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Particle Dynamics: Brownian Diffusion

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Particle Dynamics: Brownian Diffusion Particle Dynamics: Brownian Diffusion Prof. Sotiris E. Pratsinis Particle Technology Laboratory Department of Mechanical and Process Engineering, ETH Zürich, Switzerland www.ptl.ethz.ch 1 or or nucleation inception or or condensation v surface growth or evaporation v flocculation coalescence aggregation sintering chemical bonding agglomeration Aerosol-based Technologies in Nanoscale Manufacturing: attachement from Functional Materials to Devices through Core physical adhesion Chemical Engineering, AIChE J., 56, 3028-3035 (2010) Particle Dynamics Coagulation Fragmentation Convection Shrinking in Growth by evaporation by condensation or dissolution or chemical reaction Convection out Diffusion Settling 3 Theory: Population Balance Equation n dv n u Dn n c n t v dt convection diffusion growth external force 1 v ~v,v ~v n ~v n v ~v d~v v,~v nv n~v d~v 2 0 0 coagulation Sv n v v,~v Sn ~v d~v v fragmentation u = gas velocity vector ux,uy,uz n u un n u D = particle diffusivity 0 continuity c = velocity of particles of size v (e.g. settling) = coagulation rate S = fragmentation rate = fragment size distribution 4 Mean Free Path: Continuum vs. Free-molecule regime The mean free path of a gas, , is the average distance traveled by gas molecules between their collisions. When particles are much larger than (e.g. dp > 10), they do not sense individual collisions with molecules feeling a “continuum” so particle motion takes place in the so-called continuum regime and described by the standard or classic Navier-Stokes equations, the gospel of engineering. When particles are much smaller than (e.g. dp < ), they are in the so-called free-molecule regime and their motion is described by the kinetic theory of gases. Inbetween, interpolations are devised specific to the process (e.g. for diffusion, coagulation or condensation) 5 1. DIFFUSION Particles suspended in a fluid medium exhibit a haphazard dancing motion Botanist Robert Brown discovered that this motion was a general property of matter regardless of its origin (dust vs. pollen) Hands-on experiment resembling the motion of oil droplets in water with ball bearings and metal rings on a vibrating table at the Museum of Fine Arts at the San Francisco Exploratorium organized by Dr. Frank Oppenheimer (brother of Robert the father of the Atomic Bomb) 6 Diffusion is the net migration of particles from regions of HIGH to LOW concentration Net rate of transport into that element: 7 Friedlander, S.K., Smoke, Dust and Haze, Chapter 2, Oxford Press, 2nd Edition, New York, 2000 The rate of change of the number of particles per unit volume (& size), n, in the elemental volume δxδyδz is: From experimental observations: Fick’s first law Substituting in the above gives second Fick’s law: Coefficient of Diffusion or Diffusivity, D 8 D = f (particle size and gas properties) Consider particle transport in one dimension, x Release equally sized particles, N0, at t=0 and observe the n distribution in space and time For the boundary conditions at x = 0, x = ∞ & t =0, the particle concentration distribution in x,t is 9 The mean square displacement of the particles from x=0 at time t is: We can measure by putting spheres in a liquid and follow their motion through a chequered glass. 10 The goal is to relate the mean square displacement of a particle with the energy required for this “job”. Force balance on a particle in Brownian motion: Now multiply both sides of eq. (5) by the displacement x and divide by m. For a single particle: du f F() t x ux x (6) dt m m 11 define as β = f/m and A = F(t)/m and remember that: Using these expressions eq. (6) becomes Integrate from t=0 to t and obtain: where t′ is a variable of integration representing time. 12 Average over all particles: Since there is no correlation between displacement x and “kick”, A, the second term of eq. (7) vanishes: You can also write: 13 Because the derivative of the mean over particles with respect to time is equal to the mean of the derivative: From eq. (8) & (9): Integrate over time from t = 0 to t for t >> 1/β (or β t >> 1): 14 Invoke the equipartition of energy, meaning that the kinetic energy of particles is equal to the kinetic energy of the surrounding gas molecules: This is the Stokes-Einstein expression for D. It relates D to the properties of the fluid and the particle through the friction coefficient. 