laser head is connected by the optical fiber with the outlet and the camera is connected with a computer. The whole set up was also covered by a black cloth.

Particle Fluorescence is related to Particle Concentration Some calibration processes preceded to get the accurate particle concentration out of the light intensity data. This is the conversion of the light intensity to the particle concentration. The particle concentration had a linear relationship with the light intensity. Also, there was some optical distortion found, that was caused by the camera and the lens. So, how the light intensity captured by the camera varied was calibrated vertically and horizontally. Then, pixel-by-pixel calibration factor was calculated for each captured image. Particle concentration had a linear relationship with fluorescent light intensity. Pixel by pixel calibration eliminated the optical distortion caused by the camera and the lens.

Basic Experiment Inject 10 Pore Volumes (PVs) of particle suspension at C = 50 mg/l Follow with injection of 10 Pore Volumes (PVs) of non-particle suspension at C = 0 mg/l Series of data for tests in similar porous media at difference values of uf

Data Available: Particle Breakthrough Curve at Column Base Particle density versus time in fluid phase at base - C versus t at a fixed z Based on the two characteristics, the breakthrough data were matched with the Two-Site Model, which has irreversible attachment site and reversible attachment site. And the model matched the experimental data pretty well.

Particle Concentration Inside the Medium (C + S) versus time at various locations within the medium Now, let’s look into the particle behavior inside the medium. This is an example of the particle concentration measurements during a reference experiment at each location. This is close to the top of the medium, this is next and next… and this is close to the bottom of the medium. In these figures, the particles were collected inside the medium and the transport was retarded. In other words, the firm-collection and non-firm collection and reentrainment are found. And one more thing in this graph, these solid lines are the model calculations after matching the breakthrough data. You see that the model calculation underestimates at the top and kind of overestimate at the bottom, so the local particle distribution was not well matched with the model.

Microscopic Observations: Physical Insight Flow direction to (c) Particle injection (d) to (e) Particle flushing Particles are irreversibly attached at the solid-solid contact points (contact filtration) and at the top surface of the beads (surface filtration). The particles are also reversibly attached at the surface of the beads and possibly at the contact points. The microscopic observations revealed very interesting facts. I want to show you the movie of the microscopic motion of the particles captured during a downward experiment with the rough beads at the slow velocity. Particles are injected from the start and after half of the movie, the medium is flushed with no-particle fluid. As you can see, the particles were collected at two locations, at the top surface of the glass beads and at the solid-solid contact points. Some of the particles that were collected at the top surface moved back to the pore fluid and continued flowing. So, the entrapment is divided into contact entrapment and surface entrapment. The hindrance is seen at the surface, that is surface hindrance, and maybe there can be some contact hindrance, too.

Contact Filtration Particles moving near bead-bead contact points were physically strained. Bead-bead contacts Bead- glass plate contacts Flow direction If we look into the behavior in detail one by one, the contact entrapment is the particle entrapment, where the particles were physically strained at contact points. From this figure, these are the bead-glass plate, that is placed on the inside wall of the box, contact points, and these are bead-bead contact points. The particles were collected at the upper parts of the contacts making crescent shapes. Cushing and Lawler first introduced the contact straining as an important physical particle filtration behavior using 3-dimensional particle trajectory analysis numerical simulations, but this is the first time that the contact entrapment is observed experimentally. The collection mechanisms is the physical straining by size. And what is the approaching mechanism? My new hypothesis is gravity, and this will proved later in this presentation.

Surface Filtration Flow direction Some of the particles that approached the surface of the beads became “irreversibly” attached. The surface entrapment is the particle entrapment, where some of the particles that approached near the surface of the beads were firmly collected on the surface. Then, what is the collection mechanism? As I said in the material property, the surface potentials of the particles and the beads are highly negative, so they are repulsive. So, there should be some physical mechanism that can collect the particles. So, it is hypothesized that the surface roughness of the glass beads holds the particles against the drag force. Also, the approaching mechanisms here is hypothesized to be gravitational sedimentation. Considering the highly negative zeta-potentials of the particles and beads, surface filtration must be “physical” - hypothesized that surface roughness held the particles against the drag force.

Project Tasks Understand the data set Model data using traditional filtration-theory Understand the inadequacies of this theory Model data set using “more-complex” macroscopic balance equation Can any of the coefficients in this balance equation be given a physical meaning? Can micro-scale modeling techniques be applied and used to capture some of the observed behavior

What you will be given Data sets for three experiments - each at different average fluid velocity Experimental information - set-up plus parameters etc. A library of background literature Guidance, encouragement, hints (?)

What you will Deliver? Project report = technical article that discusses the shortcomings of existing modeling approaches and explores avenues for improvements based on (a) macroscopic modeling approaches and (b) microscopic approaches