15 Perrin’s (1910) study allowed calculation of the Avogadro number NAV . By observing the motion of an emulsion he calculated the number of (attacking) molecules: where R is the gas constant He gave an experimental proof of the kinetic theory by measuring the net displacement 23 Modern methods show that NAV=6.023×10 molecules/mol 16 Friction coefficient mean free path of gas medium with ρ : density of the medium (e.g. air) m1: molecular mass of the medium In the continuum regime (dP >> λ ): f = 3dP In the free molecular regime (dP << λ ): with a: accomodation coefficient ≈ 0.9 In the entire range: with C: Cunningham correction factor 17 Coefficients A1, A2, and A3 are empirical constants that have been obtained by measuring the settling velocities of particles in various gases. Table 1 gives these constants for various gases (Rader, D. J., Momentum slip correction factor for small particles in nine common gases, J. Aerosol Sci., 21 (1990), 161-168) The ratio of the mean free path of the gas and the particle radius is the Knudsen number Kn = 2λ/dp. The Cunningham correction factor does not change very much with different gases for the same Kn (Table 2). 18 Diffusion and sedimentation dominate the particles‘ motion at opposite size regimes (Table 3). 19 DIFFUSION during LAMINAR PIPE FLOW Entrance length: L = 0.04dRe (laminar flow) d : pipe diameter Re : Reynolds-number The momentum boundary layer develops rapidly while the concentration boundary layer follows: 20 Separation of variables: Result: So the average particle concentration is defined as: And in general it is given as: 2 Where Gk and λk are given in Table 3.1 in the book by Friedlander (1977). The above ratio is called also the particle penetration, P, and it is defined as: 21 Penetration curves for particle diffusion to pipe walls Penetration versus deposition parameter for circular tubes and rectangular cross section channels: D: particle Diffusivity, L: tube or channel length, Q: gas flowrate, h: interplate 22 distance, W: channel width (Hinds, 1982) 23 Rowell, J. M., Scientific American, October 1986, 147. MacChesney, J. B., O’Connor, P. B. and Presby, H. M., 1974, A new technique for preparation of low-loss and graded index optical fibers. Proc. IEEE 62, 1280-1281. Energy balance 26 Mass balance of SiCl4 Mass balance of SiO2 27 Evolution of SiO2 Particle Dynamics during MCVD through the Moments of the SiO2 size distribution 28 29 J. Aerosol Sci., 20, 101-111 (1989) 31 32 o Tmax = 1700 C o Tmax = 1500 C 33 -----Neglecting H 34 Impact of simplifications Radial Evolution of SiO2 mass concentration on deposition efficiency K.S. Kim, SEP, "Modeling and Analysis of Modified Chemical Vapor Deposition of Optical Fiber Preforms", Chem. Eng. Sci., 44, 2475-2482 (1989). 35 Impact of carrier gas Impact of SiCl4 conc’n composition on the evolution and MCVD gas flowrate of deposition efficiency on deposition efficiency ------- 1x10-6 mol/cm3 - - - - 5x10-6 // K.S. Kim, SEP, "Modeling and Analysis of Modified Chemical Vapor Deposition of Optical Fiber Preforms", Chem. Eng. Sci., 44, 2475-2482 (1989). 36 The effect of chemical Comparison with equilibrium on halide experimental GeCl4 conversion and oxide equilibrium data deposition efficiency during MCVD K.S. Kim, SEP, "Co-deposition of SiO2-GeO2 during Production of Optical Fiber Preforms by Modified Chemical Vapor Deposition", Intl. J. Heat Mass Trans., 33, 1977-1986 (1990). 37 Comparison with MCVD data @ AT&T Bell Labs 38.
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